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Presentation: Architecting For Focus, Flow, and Joy: Beyond The Unicorn Project

MMS Founder
MMS Gene Kim Michael Nygard Carin Meier

Article originally posted on InfoQ. Visit InfoQ

Transcript

Kim: I’ve had the privilege of studying high performing technology organizations since 1999. That was a journey that started for me back when I was a CTO and founder of a company called Tripwire in the information security and compliance space. Our goal was to study this amazing organization that had the best project duty and performance, the best operational stability and reliability, as well as the best posture of security and compliance. As you can imagine, in a 21 year journey, there were many surprises. By far, the biggest surprise was how it took me into the middle of the DevOps movement, which I think is urgent and important. In that journey, a particularly huge surprise, was my learning about the importance of architecture. That architecture was one of the top predictors of performance, even larger of a predictor than even continuous delivery.

I think what is so amazing is that, it is architecture that really dictates to what extent teams can work independently. To what extent can they develop, test, and deploy value to their customers without being coupled to potentially scores of other teams? I know that architecture is a particularly favorite topic here within the QCon community. When Randy Shoup asked me if I’d be willing to chair a panel on the subject, I jumped at the chance, because I wanted to explore these topics more deeply with two people whose achievements I deeply admire, Carin Meier and Mike Nygard.

Background

Could each of you briefly introduce yourselves? Tell us what you’re working on these days?

Meier: I am a data engineer right now at Reify Health. I’m also the author of, “Living Clojure.” I’m very interested lately in the Clojure data science, machine learning areas.

Kim: It’s now leveraging the Python amazing ecosystem of libraries. Mike, how about you?

Nygard: I am currently SVP of platform and architecture at Sabre, where I’m helping this company through a digital transformation and turnaround. The subject of architecture and coupling is very much on my mind every single day, at Sabre. I’ve also been a developer for a long time. In fact, Carin and I were colleagues at Cognitect, where we were both working in Clojure. We got to partner on a pretty amazing project, building a desktop IDE for building games using Clojure, which is not exactly considered the sweet spot for Clojure. It worked exceedingly well in that situation.

Kim: I saw that video. The name of that editor is called Defold.

When Coding Was Most, and Least Fun

We’re going to talk about what productivity, focus flow, and joy look like in the large, but maybe we could talk about first in the small, at the individual level. Could you both talk about when coding was most fun for you? Maybe even let’s explore the opposite, when was it also the least fun for you? Maybe talk about the factors of what made it so fun and what specific factors made it so not fun?

Meier: I’ve been doing programming for quite a while. It became really fun once I started coding in Clojure. I think that is a lot due to the nature of the language, and how fast you can get feedback, and how close you feel to the code. You can really interact with it and almost sculpt this, and the data. That really makes it a pleasure to work with during the day. It’s very productive too, it gets rid of all the boilerplate and you can just focus on the real problems. When I’m working with Clojure, is one factor. I also like to explore and do a little bit of research. That really attracts me to the data science, machine learning realm because there’s always something new to explore, and novel applications that can help businesses and just people.

Kim: In fact, one of the things I really admire about your work is it’s so clear that you’re really on the frontier of some of these problem domains in terms of solutions that are being developed across a very wide surface area of technologies. Am I overstating the case?

Meier: I do like to read the latest papers that come out, and old papers too. It’s always nice to see, what problem could that solve? It’s a new way of thinking about it and this new tool could open up possibilities that we haven’t thought about before. That’s really exciting to me.

Kim: I just want to concretize some of the things I heard. Some of the things I heard was fast feedback in your work. You get really fast feedback in terms of whether something is working or not. I know in one of our conversations, you said just how miserable you are when it takes a long time to get feedback. By long feedback cycles, you were talking about minutes, not hours, not days, the fact that it even took minutes. Am I recalling that correctly, Carin?

Meier: Yes. I get a little down when I have to do my Docker builds and deploys, that takes a little long. It’s a far greater cause building out your pipeline, but I much prefer to meet my REPL.

Kim: Creating immutable build artifacts. That’s important. It does amaze me that when you have 4, 5, 6, 7 minute build times that actually does suck the joy out of our work.

Mike, does that resonate with you? Tell us about specific times when you were having just a lot of fun, and versus not fun?

Nygard: First of all, waiting on a Docker build or anything else that’s over that one minute threshold, like it’s time enough to flip away and go look at social media and get angry and stressed out and depressed. It forces you off task. The times I’ve enjoyed most have been the ones like the project I worked on with Carin, aside from the fact she’s just a joy to work with. It was a project that we were working on all the time. We were focused on it, really focused. The previous projects I’ve enjoyed most, there was a project for Photo Studios, where we were in a full XP lab situation. We controlled our equipment. We had our OS builds, they were ours. We controlled our build infrastructure. It’s not that we were control freaks so much, it’s just that it allowed us to cut off all those external dependencies, and really focus on the work itself. There were times when we would joke about whether this was a one can of Pringles problem or a two can of Pringles problem. What it really meant was, is this something we’re going to get done in a morning, in the short block? Is it an afternoon, or is it an afternoon and an evening? Sometimes you’d get into that state of flow, and suddenly realize it was a two can of Pringles problem, because it was 9:00, and that was dinner. Not great on the health front, but it was a really enjoyable experience because we were able to work together, work closely, and create everything we needed to create. I think that’s one of the ideals you wrote about around locality. We really had that. Those are the times that I’ve enjoyed the most.

Kim: Locality was really meant to suggest, to what extent can an individual or team do what they need to do by themselves, without having to open up tickets with potentially 15, 20 different teams? Mike, you had shared a story about your least fun moment. Can you describe what that looked like, and what are the factors that made that so frustrating and miserable?

Nygard: I don’t even remember which example I used before.

Kim: Let me remind you. It was a floor with 300 people on it, tables.

Nygard: I figured it was either that or one other. No, it was a vast project. It was late and getting later, and so their solution to solving the late project was to add another 100 people. They had emptied out a floor of a bank and had rows of folding tables with all of us in there. The team was strictly organized by layers of the application, so we had a persistence team that had no idea what the domain needed. We had a domain team that had no idea what the users needed. We had a presentation layer team that also didn’t know what the users needed. We were all trying to model the world while also managing these vertical dependencies that were just changing all the time. It was a tough slog.

Kim: Just to, again, concretize that. The fact that you had these teams organized, whether it was technology, it meant that anything that you need to implement from the user’s perspective, from the customers’ perspective was now smeared across those teams, and that involved communication, coordination, prioritization, sequencing. These are the things that suck.

Nygard: Exactly. Big documents, lots of meetings.

The Intolerable 4-Minute Build Times

Kim: I’ll be the first to admit that I’m pretty fussy, and sometimes impatient. When Carin brings up the notion of, was it the intolerable 4-minute build times? Could we just talk a little bit about to what extent really that is tolerable or not tolerable? When Carin brings up that story, it reminds me of one of the most miserable experiences I’ve had as a developer, which was trying to get something working in OAuth. I’ll admit, OAuth isn’t my favorite thing to do, but what made it so frustrating was that the build and deploy times was about 7 minutes. To me, this was just an exercise in trial and error, in that every trial would take 7 minutes. I just found myself 2 hours later, in a pretty wretched state. I was no longer thinking clearly. I don’t remember exactly what I did, but I got a more representative environment on my dev laptop, and suddenly, I could find out something works within 7 seconds. Suddenly, I could now be much more deliberate and productive in terms of actually fixing the problem. On a scale of 1 to 10, can you just react to that? One is [inaudible 00:11:21] that is creating childish impatience, and an inability to actually work mythology through a poem, or 10 is like, no, this is actually of concern, because those are the conditions that any developer would actually be able to be productive in. Mike?

Nygard: I don’t want to belittle a 7-minute delay, but somebody has always got a worse story. I vividly remember C++ projects that would take 2 hours to compile, or even overnight. Sometimes you would commit your code, and you’d come back the next morning to see if the nightly build succeeded or not. To the extent that all of those delay feedback, they delay learning, they make it harder for you to adapt the software to what it wants to be, and to what your users need it to be. They’re all bad. There’s a really interesting cutoff point to me, somewhere between 10 minutes to 30 minutes, where people start to bend their whole workflow around the build times. If you know you only get three builds a day, then you plan your work around those builds, which has its own set of issues. There’s something uniquely irritating about those medium-sized chunks, because they’re too big to ignore, but too little to really switch modes into something else and get your head in a different space.

Kim: Carin, how about you?

Meier: I totally agree with it. Trying to minimize it, and whatever that means to you. You know when you’re annoyed, when that time frame is for you. You should try to do something about it. One of the most recent times that we had to deal with that was an extremely annoying one that made me post a hawk GIF, because it enraged me so much every time it happened. It was in the middle of our Docker build, randomly, we would be building a JAR and the JAR would be cropped for just one of those, you have no idea why. It randomly happened but it was rage inducing, because then again, you’d have to lose 10 minutes. It got pushed to the backburner until it finally, as these things happen, you decide to do something about it. I think one approach is to timebox it. Say, I am going to take a day and try to timebox fixing this crop JAR problem. In the long run, it is going to make everything run a lot smoother, and make everybody a lot happier, less hawk GIFs in Slack. I think that’s a good way to put the investment. We did solve it, which was nice. There’s always something like that that gets pushed to the backburner because it doesn’t happen all the time but it makes your cycle time longer, and you’ve got to weigh.

Kim: It impacts everybody. It will impact everyone who’s incorporating code, benefiting from builds, benefits from this improvement.

Nygard: What I find really interesting about it though, is people don’t get upset about it unless they know it doesn’t have to be that way. If they think that that lost time is just the way the world is, then there’s no emotion about it. It’s just the way the world is. If you come into that project from somewhere else, you’re like, “Your unit tests take 10 minutes to run? What are you, savages? How do you live like this?” You get that level of dissatisfaction. Then pretty soon something has to get done about it. Sometimes it takes an example from outside to say, actually, this thing is not a fact of the universe, it is an artifact of the way you’re working, or the technology you’re working in.

Kim: I love that. In the unicorn project, I think these concepts that are contrary and counterintuitive, maybe even crazy sounding, one of them, to me, was the notion of where we put our best developers. If you look at the tech giants, Facebook, Amazon, Netflix, Google, they put their best developers, the most experienced developers on dev productivity. The next most experienced developers on backend services. Then probably the most junior developers on the user facing features. Whereas in most large, complex enterprises, it’s the exact opposite. They put the best developers on the feet first. The next most experienced developers on backend services. Then they end up putting their summer interns on dev productivity and build systems, which is, I think, exactly not what you want, for the reasons that you cited there.

How Important Functional Programming Techniques and Principles Are For the Everyday Programmer

One of the other things that made me so excited to talk to both of you is our common love for functional programming, and in particular, one functional programming language called Clojure. Can you talk about how important you think functional programming techniques and principles are for the everyday programmer? In other words, is it only for the senior engineers and architects, as represented here within the QCon community, or is there something in it for junior programmers as well? I’ll put that out for both of you.

Nygard: I think it’s much too powerful and fun for the front line developers, it should be reserved for wizards who’ve ranked up a few times.

Kim: That’s right, because it’s finite. Only so many people can use it at one time. Mike, why would you say such a thing? You said it’s powerful, what makes it so powerful?

Nygard: We have to unpack a little bit what we mean by functional programming. I’m not going to try and pull up multiple academic definitions. Generally speaking, we’re talking about languages that favor immutable values, which just make entire classes of problem disappear. There are also languages that favor building functions out of other functions. You get this effective leverage, where you can create increasingly powerful abstractions to avoid repetitive boilerplate code. For me, those are two of the features that I really cherish.

Kim: To what extent can they be benefited by even junior programmers, or is this only reserved for the level 30 definition?

Nygard: Yes, level 30, for sure. No, I’m being facetious of course. No, I think there’s a certain amount of introspection or soul searching in the functional programming community saying, why is this not the default? Why is this not the mainstream? Maybe it’s just time. Maybe it just requires enough of a critical mass to build up, or enough people to be exposed to it. Certainly, I think a lot of the FP principles are making their way into all of the mainstream languages, to an extent everyone’s going to be a functional programmer. I think it does have a lot of benefits to offer even beginning level programmers. I can’t tell you the number of hours I lost to race conditions mysteriously changing variables, deadlocks, all of the concurrency problems that you expect to experience. I probably left behind some horrifically gnarly dependencies, because I wouldn’t have thought about building a function that can take any function from Int to Int. I would have thought about, this class knows that class which knows that class, and there’s a point where you are impressed with your own ability to hold a lot of complexity in your head. Then, hopefully, you evolve past that and realize, no, the true mastery is not needing to hold that complexity in your head.

Kim: I’m thinking of the chief architect for Java. His name is Brian Goetz, and his amazing book, “Java Currency in Practice.” I actually came from some background in concurrent programming. I thought I knew a lot about concurrent programming, then I read his book, and I cannot tell you how many shocks were, and these questions of like, I had no idea something actually worked this way. Then that feeling of, how many times did I make this mistake that’s now planted in somewhere that will get triggered. I totally resonate with that.

Carin, how about you? Is functional programming accessible or should be accessible to junior programmers?

Meier: Yes, I think so. I think the only reason why people have trouble with it at first is because it’s a completely different mindset, looking at the world, and that’s hard to transition to. I’ve talked to people that their first exposure to programming was functional programming, and they actually have a hard time trying to then do object oriented programming. I don’t think there’s anything intrinsically hard about it, I think it’s just that transition period, of changing your mind to be more data oriented and immutable, over the object oriented way of looking at the world.

Kim: I had a sobering moment when my friend, Cornelia Davis, she was talking about, working with her son in college, who was learning programming for genetic sequencing. It was an algorithm that could fit basically on one PowerPoint slide. She noticed a bug that he had introduced just on iteration, and it was an off by one error. That was a very sobering moment for me in terms of like just how fraught with errors even things like iteration are, and that there’s actually a better way to do things.

How Leaders Can Bring Better Ways of Doing & Thinking into Daily Work

We’ve talked about some things that causes better ways of working, better ways of thinking. How does someone bring a better way of working and thinking into their daily work, which might be at the mercy of too many committees, managers who are quite happy to do things the way they’ve always done? Can you talk a little bit about how do leaders at all levels bring in better ways of thinking and doing into daily work? Mike, you had mentioned that sometimes it takes someone from the outside to see how savage and inhumane certain working situations are. We’re here at QCon, where there are a lot of great ideas forged through tough experiences. What advice would you give to people trying to introduce better ways of working?

Nygard: I think the more locally you can begin, the better. If you’re trying to bring in an idea that requires the whole company to get on board, you’re not going to get very far unless it’s a five person startup. Neal Ford used to talk about bringing Clojure into organizations as just a JAR file for a dependency for better unit tests. Bring it in at a level where it doesn’t require a lot of approval, because you’re not changing the production runtime, it’s still the JVM. You’re not changing the language that the production app is written in so you don’t need new linters or new syntax checkers or formatters, or build tools, or anything like that. You are giving people a taste of where you can derive some real benefit and get some expressivity out of it.

If you’re in a team where you control more of your own runtime environment, you’re in a more DevOps style: you build it, you run it type of environment. Then you might say, “Within our boundaries, we’re going to try out a new technique, a new language, a new architecture, but we’re going to maintain all of our interfaces the same way so we don’t require signoff or agreement from the parties on the other sides.” I view it as try and get that seed crystal going in a way that doesn’t trigger the organizational antibodies. As you do that, you also look for allies. You build your Rebel Alliance meeting at the beach bar at 5:00 every Thursday or whatever, and look for executives who have some enlightenment and can offer support for your Rebel Alliance, and help provide them some shielding and some air cover as you start to make larger changes. Of course, be aware that you’re not the only party introducing changes, and other people are introducing their own waves of change simultaneously to yours. How they intersect and overlap, and constructively or destructively reinforce each other, can matter a lot. Keep your eye out for that. Don’t try and stop all of the others because they may be making improvements too, and you’d rather have allies than enemies. Build that network for change laterally.

Kim: I love that notion of the other insurgent team. I heard at the DevOps Enterprise Summit, that the only thing worse than one DevOps team is two DevOps teams, who are all clamoring for attention trying to do the right thing.

Carin, how about you?

Meier: At least in my position now, I’m working on a much smaller team, so we don’t have to deal with a lot of the organizational complexity. I think some of the same fundamentals are true, and that’s communication, trust, respect, and feedback within people. Because fast feedback is not only with your REPL and not only with your program, it’s with the people on the organization as well. There’s various techniques to do that, if you want to explore a different way of looking or doing something, maybe you could do a lunch and learn. You can present your idea, educate people on it, and get their feeling of it. Is it something that you want to invest in like a spike day? That’s just one day that you make some goals that you’re going to spike something out and see if it has potential. Then share those results with everybody else, get feedback again. There’s various ways that you can do this in an incremental fashion. Again, feedback is not only for the REPL, it’s for people in the organization, too.

Reactions to JAR File Fix

Kim: In fact, can you talk a little bit about what people’s reactions were when you fixed that terrible JAR file, long build time plus JAR file corruption, as if long build times weren’t enough, 7 minutes, terrible. When you actually finally fixed the problem, what were people’s reactions?

Meier: We’re all remote, like most people now. In Slack, there were many GIFs of rejoicing. That’s how we celebrated. Yes, celebrated wins too, that helps everyone.

Kim: I have to imagine this is exactly the reaction that one would hope for. It positively reinforces that brave and initially thankless task of looking with the build system and the guts of Dr. Build, to maybe skepticism, to genuine appreciation as everyone’s benefiting from this improvement that you had made.

Meier: That goes also to new techniques. One of the things we’re talking about, blending Python and Clojure using a bridge. We’re using a Python library to do some differential privacy, so that was a new technique we were introducing in the organization. We did that with research, lunch and learn. Do a spike day, is it good? Then develop it out, and assess the results. That’s a technique that you can use with just about anything.

Current Passions

Kim: I had mentioned how excited I was just to hear about your perspectives on things that cause focus flow and joy. One of the other things I wanted to learn from you is just, what are you working on these days? What are you most passionate about now in programming, given the fact that this is probably, I know, something that is inherently challenging? You both don’t gravitate towards the easy. How would you recommend others to get into it who are also interested in this? Carin, I’ve been dazzled by all the work that you’ve been doing in the ML and the machine learning community, and then this incredibly audacious project to bridge the worlds of the JVM, Clojure and Python. When I first heard about it, my first reaction was like, that’ll never work. Just to see all the achievements coming out of this group of people has just been dazzling. Carin, what are you most passionate about these days?

Meier: I’m very much into the machine learning and data science combining with the Clojure. That takes a blending of worlds because there’s a lot of specialized libraries out there that are available in Python. Traditionally, it’s very hard to meld those two worlds. There is this library that was created by a very smart guy, Chris Nuernberger, called libpython-clj, that allows you to actually bring Python into your REPL, and be able to use that library and then also have the same advantages of being able to integrate it into your larger Clojure infrastructure. I think that’s really the best of both worlds. It’s very much with the Clojure philosophy of being pragmatic. You’re powerful, but then you want to get the job done. Yes, we’ve used that with differential privacy at Reify Health, and we’re also looking at using various other data science techniques to improve the speed of enrollment and to drug trials.

Reify Health

Kim: Could just say a little bit what Reify Health does, because in this age, I can’t think of a more noble mission than what you’re working on these days.

Meier: It’s really an exciting place, meaningful right now, especially. Reify Health has an application that is aimed at addressing the first bottleneck in a clinical trial, which is getting enough people enrolled. We all know, we’ve been all watching, are enough people enrolled yet? We want this vaccine. That’s one of the things. We’re involved in some COVID trials, also, cancer treatments. All aimed at trying to get cures to people faster.

Kim: I’ve got chills just hearing about that. Yes, that is amazing. All these breakthroughs that you’re talking about are in service of these missions that you’re talking about?

Meier: Yes, definitely. I’m on the data team, which is a new team that’s been formed to build out our data pipeline, and be able to bring in all these data science techniques to accelerate this.

Current Passions

Kim: Mike, how about you? What are you most passionate about these days?

Nygard: For the day job, we are taking a 50 year old company that started with a mainframe, in fact, the name of the company was originally just the name of the machine. We’re getting off of the mainframe and moving everything to cloud. That includes the engines that power most travel searches that you execute today. If you go on to the popular online websites, if you engage with the travel agencies, or the corporate booking agencies that’s using our flight search, travel search technology. It’s a company with a long and rich history, which can have good and bad aspects, or hindering and helping aspects. We’re moving all of that to Google Cloud, and rearchitecting a lot of it along the way. That’s the day job. I mostly am working at that nexus of organization and technology. I don’t do a lot of hands-on coding during the day job. To keep myself grounded and sane in the off hours, my passion is doing Rust on bare metal, and stripping away all the layers of complexity as far as possible. Down to, I’m booting into some Rust code.

Kim: Is there a particular goal that is driving you to this area of interest?

Nygard: I got my start on 8-bit microcomputers where you knew where all the registers were, and had direct control over all of the memory. Partly, it’s for fun, but partly, it’s also because I think, in some areas, we have built up a Jenga tower of complexity for solving general purpose problems. We have some specialized problems that may admit specialized solutions, and gain pretty significant benefits from straying away some of the complexity.

Parting Advice, and Help Sought

Kim: Is there any advice that you would give this community here at QCon? Is there any help that you’re looking for? Carin, advice and help you’re looking for?

Meier: The advice is, have fun. You can bring fun into your daily job and with your coworkers, so whatever you’re doing during the day, try to bring a little fun into it. Help that I’m looking for? Yes, I’m always looking for good ideas. If you have any good ideas, data science, or especially machine learning, or writing interesting articles that you think I ought to be aware of, please pass it my way.

Kim: Mike, how about you, advice you would give and help you’re looking for?

Nygard: I love Carin’s advice so much. I’d love to just say ditto on that. Fun and whimsy is sadly lacking this year. We’ve all gotten remote. We’re largely isolated from each other and from the world. One of the best pieces of advice I’ve gotten recently is get outdoors, reconnect with nature. It doesn’t have to be around people, get around plants. You can’t get COVID from plants, I think. Stay grounded. We work in a lot of abstractions, and with a lot of abstractions, and sometimes we can lose sight of the real physical world that’s happening all around us. That would be my advice.

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How Data Science And Machine Learning Works To Counter Cyber Attacks

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Article originally posted on Data Science Central. Visit Data Science Central

We are all aware of the heinous cyber-attack that took down more than 200,000 systems in 150 countries in only a few days in May 2017. This was found by the National Security Agency (NSA) and was nicknamed “WannaCry,” which exploited a vulnerability and stole important resources before being distributed online. 

After successfully accessing the computer, it encrypted the machine’s contents and rendered them unreadable. Now, victims of the assault were informed they needed to acquire special decryption software to retrieve their stolen material. Furthermore, the attackers marketed this software.

This ransomware outbreak targeted both people and big organizations, including the United Kingdom’s National Health Business, Russian banks, Chinese schools, the Spanish telecommunications company Telefonica, and the US-based transportation service FedEx. 

The overall losses were estimated at $4 billion. Other forms of cyber intrusions, such as crypto jacking, which are more subtle and less destructive but costly, are on the rise. Even high-profile firms with sophisticated cybersecurity processes are vulnerable. 

A recent panic at Tesla in 2018 was averted owing to a diligent third-party team of cybersecurity specialists. As a result, there were over 11 billion malware infections in 2018. That is a major problem that cannot be solved solely by humans.

Fortunately, this is where machine learning may come in handy.

How Machine Learning Helps to Boost Cybersecurity? 

Machine learning is a subset of artificial intelligence that makes assumptions about a computer’s behavior by using algorithms from prior datasets and statistical analysis. It allows the computer to modify its operations and even execute functions for which it was not expressly intended. Thus, the role of ML and AI in cybersecurity has been increasing. 

Machine learning is increasing in popularity to detect risks and automatically eliminate them before they can wreak mayhem. It can filter through millions of files and detect potentially dangerous ones. This was accomplished by Microsoft’s software in early 2018.

According to the firm, hackers utilized Trojan spyware to infiltrate hundreds of thousands of systems and run rogue cryptocurrency miners. Microsoft’s Windows Defender, a software that utilizes many layers of machine learning to identify and block potential threats, effectively blocked this attack. 

As a result, the business was able to shut off the crypto miners as soon as they began digging. Machine learning is used to search for network vulnerabilities and automate actions, in addition to detecting early threats. Machine learning excels at some tasks, such as swiftly scanning vast volumes of data and evaluating it with statistics. Cybersecurity systems create massive amounts of data, so it’s no surprise that this technology is so beneficial. As a result, in the domain of cybersecurity, this is proving to be a big benefit.

Microsoft, Chronicle, Splunk, Sqrrl, BlackBerry, Demisto, and other big corporations are utilizing machine learning to strengthen their cybersecurity systems.

How Modern Data Science Powered by AI Identifies and FIxed IT Vulnerabilities

Here is how data science helps identify and resolve IT vulnerabilities:

1- Improve the Usage of Technologies

Modern Data Science has the potential to both improve and simplify the usage of such technologies. A machine-learning algorithm may be fed both current and historical data through data science. So that the system can detect possible problems accurately over time.

This allows the system to be more precise since it can predict assaults and identify potential vulnerabilities. 

2- Use Encryption

A data breach or assault can cause severe damage to your organization in terms of the loss of important data and information.

This is where data science comes in handy since it uses very sophisticated signatures or encryption to prevent anyone from delving into a dataset. 

3- Create Protocols

Data science has the potential to create impenetrable protocols. By examining the history of your cyber-attacks, you may create algorithms to detect the most often targeted pieces of data. Data science programs may assist you in harnessing the potential of data science to empower networks powered by self-improving algorithms.

Why Should Companies Hire Qualified Professionals?

Thus, the above points indicate the importance of data science and qualified data science professionals in your firm. Focus on hiring professionals who have a master’s degree in engineering in data science and the knowledge of how to decode big data.

We have access to a massive amount of data, and the data is typically telling a narrative. You should be able to identify deviations from the norm if you understand how to analyze data. and such variations can occasionally signal a threat. And, owing to the usage and advancements achieved in machine learning, dangers may now be appropriately countered in a wide range of industries. It is used for image recognition and speech recognition applications.

Even though cybersecurity has improved as a result of this process, humans remain critical. Some individuals believe that you can learn everything from data, but this is just not true. An over-reliance on AI might lead to a false sense of security. 

However, without a doubt, artificial intelligence will become increasingly widespread in maintaining security. It’s maturing, and it’s a feature, not a business. It will play a part in resolving a certain issue. 

Final Thoughts

However, AI cannot address every problem. It will be a tool in the toolbox. At the end of the day, humans are the overlords. 

As a result, in addition to carefully deployed algorithms, cybersecurity specialists, data scientists, and psychologists will play an important role. Human efforts, like those of all existing artificial intelligence and machine learning supplements, augment rather than replace them.

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MongoDB Inc. (NASDAQ:MDB) Reduces -0.72% In A Week: What's Taking The Stock Higher?

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Posted on mongodb google news. Visit mongodb google news

In last trading session, MongoDB Inc. (NASDAQ:MDB) saw 0.39 million shares changing hands with its beta currently measuring 0.73. Company’s recent per share price level of $358.92 trading at -$3.14 or -0.87% at ring of the bell on the day assigns it a market valuation of $22.71B. That closing price of MDB’s stock is at a discount of -19.51% from its 52-week high price of $428.96 and is indicating a premium of 48.1% from its 52-week low price of $186.27. Taking a look at company’s average trading volume for last 10-days demonstrates a volume of 0.45 million shares which gives us an average trading volume of 776.04K if we extend that period to 3-months.

For MongoDB Inc. (MDB), analysts’ consensus is at an average recommendation of an Overweight while assigning it a mean rating of 1.90. Splitting up the data highlights that, out of 18 analysts covering the stock, 1 rated the stock as a Sell while 0 recommended an Overweight rating for the stock. 5 suggested the stock as a Hold whereas 12 see the stock as a Buy. 0 analyst(s) advised it as an Underweight. The company is expected to be making an EPS of -$0.39 in the current quarter.


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Upright in the red during last session for losing -0.87%, in the last five days MDB remained trading in the red while hitting it’s week-highest on Tuesday, 07/27/21 when the stock touched $358.92 price level, adding 3.52% to its value on the day. MongoDB Inc.’s shares saw a change of -0.03% in year-to-date performance and have moved -0.72% in past 5-day. MongoDB Inc. (NASDAQ:MDB) showed a performance of -0.72% in past 30-days. Number of shares sold short was 5.43 million shares which calculate 8.05 days to cover the short interests.

Wall Street analysts have assigned a consensus price target of $387.23 to the stock, which implies a rise of 7.31% to its current value. Analysts have been projecting $300.00 as a low price target for the stock while placing it at a high target of $450.00. It follows that stock’s current price would drop -25.38% in reaching the projected high whereas dropping to the targeted low would mean a gain of 16.42% for stock’s current value.

MongoDB Inc. (MDB) estimates and forecasts

Statistics highlight that MongoDB Inc. is scoring comparatively lower than the scores of other players of the relevant industry. The company lost -2.89% of value to its shares in past 6 months, showing an annual growth rate of -31.31% while that of industry is 3.30. Apart from that, the company came lowering its revenue forecast for fiscal year 2021. The company is estimating its revenue growth to decrease by -77.30% in the current quarter and calculating -22.60% decrease in the next quarter. This year revenue growth is estimated to rise 33.00% from the last financial year’s standing.

12 industry analysts have given their estimates about the company’s current quarter revenue by setting an average figure of $183.84 million for the same. And 12 analysts are in estimates of company making revenue of $198.16 million in the next quarter that will end on Oct 2021.

Weighing up company’s earnings over the past 5-year and in the next 5-year periods, we find the company posting an annual earnings growth rate of -24.70% during past 5 years.

MDB Dividends

MongoDB Inc. is more likely to be releasing its next quarterly report between August 31 and September 06 and investors are confident in the company announcing better current-quarter dividends despite the fact that it has been facing issues arising out of mounting debt.

MongoDB Inc. (NASDAQ:MDB)’s Major holders

Insiders are in possession of 6.32% of company’s total shares while institution are holding 86.58 percent of that, with stock having share float percentage of 92.42%. Investors also watch the number of corporate investors in a company very closely, which is 86.58% institutions for MongoDB Inc. that are currently holding shares of the company. Capital World Investors is the top institutional holder at MDB for having 7.46 million shares of worth $1.99 billion. And as of Mar 30, 2021, it was holding 12.00% of the company’s outstanding shares.

The second largest institutional holder is Blackrock Inc., which was holding about 5.23 million shares on Mar 30, 2021. The number of shares represents firm’s hold over 8.41% of outstanding shares, having a total worth of $1.4 billion.

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On the other hand, Growth Fund Of America Inc and Smallcap World Fund are the top two Mutual Funds which own company’s shares. As of Mar 30, 2021, the former fund manager was holding 4.82 million shares of worth $1.29 billion or 7.76% of the total outstanding shares. The later fund manager was in possession of 2.65 million shares on Mar 30, 2021, making its stake of worth around $708.3 million in the company or a holder of 4.26% of company’s stock.

Article originally posted on mongodb google news. Visit mongodb google news

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Global NoSQL Database Market Top Company Profile: DynamoDB, ObjectLabs Corporation, Skyll …

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The NoSQL Database market research report is intended to elaborate market opportunities and the potential for the producers, suppliers, merchants, business managers and other shareholders in the NoSQL Database market. The research report is curated with an aim to provide comprehensive and actionable insights that could enable the NoSQL Database industry market participants take rightful decisions in terms of investments and other important decisions to secure a better place in the market. The data gathered in the report is appropriately tabulated and classified to analyze the Compound Annual Growth Rate (CAGR) of the NoSQL Database market.

Vendor Profiling: NoSQL Database Market, 2020-28:

DynamoDB
ObjectLabs Corporation
Skyll
MarkLogic
InfiniteGraph
Oracle
MapR Technologies
he Apache Software Foundation
Basho Technologies
Aerospike

We Have Recent Updates of NoSQL Database Market in Sample [email protected] https://www.orbisresearch.com/contacts/request-sample/4421347?utm_source=puja

The research report studies the NoSQL Database market in terms of its expansion, advances in technology and its positive impact on the progress, supply chains, and work arrangements. Due to the increasing relevance, the research report has developed industry and sector specific interventions of the NoSQL Database market. The study intends to disseminate crucial information on the concerns in the NoSQL Database market and current events happening in the NoSQL Database market. Moreover, developments among policy-makers, leading enterprises, associations, enterprises, international and national trade unions, and the media is provided to the market participants through the report.

Segmentation
The principal objective of curating the research report is to contribute to informed decision making and provide a clear picture of how their business issues or operational issues can be addressed productively by using the crucial information about the enterprises and other major factors influencing the NoSQL Database market performance.

Analysis by Type:

Column
Document
Key-value
Graph

Analysis by Application:

E-Commerce
Social Networking
Data Analytics
Data Storage
Others

Major economies in certain geographic regions controlling the NoSQL Database market are analyzed. The geographic regions and countries covered in the study include:

• North America: Canada, U.S., and Mexico
• South America: Brazil, Ecuador, Argentina, Venezuela, Colombia, Peru, Costa Rica
• Europe: Italy, the U.K., France, Belgium, Germany, Denmark, Netherlands, Spain
• APAC: Japan, China, South Korea, Malaysia, Australia, Taiwan, India, and Hong Kong
• Middle East and Africa: Saudi Arabia, Israel, South Africa

Our key underpinning is that the report on the NoSQL Database market offers detailed visualization of the following elements:

• Customer Experience Maps that visually represent complex customer interactions
• Data-driven research based on qualitative and quantitative research, and SWOT analysis
• Actionable insights that meet all the business requirements
• The report offers strategic frameworks to improve the market position of enterprises in the NoSQL Database market.

Do You Have Any Query or Specific Requirement? Ask Our Industry [email protected] https://www.orbisresearch.com/contacts/enquiry-before-buying/4421347?utm_source=puja

Additionally, the research study strives to evaluate the current and future growth prospects, hidden opportunities, factors boosting the potential of revenue, and demand-supply, consumption patterns, pricing patterns of the goods and services available in the NoSQL Database market by region-wise assessment. The report gathers a wide spectrum of data-driven research and advisory helpful for CXOs and other market participants.

Highlights of the Research Report
• The research report is developed for a better market understanding of the market participants like producers, suppliers, reseller, wholesalers, merchants, CXOs, project managers, and other market players about the technological changes and its impact on the overall progress of the NoSQL Database market.
• To stimulate the market productivity, the role played by trade unions, international organizations or government bodies is depicted in the report.
• Production and employments trends in the regional and international markets along with the specific countries and regions influencing the performance of the NoSQL Database market are provided in detail in the report.
• The research report is an effective tool to identify risks, overcome challenges in advance without hampering the productivity and provides a better understanding of the consequences of changes taking place in the market.
• Leading players that manufactures high-value consumer products are detailed along with their market capitalization.
• The cost incurred by each segment, transportation, production processes, and distribution constraints are highlighted.

About Us:
Orbis Research (orbisresearch.com) is a single point aid for all your market research requirements. We have vast database of reports from the leading publishers and authors across the globe. We specialize in delivering customized reports as per the requirements of our clients. We have complete information about our publishers and hence are sure about the accuracy of the industries and verticals of their specialization. This helps our clients to map their needs and we produce the perfect required market research study for our clients.

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AWS Announces the General Availability of Amazon EBS io2 Block Express Volumes

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MMS Steef-Jan Wiggers

Article originally posted on InfoQ. Visit InfoQ

Amazon Elastic Block Store (EBS) volumes are a key Elastic Compute (EC2) component with several HDD and SSD volumes, each designed for a particular use case. And recently, AWS announced the general availability of its cloud-based storage area network (SAN) offering, Amazon EBS io2 Block Express volumes – providing 4x higher throughput, IOPS, and capacity than io2 volumes.

Last year at re:Invent 2020, the company previewed Amazon EBS io2 Block Express volumes as a SAN offering. It is designed according to AWS to meet the requirements of the largest, most I/O-intensive, mission-critical deployments of Microsoft SQL Server, Oracle, SAP HANA, and SAS Analytics on AWS. The volumes are now generally available first with Amazon EC2 R5b instances powered by the AWS Nitro System, which delivers the highest EBS-optimized performance. Support for other instances besides R5b is coming soon. In addition, with the GA release, the io2 Block Express volumes now also support io2 features such as Multi-Attach and Elastic Volumes.

Channy Yun, a Principal Developer Advocate for AWS, explains in an AWS News blog post on the GA release:

The new Block Express architecture delivers the highest levels of performance with sub-millisecond latency by communicating with an AWS Nitro System-based instance using the Scalable Reliable Datagrams (SRD) protocol, which is implemented in the Nitro Card dedicated for EBS I/O function on the host hardware of the instance. Block Express also offers modular software and hardware building blocks that can be assembled in many ways, giving you the flexibility to design and deliver improved performance and new features at a faster rate.

Users can create io2 Block Express volumes in the Amazon EC2 console, AWS Command Line Interface (AWS CLI), or an SDK with the Amazon EC2 API when creating R5b instances. Next, after selecting the EC2 R5b instance type, on the Add Storage page, under Volume Type, users can choose Provisioned IOPS SSD (io2) – and the new volumes will be created in the Block Express format.


Source: https://aws.amazon.com/blogs/aws/amazon-ebs-io2-block-express-volumes-with-amazon-ec2-r5b-instances-are-now-generally-available/

Amazon EBS io2 Block Express volumes can be an alternative to enterprises for their on-premise solution. In an AWS press release on the GA release, the company states:

io2 Block Express volumes reinvent block storage and give customers the performance they expect from a SAN, but with the elasticity of AWS, unlimited scale, and flexibility of pay-as-you-go pricing—at as low as half the cost of a typical SAN. io2 Block Express volumes are designed for applications that benefit from high-volume IOPS, high throughput, high durability, high storage capacity, and low latency.

And in a tweet by Igor Nemy, Technologist at labSpaceSys:

Public clouds are getting closer and closer to be identified as large mainframes. SAN volume with 256k IOps, 4GB/s throughput, and 99.999% of durability. I won’t be surprised if this is powered by bespoke ARM-based Nitro (!side-) project.

Currently, io2 Block Express volumes are available in all regions where R5b is available – which include US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Tokyo), and Europe (Frankfurt). In addition, the company announced that support for more regions is coming soon. 

Note that AWS bills the io2- and io2 Express volumes the same way and recommends using tags to identify costs associated with io2 Block Express volumes. Pricing details of io2 volumes are available on the Amazon EBS pricing page.

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NoSQL Database Market Size, Growth, Opportunities, Industry Applications, Analysis and Forecast …

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New Jersey, United States,- Verified Market Research has released a new NoSQL Database Market growth 2021-2028 survey report that includes data and statistics related to the market structure and size. The aim of the research is to provide market insight and strategy to help policymakers make informed investment decisions and identify potential gaps and growth opportunities. The aim of this study is to provide a detailed overview of market trends and growth situations so that appropriate tactics can be applied to outperform the global Copper Mask market.

The study accurately predicts the size and volume of the market in the present and the future. The report offers a comprehensive study of the NoSQL Database industry and information about the expected future trends that will have a significant impact on the growth of the market. The paper then looks at the major global players in the industry.

The Global NoSQL Database market was valued at USD 3.00 Billion in 2019 and is projected to reach USD 24.89 Billion by 2027 growing at a CAGR of 30.14% from 2020 to 2027.

Get | Download Sample Copy with TOC, Graphs & List of Figures @ https://www.verifiedmarketresearch.com/download-sample/?rid=129411

The competitive landscape is a critical aspect that every key player must be aware of. The report throws light on the competitive scenario of the NoSQL Database Market for knowing the competition at the national and global level. The market experts have also outlined all the major players in the NoSQL Database market, taking into account key aspects such as operational areas, production, and product portfolio. Further, the companies included in the report are examined on the basis of key factors such as company size, market share, market growth, revenue, production volume, and profit.

The report covers extensive analysis of the key market players in the market, along with their business overview, expansion plans, and strategies. The key players studied in the report include:

• Objectivity Inc
• Neo Technology Inc
• MongoDB Inc
• MarkLogic Corporation
• Google LLC
• Couchbase Inc
• Microsoft Corporation
• DataStax Inc
• Amazon Web Services Inc & Aerospike Inc.

NoSQL Database Market Segmentation

Global NoSQL Database Market by Type
• Graph Database
• Column Based Store
• Document Database
• Key-Value Store

Global NoSQL Database Market by Application
• Web Apps
• Data Analytics
• Mobile Apps
• Metadata Store
• Cache Memory
• Others

Global NoSQL Database Market by Industry Vertical
• Retail
• Gaming
• IT
• Others

The NoSQL Database market report has been segmented on the basis of various categories such as product type, application, end-user, and region. Each segment is evaluated based on CAGR, share, and growth potential. In the regional analysis, the report highlights the potential region which is expected to create opportunities in the NoSQL Database Market in the coming years. This segmented analysis will surely prove to be a useful tool for the readers, stakeholders, and market players to get a complete picture of the NoSQL Database market and its growth potential in the coming years.

Get Discount On The Purchase Of This Report @ https://www.verifiedmarketresearch.com/ask-for-discount/?rid=129411

NoSQL Database Market Report Scope 

Report Attribute Details
Market size available for years 2021 – 2028
Base year considered 2021
Historical data 2015 – 2020
Forecast Period 2021 – 2028
Quantitative units Revenue in USD million and CAGR from 2021 to 2028
Segments Covered Types, Applications, End-Users, and more.
Report Coverage Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, and Trends
Regional Scope North America, Europe, Asia Pacific, Latin America, Middle East and Africa
Customization scope Free report customization (equivalent up to 8 analysts working days) with purchase. Addition or alteration to country, regional & segment scope.
Pricing and purchase options Avail of customized purchase options to meet your exact research needs. Explore purchase options

 Geographic Segment Covered in the Report:

 • North America (USA and Canada)
 • Europe (UK, Germany, France and the rest of Europe)
 • Asia Pacific (China, Japan, India, and the rest of the Asia Pacific region)
 • Latin America (Brazil, Mexico, and the rest of Latin America)
 • Middle East and Africa (GCC and rest of the Middle East and Africa)

Key questions answered in the report:

  • What is the growth potential of the NoSQL Database market?
  • Which product segment will take the lion’s share?
  • Which regional market will emerge as a pioneer in the years to come?
  • Which application segment will experience strong growth?
  • What growth opportunities might arise in the NoSQL Database industry in the years to come?
  • What are the most significant challenges that the NoSQL Database market could face in the future?
  • Who are the leading companies on the NoSQL Database market?
  • What are the main trends that are positively impacting the growth of the market?
  • What growth strategies are the players considering to stay in the NoSQL Database market?

For More Information or Query or Customization Before Buying, Visit @ https://www.verifiedmarketresearch.com/product/nosql-database-market/

Visualize NoSQL Database Market using Verified Market Intelligence:-

Verified Market Intelligence is our BI-enabled platform for narrative storytelling of this market. VMI offers in-depth forecasted trends and accurate Insights on over 20,000+ emerging & niche markets, helping you make critical revenue-impacting decisions for a brilliant future.

VMI provides a holistic overview and global competitive landscape with respect to Region, Country, and Segment, and Key players of your market. Present your Market Report & findings with an inbuilt presentation feature saving over 70% of your time and resources for Investor, Sales & Marketing, R&D, and Product Development pitches. VMI enables data delivery In Excel and Interactive PDF formats with over 15+ Key Market Indicators for your market.

Visualize NoSQL Database Market using VMI @ https://www.verifiedmarketresearch.com/vmintelligence/

About Us: Verified Market Research®

Verified Market Research® is a leading Global Research and Consulting firm that has been providing advanced analytical research solutions, custom consulting and in-depth data analysis for 10+ years to individuals and companies alike that are looking for accurate, reliable and up to date research data and technical consulting. We offer insights into strategic and growth analyses, Data necessary to achieve corporate goals and help make critical revenue decisions.

Our research studies help our clients make superior data-driven decisions, understand market forecast, capitalize on future opportunities and optimize efficiency by working as their partner to deliver accurate and valuable information. The industries we cover span over a large spectrum including Technology, Chemicals, Manufacturing, Energy, Food and Beverages, Automotive, Robotics, Packaging, Construction, Mining & Gas. Etc.

We, at Verified Market Research, assist in understanding holistic market indicating factors and most current and future market trends. Our analysts, with their high expertise in data gathering and governance, utilize industry techniques to collate and examine data at all stages. They are trained to combine modern data collection techniques, superior research methodology, subject expertise and years of collective experience to produce informative and accurate research.

Having serviced over 5000+ clients, we have provided reliable market research services to more than 100 Global Fortune 500 companies such as Amazon, Dell, IBM, Shell, Exxon Mobil, General Electric, Siemens, Microsoft, Sony and Hitachi. We have co-consulted with some of the world’s leading consulting firms like McKinsey & Company, Boston Consulting Group, Bain and Company for custom research and consulting projects for businesses worldwide.

Contact us:

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WebContainers, Running Node.JS in the Browser

MMS Founder
MMS Guy Nesher

Article originally posted on InfoQ. Visit InfoQ

Stackblitz recently released a new product called WebContainers that enables developers to create full stack Node.js environments within the browser which loads instantly and comes bundled with VS Code, a full terminal, NPM, and more.

Writing and executing custom code inside the browser isn’t a new capability. In fact, vendors have been offering such solutions for a good number of years. In order to offer these capabilities, vendors relied on a remote development environment that would execute the code before streaming it back to the browser.

While these solutions allowed developers to access capabilities and execute languages that are not supported by the browser, they suffer several drawbacks:

  1. Spinning a new remote container can take a noticeable amount of time.
  2. Executing code on remote machines costs money.
  3. The solution requires a stable internet connection and inherently does not support offline work.
  4. Sending the code to a remote server raises some security concerns. 

In order to address the aforementioned drawbacks, Stackblitz has collaborated with the teams at Next.js and Google to create WebContainers, a progressive web application that spawns a Node.js development environment within the browser.

To achieve that, Stackblitz uses the latest capabilities of WebAssembly, and WASI (or WebAssembly System Interface), and Web APIs to create a container that is capable of running Node.js from within the browser. Service workers are then mapped to the Node.js server to serve the HTTP requests.

The result is a web application that can run offline, is surprisingly fast (Builds complete up to 20% faster and package installs complete >= 5x faster than yarn/npm according to Stackblitz), and offers a secure environment to execute code as it runs behind the browser sandbox.

It’s important to keep in mind that WebContainers is still in beta and currently only runs on Chromium based browsers. This limitation seems to be primarily caused by its reliance on recent/non-standard web APIs such as the File System Access API and according to the official Github page should be addressed in future releases.

In addition to the current capabilities of WebContainers, Stackblitz has promised to add several important enchantments including the support of private NPM registries, SQLite, and ES modules. Looking further into the future, it may also be possible to support additional languages such as Ruby and Python.

While the core WebContainers project is not open source, developers are encouraged to get involved by adding support to additional frameworks through the official Github repository and participate in the conversation via the official Discord channel.

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Global Database as a Service (DBaaS) Provider Market 2021-2027 By Top Key Players: IBM, AWS …

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Posted on mongodb google news. Visit mongodb google news

Database as a Service (DBaaS) Provider

Database as a Service (DBaaS) Provider Market Size 2021 Industry Share, Strategies, Growth Analysis, Regional Demand, Revenue, Key Players and 2027 Forecast Research Report

In this report a comprehensive analysis of current global Database as a Service (DBaaS) Provider market in terms of demand and supply environment is provided, as well as price trend currently and in the next few years. Global leading players are profiled with their revenue, market share, profit margin, major product portfolio and SWOT analysis. From industry perspective this report analyses supply chain, including process chart introduction, upstream key raw material and cost analysis, distributor and downstream buyer analysis. This report also includes global and regional market size and forecast, major product development trend and typical downstream segment scenario, under the context of market drivers and inhibitors analysis.

Request for Sample with Complete TOC and Figures & Graphs @ https://crediblemarkets.com/sample-request/database-as-a-service-dbaas-provider-market-889551?utm_source=Priyanka&utm_medium=SatPR

Market segmentation

Database as a Service (DBaaS) Provider market is split by Type and by Application. For the period 2016-2026, the growth among segments provide accurate calculations and forecasts for revenue by Type and by Application. This analysis can help you expand your business by targeting qualified niche markets.

Market segment by Type, covers

➥ Cloud-based

➥ On-premise

Market segment by Application, can be divided into

➥ Large Enterprises

➥ SMEs

Market segment by players, this report covers

➥ IBM

➥ AWS

➥ MongoDB Atlas

➥ Ninox

➥ Aiven

➥ Azure

➥ Oracle

➥ Zoho Creator

➥ Kintone

➥ Beats

➥ Google Cloud Bigtable

➥ DataStax

➥ Caspio

➥ SAP

➥ Fusioo

Global Database as a Service (DBaaS) Provider Market is further classified on the basis of region as follows:

  • North America (United States, Canada), Market size, Y-O-Y Growth Market size, Y-O-Y growth & Opportunity Analysis, Future forecast & Opportunity Analysis
  • Latin America (Brazil, Mexico, Argentina, Rest of LATAM), Market size, Y-O-Y growth, Future forecast & Opportunity Analysis
  • Europe (U.K., Germany, France, Italy, Spain, Hungary, BENELUX (Belgium, Netherlands, Luxembourg), NORDIC (Norway, Denmark, Sweden, Finland), Poland, Russia, Rest of Europe), Market size, Y-O-Y growth, Future forecast & Opportunity Analysis
  • Asia-Pacific (China, India, Japan, South Korea, Malaysia, Indonesia, Taiwan, Hong Kong, Australia, New Zealand, Rest of Asia-Pacific), Market size, Y-O-Y growth, Future forecast & Opportunity Analysis
  • Middle East and Africa (Israel, GCC (Saudi Arabia, UAE, Bahrain, Kuwait, Qatar, Oman), North Africa, South Africa, Rest of Middle East and Africa), Market size, Y-O-Y growth, Future forecast & Opportunity Analysis

Direct Purchase this Market Research Report Now @ https://crediblemarkets.com/reports/purchase/database-as-a-service-dbaas-provider-market-889551?license_type=single_user;utm_source=Priyanka&utm_medium=SatPR

Some Point from Table of Content:

  • Market Overview: It includes six chapters, research scope, major manufacturers covered, market segments by type, Database as a Service (DBaaS) Provider market segments by application, study objectives, and years considered.
  • Market Landscape: Here, the competition in the Worldwide Database as a Service (DBaaS) Provider Market is analysed, by price, revenue, sales, and market share by company, market rate, competitive situations Landscape, and latest trends, merger, expansion, acquisition, and market shares of top companies.
  • Profiles of Manufacturers: Here, leading players of the global Database as a Service (DBaaS) Provider market are studied based on sales area, key products, gross margin, revenue, price, and production.
  • Market Status and Outlook by Region: In this section, the report discusses about gross margin, sales, revenue, production, market share, CAGR, and market size by region. Here, the global Database as a Service (DBaaS) Provider Market is deeply analysed on the basis of regions and countries such as North America, Europe, China, India, Japan, and the MEA.
  • Application or End User: This section of the research study shows how different end-user/application segments contribute to the global Database as a Service (DBaaS) Provider Market.
  • Market Forecast: Production Side: In this part of the report, the authors have focused on production and production value forecast, key producers forecast, and production and production value forecast by type.
  • Research Findings and Conclusion: This is one of the last sections of the report where the findings of the analysts and the conclusion of the research study are provided.

Do You Have Any Query Or Specific Requirement? Ask to Our Industry Expert @ https://crediblemarkets.com/enquire-request/database-as-a-service-dbaas-provider-market-889551?utm_source=Priyanka&utm_medium=SatPR

Important Questions Answered

  • What is the growth potential of the Database as a Service (DBaaS) Provider market?
  • Which company is currently leading the Database as a Service (DBaaS) Provider market? Will the company continue to lead during the forecast period 2021-2027?
  • What are the top strategies that players are expected to adopt in the coming years?
  • Which regional market is anticipated to secure the highest market share?
  • How will the competitive landscape change in the future?
  • What do players need to do to adapt to future competitive changes?
  • What will be the total production and consumption in the Database as a Service (DBaaS) Provider Market by 2027?
  • Which are the key upcoming technologies? How will they impact the Database as a Service (DBaaS) Provider Market?
  • Which product segment is expected to show the highest CAGR?
  • Which application is forecast to gain the biggest market share?

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Podcast: Cliff Berg and Raj Nagappan on Agile 2: The Next Iteration of Agile

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MMS Cliff Berg Raj Nagappan

Article originally posted on InfoQ. Visit InfoQ

Subscribe on:






Transcript

Introductions [00:21]

Shane Hastie: Good day folks, this is Shane Hastie for the InfoQ Engineering Culture Podcast. I’m sitting down today with Cliff Berg and Raj Nagappan. You are two of the authors of Agile 2: The Next Iteration of Agile. Welcome, thanks for taking the time to talk to us today.

Cliff Berg: Our pleasure.

Raj Nagappan: Thanks very much for having us.

Shane Hastie: So Agile 2, why? We’ve got an Agile, it works. Or does it?

Why Agile 2 [00:46]

Raj Nagappan: I think it was quite timely, actually, to come up with another iteration of Agile, given that it’s a 20th anniversary of Agile at the moment. I think that just passed last month or the month before. What’s happened is that the world has moved on, so technology has moved on, business expectations have moved on and customer expectations have moved on. And I think that Agile really needs to catch up, it needs to iterate. So yeah. Agile is all about rapid iterations and the process itself, the philosophy itself, needs to iterate. And that’s exactly what we’ve done here.

Cliff Berg: Yeah, I would agree with that, and it seems like there are really powerful things in Agile. When the Agile Manifesto came out, I was 20 years into my career. And I was CTO of a company at the time, a small company, about 200 people. But we built some pretty significant stuff. B2B stuff that had to work. And we got our feet into Agile very early, so we were early adopters. It was Extreme Programming, actually, in 2000. And then Agile kind of took the mantle away from XP and kind of co-opted it in a way. But there were some really powerful, good ideas that resonate, basically make things simpler. Smaller teams, work incrementally, build a little at a time. Kind of simplify.

My sister loves books on simplify. That’s kind of what it was, simplify. Simplify for IT. And Raj was right, a lot of things have moved on and we have DevOps today which wasn’t really possible 20 years ago because it really was commodity virtualization that made cloud services possible, which really is kind of what made DevOps possible. But some of the core things really resonate. But a lot of dysfunction sprouted within the movement, which is very common with any movement. It’s normal. It’s not really trying to say, “Ah, we did this bad,” or something. This is like normal.

Some of the factors driving the need for course corrections in agile after 20 years [02:38]

Cliff Berg: And we feel that we need some course corrections and some of us also feel that the original ideas were really powerful but they weren’t quite right. They were good, they were great actually, but there were some issues. Especially like if you look at the Agile Manifesto, some of the principles are a little bit extreme, and one thing that I found in my career I believe is that extremes usually don’t work well. Unless you have an extreme situation. I’m not talking about Extreme Programming, that’s a whole topic, we could do 10 podcasts on Extreme Programming, but just in general. Extremes. Whenever I hear something that’s extreme, a red flag goes up.

So anyway, we feel that let’s revisit some of this stuff. And we also kind of tested what people think. We found that there are a lot of people in the Agile community and the IT community, especially among programmers, who feel like there’s some good stuff about Agile but there’s some stuff that we don’t like at all. So what is that?

Agile team rooms, the open plan office, just google that and you’ll see how many people hate that. So there’s some good things about it, it’s not all bad. And some people love it and some people don’t love it, there are differences too, and that’s another thing. The Agile movement kind of became like one size fits all in a lot of ways, like this is how we do it. So it’s been 20 years and we feel it’s a good time to just revisit some of this.

Raj Nagappan: Yeah, I definitely agree with that, and picking up on some of the themes that Cliff has mentioned, so when the Agile Manifesto came out, one of its key strengths was its simplicity. And that’s what enabled it to take off like a rocket, and simple messages spread very fast. The problem with simple messages though is that they’re also open to interpretation, and we’ve seen that in the intervening 20 years, we’ve seen Agile interpreted in many different ways and misinterpreted in many different ways too.

So for instance, the manifesto itself says we value the things on the left and we value the things on the right. In a lot of misinterpretations people will take that to say okay, we value the things on the left and not the things on the right. That’s like a common misappropriation. I think you can look up the Dark Agile Manifesto which says exactly that.

In itself, the Agile Manifesto was a great blueprint but I think it needed a bit more rigor around it, it needed a bit more fleshing out of well, actually, this is what we meant. We meant this and not that. So that’s how we ended up coming up with a bit more clarification.

Shane Hastie: What is the clarification? What are the key, I suppose we could say, themes or dare we even say values from Agile 2?

Introducing Agile 2 [05:11]

Raj Nagappan: Agile 2 has values and principles the same way that the original Agile Manifesto did. The first difference you notice is that there’s a lot more of them. So we have six pairs of values and we specifically say we value both of these things. So altogether, within those six pairs of values, you’ve got a dozen values altogether. And then in the principles we have 43 principles, I believe, and they’re grouped into a number of groups, how many groups are they? 10 groups. So 10 different areas.

It looks like a lot but there’s a lot of different ground that needs to be covered, because Agile software development, Agile development in general, whether it’s for software or hardware or anything else, is quite a complicated process, it’s quite a complicated beast. There are a lot of different things that you have to do.

But to come back to your question, I think probably the two most important themes that I would say that has come out for me from this process has been balance. So balanced the things on the left with the things on the right, that’s critical. And the other one is leadership. I think that leadership has been sorely missing from Agile up until this point and a lot of the dysfunctions that we see are from disconnects between conventional leadership and how Agile teams want to work. So that has created a real schism or a real friction and Agile 2 has a real focus on effective leadership.

Shane Hastie: Let’s explore those two themes. I see one of the values there, individual empowerment and good leadership. So individual empowerment, well, is it individual or is it teams? But there again there’s another value, individuals and teams. Oh, this is getting interwoven.

Raj Nagappan: Yes.

Shane Hastie: So let’s explore the leadership one.

Teams are made up of individuals – make sure you support them [06:45]

Raj Nagappan: Okay, so we’ve mentioned three different concepts here. So we’ve got leadership, we’ve got teams, and we’ve got individuals. And what happened in the original Agile is they basically talked about teams to the exclusion of the two others. But what you have to remember is even though there’s no I in team, teams are made up of individuals. And if you don’t also respect the aspirations and the requirements and the emotional needs of the individuals then your team’s not going to be effective.

For example, in a sports team, you can take a whole bunch of world-class athletes and you can put them together in a team and the common saying is that okay, well if the team isn’t coordinated then those athletes aren’t going to perform well together. But the reverse is also true, which is that if you don’t motivate those individual athletes to contribute to the team in a meaningful way and to feel comfortable, psychologically safe, feel like their aspirations and so on are taken care of, then they’re not going to have that bipartisan relationship, they’re not going to contribute to the team.

Coming back to the team versus the individual, so what that means is that you have to not only look after what the goals of the team are, to produce code, to produce output at the end of every sprint, things like that, but you also have to look after what the actual individuals need.

These might be things like career development, ability to focus deeply on their work, ability to care about their work. So not only collective ownership but to actually take a kind of possession where they look after it and they nurture it. Those kinds of things are important to them.

Then coming back to what you’re saying about the leadership, so leadership is the one who has to empower that. So if leadership does not provide for those individuals to be nurtured and to be looked after, then you’ll find that your team becomes shaky and the wheels will fall off the wagon eventually. And we do see that in quite a few dysfunctional teams where the individuals are unhappy, leadership is not looking after the individuals, they’re just looking at the team level. Then everybody’s locking heads with each other.

Shane Hastie: How does that good leadership show up?

Good leadership nurtures teams and individuals effectively [08:35]

Cliff Berg: You know, you have to realize we talked about this for almost a year before we put a bow around it, 15 people. Remotely, by the way, because it was during COVID. But how does leadership show up? Well, that’s the rub. People have written about leadership for thousands of years, it’s not a new thing, there are thousands, maybe millions, I don’t know, books about it. First you have to decide what are your leadership models and how do you put it in place? It’s just like self-organizing team but how do you create that team, who creates that team? Well, someone has to have some leadership to create the team in the first place.

We believe it takes leadership to actually properly constitute a team and to incubate it and watch it, especially if it’s less experienced people or people with divergent ways of working. So deciding on what good leadership looks like, it probably looks like many different things. There isn’t just one kind of leadership you need for most endeavours, you need several kinds of leadership. And to some extent you let it emerge but also you cannot just let it emerge because that can be very dysfunctional too if you just let leadership emerge. That can be just as bad as having autocratic leadership. It depends.

Raj Nagappan: That’s a good point which Cliff raises, which is that if you don’t appoint a leader then one will emerge from the group. And the person who emerges from the group may not necessarily be the most egalitarian leader, let’s put it that way. They may well be someone with their own motives or with their own autocratic way of working and it just so happens that they’re the most forceful in the group and that they force their will on to everyone else.

Different leadership styles needed in different contexts [10:20]

Cliff Berg: Yeah, and it might not be forced. Force might be soft force, it could just be like they’re very charismatic. There was a study I saw some time back where it turns out that in remote teams, different people tend to emerge as the leader if you allow for emergent leadership. In remote teams, it tends to be like the organizer. The person who’s moving stuff along.

Cliff Berg: Because think about it, people are sitting on their computers and there’s no one to come around and say, “Let’s all get together.” So it tends to be the person who schedules a Zoom meeting at 10 o’clock tomorrow and creates an agenda. You know, the organizer. That person tends to end up becoming the default leader over time.

Whereas, in in-person teams it tends to be the person who looks like a leader. This is based on a study that I read, it tends to be the person who fits some kind of leadership stereotype. It’s a different person.

Cliff Berg: I find that interesting, not so much because of the kinds of people who tend to get chosen but the fact that it’s different, which kind of proves to me that the selection process for an emergent leader is not a trustworthy process. It can vary depending on whether people are in-person or not. And there also are studies of organizations that have very loose structure and interestingly, at the turn of the last century in the early 1900s, hierarchy, which we know can be very toxic, so I’m not advocating traditional hierarchy, but hierarchy was seen as a solution to lack of structure which tended to favor nepotism and the most aggressive and charismatic person.

Hierarchy was seen as the way that today we see Agile as the solution for hierarchy, 100 years ago hierarchy was seen as the solution for emergent leadership. So which is it? Well, it turns out it’s neither. You don’t want either one. You want something much more nuanced and sophisticated, and that’s why leadership is the most complex issue of all in this, and what does good leadership look like? What are the many forms of good leadership? How do you get them to be creative? And that was your original question chain.

Cliff Berg: And that’s the hardest question, how do you put them in place? That’s cultural change. The Agile community is always talking about cultural change. So Agile coaches generally know senior leadership needs to demonstrate themselves the right paths. But they need to also decide on the patterns and getting that cultural change is the hard problem after you decide what kinds of leadership.

And there’s more to it. I’m going to stop but there’s more to it, because I mentioned hierarchy is not what we want but we do need hierarchy to scale. But today the issues tend to be cross-functional. They tend to cut across the org boundaries. So you need leadership in multiple directions at different times. So things have become very messy today. That’s why it’s so difficult.

Socratic leadership and the Coaching Kata [13:21]

Raj Nagappan: I’ll give you two concrete examples of kinds of leadership that I think we have found in the group that have been quite effective. The first one is Socratic leadership, which is the idea of asking questions as opposed to dictating commands. That’s based on the Socrates model of telling me why is this, tell me why is that, the five whys for example.

And getting the individuals in the team to basically, to get to the root of a problem by asking them to go through the process of identifying the root cause. So that tends to be quite a good, empowering way because it means that the individuals whom you’re coaching, they’re the ones who are actually coming up with the answers rather than you telling them.

A second way, which is a variant on the same thing, is the Coaching Kata. So the Coaching Kata from the Toyota lean process basically does exactly the same thing. You have a mentor and a mentee relationship. And the mentee is the individual whom you’re trying to get to do the work. So you go through the process of coaching them and enabling them to come up with the answers themselves and to become more empowered. So you look at it more of a point of you as a coach rather than as a manager as such.

Shane Hastie: So that was leadership, and you’re right, we can go on about leadership for a long time. But we’ll point people to some of those leadership resources. Balance was the other important theme. Tell me about balance.

Balance is key –  every decision is a contextual decision [14:40]

Cliff Berg: Actually, Raj has talked about that a little bit and he mentioned the values. Actually, the other day on LinkedIn, someone looked at the Agile 2 values and basically said, “I don’t like it because you’re equating this with that.” Because our values say, “We value this and that.” And some of the things that we say we value sound kind of un-Agile. We value planning and contextual decision making, which I forget what it exactly is.

Raj Nagappan: Adaptability and planning.

Cliff Berg: Adaptability and planning. So his thought was you’re not saying one’s better than the other. And that was intentional and it’s because it depends. It depends on the situation. You do need planning. You also need adaptability and sometimes you need more of one than the other. Generally in an Agile context we assume you want more adaptability and we generally do, but we don’t want to throw planning out. Like Raj mentioned, the Dark Agile Manifesto is a parody of Agile and it basically says we value this not that.

You do need those other things. One of the major points of Agile 2 is we feel that the Agile movement was a rejection of trying to manage projects by numbers and by checklist. Not that checklists are bad, checklists are really important, but you have to know what you’re doing. Every decision is a contextual decision. It’s not like do this then this, there’s not a procedure. Managing projects is not a procedure, it’s a sequence of contextual issues that expose themselves over time. So it always depends. Malcolm Gladwell, the only right answer is it always depends.

So balance is about recognizing that every decision, an organization’s trying to create products and do hard things. Every decision’s a contextual decision. You cannot prescribe we should always do it this way.

Raj Nagappan: Yeah, I agree. I think with the planning and adaptability example, you can’t do anything significant in life without creating a plan for it in some way. So for instance, if you’ve got a startup, if you’re trying to raise money, you can’t raise money without a plan. If you’re trying to build a building, a house or an office tower or something like that, you can’t build that building without a plan. You can’t even bake a cake without a plan. I mean, have you seen an Agile cake? It might turn out great and it might be a complete flop, and that’s the risk. So there is an old saying, which is that there’s value in planning and it’s certainly true.

When we look at how Agile swung the pendulum, they said okay, well we’ve gone way too far from the right, which is really, really concrete plans which go down into the hundreds and hundreds of pages, which we didn’t end up following anyway. So let’s throw that out and let’s swing the pendulum all the way to the left and let’s do no planning whatsoever.

More accurately, let’s do very, very lightweight planning. So just two weeks at a time and no further than that. What we’re seeing is that any broad scale initiative, you need to be able to plan further ahead than two weeks at a time. Maybe not in such detail that we were talking about earlier where you’ve got a 300 page plan, but you do need to have a sense of direction.

We see this not only with Agile too but also within the broader Agile community. You see concepts coming back in like product vision and product goals. So these are quite big in the product management area at the moment, and even the latest version of The Scrum Guide has added a product vision in there which it didn’t used to have. So you see that balance actually coming back in the industry broader overall, not just in Agile 2.

These are not new ides – they are the distilled result of experience [17:55]

Cliff Berg: Actually, there’s a point there I’d like to make that Raj kind of just alluded to. In Agile 2, there are no new ideas. There are no new ideas in Agile 2. We haven’t talked about how Agile 2 was created but it was 15 very experienced people with a wide range of background, not just all programmers. It was product design, human resources, DevOps and programming of course, but other things. And the ideas of Agile 2 are ideas that we would hear and experienced ourselves when this stuff works.

If you talk to people who really do this stuff well at scale where they get complex products out rapidly and things are going well, this is generally what’s in their head. This is how they look at it. So it’s not like these are new revolutionary things. What we’ve tried to do is take all that wisdom that many Agilists have, including DevOps people, and Jez Humble, father of DevOps, always identified as an Agilist.

Taking those ideas from people who really know this shit. We’ve tried to add that stuff to the Agile narrative because it wasn’t there. There have been very opinionated books, Klaus Leopold, Reinventing Agile, a lot of books basically saying, “Hey, we’re doing it all wrong.” But those are seen as opinionated and so some people love them and some people hate them.

We feel that the stuff that’s the goal, what really works needs to be part of the standard narrative. So we’re trying to enhance the standard Agile narrative with the wisdom and more nuanced understanding of these things.

Shane Hastie: One of the questions I had, because I was asked to look at this very early on, was why carry on calling it Agile?

These ideas are an iteration of agile approaches – not a replacement [19:40]

Cliff Berg: We debated that a lot.

Raj Nagappan: Yeah, so we had quite a few names which we debated and went back and forth with. One of the things is that there’s significant brand value with the name Agile, and the subtitle of Agile 2 is the next iteration of Agile. We really felt that this was an evolution or an iteration on the original Agile concepts.

As we were debating the other different names, we have people who were involved in some of those other different movements, for example Agnostic Agile and so on. We always came back to the most powerful, simple name, the one which had the most impact and which people could get behind the most was Agile 2.

Cliff Berg: So we wanted to make it clear, we’re talking about Agile, not some special type of Agile like XYZ Agile or something. We wanted to make it clear we’re talking about Agile.

Shane Hastie: So if we come back to some of those values where you touched on adaptability and planning, individual empowerment and good leadership, individuals and teams. The next one in your chain there is business understanding and technical understanding.

Business understanding and technical understanding [20:40]

Raj Nagappan: So actually, I’ve got a very good example of this. A company I used to work for, they worked in the legal software space. And the thing about the legal software space is that you need to know your customers very well and their processes, their work processes are quite complicated and quite convoluted, and they’re very high risk.

The problem is if you do something wrong as a software developer and you work with the data wrong, then the evidence which your software is being used to detect will be thrown out of court. And that’s bad, right? So for example, if you’re trying to prosecute a criminal and that criminal might be like cyber crime or organized crime or a drug dealer or something like that, arms dealer. These are like significant crimes that this software is used for. So that’s a bad consequence of the programmer making a mistake, it’s not just like it’s a blue button rather than a red button.

What I found was, because I had worked for this company for quite some time, I got quite a good understanding of what the particular customers workflows were and what their particular needs were. And as the company got bigger and as we had more and more developers coming into the development group, they didn’t come from that background. They didn’t have that understanding. Because how many developers, how many software engineers have worked for a legal software company? Well, it’s pretty small, it’s a pretty esoteric area. There’s not much of a crossover.

What happened was I ended up spending a lot of time coaching my newer developers as to what the actual business requirements were. Because they would look at a piece of paper, they would look at a requirement, and they’d say, “Okay, well I think I can do it this way and not that way.” And I’d say, “Actually, no, you have to do it that way not this way because this is what’s going to happen when it goes into the real world, when the lawyers use it, and when they submit it to court it has to satisfy all of these criteria.”

That’s a really good example where the technical side, where the developers and the designers and the testers, they have to have a very, very good business understanding of how the business works and what the business demands are for that product which they’re making.

Then the same is also true on the other side, because I would talk with the marketing people and the salespeople and they would say to me, “Our customers are asking for XYZ, they want to have this particular feature, can we make it work?” And some things I’d say, “Yeah, okay, that’s easy to do,” and other things I’d say, “Well, that’s not really possible, it’s very, very difficult.”

And what we see is that the best companies, you look at all of the Silicon Valley giants, the ones who really are kicking goals and kicking it out of the park, their business function and their technical function are very, very well in tuned with each other. It’s like a yin and a yang diagram. The technology people understand the business, what it is that they’re trying to sell, and the salespeople, the sales side, they understand the technology, they understand what’s feasible and what’s not feasible. So we can’t split off things into different divisions, into silos. Those two parts of the business have to really work together. That’s what I’ve found.

Cliff Berg: Yeah, it’s true. I mean, most companies today, most companies that aren’t the corner drug store operate on a technology platform. Whether it’s a web platform or something non-computer but… Like Tesla, they make cars but their factories and design systems, that’s their technology platform. Which have a very huge digital component to them.

And the value proposition today often is not just what do we sell but how do we make it? Because that affects how fast we can turn out new versions and things like that. Today, for a product manager to make good trade-offs, they have to make trade-offs between we’ll add a new feature or improve our time to market by changing how we do stuff. Improve our time to market or shorten our time to market while retaining the same quality, by changing how we do it. That has business value.

Can we get time to market down from two months to three weeks? That has a lot of business value. But they have to trade that off with hey there’s some new feature we could have. So to be able to make trade-offs, they kind of have to have some level of understanding, not just of the product but how it’s made too. So they can have those discussions and make those choices.

Like Raj said, you cannot be in a silo, you cannot just say, “All right, that’s technical, I don’t need to know that.” And the technical people also need to understand what the heck is this product, how are people using it? Otherwise they can’t fill in the blanks. They’re basically acting like robots painting by numbers. People need to understand the whole flow. Up to some level. Not the experts and everything but to be able to hold good conversations about the entire flow, today really essential for everybody.

Shane Hastie: So the next one in the list of values is the outcomes and outputs.

Outcomes and outputs [25:14]

Raj Nagappan: Yes, so outcomes are very fashionable at the moment. In the product management area in particular, a lot of people are talking about outcomes over outputs. So what’s traditionally happened with Agile is that people have focused on the outputs. So Scrum is a very good example of this, where you have a sprint, your sprint lasts two or three weeks, and then at the end of it you have an output, you have a product increment. So this is a tangible artifact, a piece of software typically, which is something that is spit out at the end of the sprint which is the result of your work. That’s an output.

But what people have found is that you can do all of that and you can do that sprint after sprint after sprint, but your customers don’t necessarily get value out of that. You might have a lot of features which they don’t end up using, if they use it maybe it’s marginally or maybe they don’t use it at all or maybe it doesn’t live up to their expectations.

That’s why the conversation shifted from outputs to outcomes. So outcomes would be that the customer is actually using the feature, that they’re getting value out of it and that it’s helping them to solve some problem in their life. I think Kathy Sierra, I think she talks about your customer doesn’t value using your software, your customer values getting on with their life and achieving some goal in their life. Your software, your product, whatever it is that you’re making is really just a means to an end for them to do that.

That’s how the conversation shifted over to say okay, we value outcomes. But the balance comes back to say okay, well outcomes are only really enabled by outputs. You have to do both. So you have to both make a meaningful contribution to your customer’s life, you have to make them be able to solve their task or to solve their goal, and you also have to provide the concrete, tangible product which does that. So both of those things matter. So coming back to the theme of balance, you can’t have the outcome without the output being realized.

Shane Hastie: And the last one, thoughtfulness and prescription.

Thoughtfulness and prescription [27:06]

Raj Nagappan: I’ll let Cliff go on that one.

Cliff Berg: Yeah, Raj is letting me go with that because he knows that’s near and dear to me. In fact, there were two areas during the development of this where we had a lot of contentious debate. One had to do with soft forms of leadership and the other had to do with what effective collaboration looks like. So much of Agile 2, it depends. It depends on the individuals, it depends on the circumstances, but we felt that the Agile movement in reaction to horrible dysfunction in the 1990s where, Shane maybe you experienced some of this, where someone would hire a consulting company to create a requirements document, and then they’d give that to another company to create a design and then they’d give it to another lowest bidder to implement the design. Maybe you can do that for a bridge, but you can’t freaking do that for software. You end up with garbage, people won’t understand the design, because they didn’t create it and there’s no one to ask about the requirements because that consulting company left.

So basically it’s like giving someone a big document on music theory and say, “Here, learn to play the piano.” So we realized that the Agile community, in reaction to that, basically said, “Let’s stop doing that, let’s have conversations.” Which is really powerful. That’s what you need. But you also need documents too, but good documents, not big stupid documents. You need the right documents made by the right people who are still there and having conversations. The people doing the work should be creating the documents because writing something down is part of the learning process, it’s part of how you figure out what it is you’re going to do.

It’s like we replaced one dysfunction with another dysfunction, and that comes into how do people collaborate effectively? One of the principles in the Agile Manifesto I actually think is wrong. All the others I think they’re misinterpreted or taken to an extreme, but there’s good stuff there. There’s one that I actually think is wrong because it’s expressed as an absolute. It says the best form of communication is face-to-face.

Well, it depends. That’s true sometimes but sometimes that’s not true. If you say it like that it’s a false statement. Collaboration about simple things, yeah. Hey Joe, what’s the data type of the customer ID field? Oh it’s a string, okay, thank you. Yeah, face-to-face. Of course, you just disrupted Joe, he was deep in thought and now you just scattered his thinking. But you got what you wanted really quickly and really effectively.

But if you want to talk about something complicated, some people like to immediately sit down and start talking about it but not everybody. Some people say, “Let me collect my thoughts on that and I’ll write down what I think and I’ll send it to you and then maybe we’ll get together tomorrow and talk.” People work differently. And for complex things, you need to allow people time to mentally build their mental model. Effective collaboration involves listening, talking, reading, writing and thinking. Those five things.

And if you short circuit one of those you potentially derail people’s process. And again, people are different. Some people like to write, some people like to talk. Their brain’s different and that’s okay. We need to try to meet people where they are to the extent we’re able to. But the Agile community, not just in going too far with the face-to-face communication. Which is a good thing, face-to-face communication is a good thing, but we went too far with it. We made it an absolute, we made it an extreme. It’s like always the default, always have a meeting, always talk.

We also, in order to encourage the always talk, we put people in rooms sitting side by side where they can’t focus. I myself can distinctly recall being in such rooms where I’d be working on something that was complicated and someone will walk by and start having a conversation with someone else and I would literally stop thinking until they were done. And I would pretend I was still staring at the screen, I was pretending to be working but I literally completely stopped my thinking for 10, 15 minutes until they finished. Then I was so frazzled I would get up and go get a cup of coffee and come back and kind of rebuild the mental body I had. So basically they took half an hour away from me.

Raj Nagappan: That’s the concept of flow, right? Because flow is very easy to break and can be very difficult to get back into. One of the arts of learning how to control your flow state is being able to get back into that quickly, right?

Cliff Berg: Well, to get back into it because what happens when you get into a state of flow is you build a very detailed decorated mental model of a problem and what you’re trying to do, you’re trying to solve the problem. So that means that there are conditions that you’re trying to meet. And so you’re testing your mental model against what happens if this happens? Inputs, basically, to see if the mental model predicts the outputs that you want. Does my solution actually work?

And if someone disrupts that mental model, basically parts of it fall off and then when they go away and you try to get back in the flow, you have to go back to that mental model and fix all the broken pieces. You have to refresh those parts of the model, think them through again. Then finally when it’s all fixed, that’s when you’re ready to resume.

So depending how long the interruption is, and how distracted you get, the more distracted, the more interrupted, the more pieces fall off and the longer it takes you to rebuild the broken parts of that mental model.

The importance of concentration and flow [32:43]

Raj Nagappan: Yeah, I think that’s one of the more important principles that we had in our list of principles, is you really need to give people the ability to focus and to not distract them. I think face-to-face conversations is one way that you do end up distracting them, but to bring that back to the face-to-face example, a simple example of that is how many times have you had a thought in the shower or a thought when you’re going to bed or a thought when you’re eating dinner?

So, they happen asynchronously, it’s like what Cliff is saying about the mental model. When your mind is not consciously occupied on that problem, the cogs sort of start churning and they eventual come into place. So there needs to be a variety of communication mechanisms, not one solution fits all, and we really need to respect people to communicate sometimes but also to be able to maintain deep focus and concentration at other times. I think those two ideas go hand in hand.

Cliff Berg: This is actually an area where leadership, a particular kind of leadership, really helps. Because if you have a group of people, let’s just say it’s kind of random, or say you have a group of six people. Three out of the six have a general preference for let’s always get together and talk it through. Maybe they’re extroverts, I don’t know what they are, but they tend to like to get together and always talk it through.

And the other three say, “Well I’m not ready to talk, I want to go and think about this. Don’t bother me right now, I want to think it through. Maybe I’ll write some things down but I’m not ready to talk yet.”

Raj Nagappan: Right, so they’d say, “Let me come back to you on that.”

Cliff Berg: Yeah, let me come back to you on that. And so if you have a group like that that are kind of like well what do we do? The people who want to talk it through will be confused and they’ll think the others are being difficult or something like that. And the people who wanted to think it through are thinking that the other people are being aggressive and obnoxious and are not giving them a chance to like mentally process this.

So immediately you have a disconnect and there’s no one orchestrating it to kind of show those differences. What can really help is if you have someone who is a Socratic leader who has a good skill of architecting good discussions. A discussion isn’t necessarily a onetime event, it’s over time, where they’re sensitive to who tends to work in what way and who’s asking for time, who’s asking for a meeting, and then interpreting and suggesting.

I think that these three people need some time to mentally process. But they do want to talk about it and you other three, you want to talk right away. Bear with them, give them some time, and what if we all meet and talk about tomorrow at 11:00? Yes? Yes? Okay. So someone to kind of orchestrate that and find a solution that works for everybody and then be ready to pivot. Look at how it goes, see if they still need more time, see what comes out. Someone needs to be kind of watching that in order to make it go well. It might go well on its own, but it probably won’t. But if you have someone who’s good at that they can vastly increase the chance that it will go well and keep moving forward. And that’s a form of leadership.

Shane Hastie: Thank you for that. One of the challenges, sometimes criticisms of the Agile Manifesto was it was the work of 17 middle aged white men getting together in a ski resort. Who was behind Agile 2?

Intentionally aiming for diverse viewpoints in the Agile 2 team [35:52]

Cliff Berg: We intentionally did not create a homogenous team. We actually created a table of the skills we wanted to cover, and it was important to have a global team, which we did. I mean, Raj is the other side of the world from me. I was joking to him that he’s sitting upside down.

Raj Nagappan: And it’s tomorrow.

Cliff Berg: Yeah.

Shane Hastie: That’s right.

Cliff Berg: We have a very mixed team. And we have a range of skills. And the other thing is the authors of the Agile Manifesto, I think they had pent up thoughts. They had been emailing each other kind of ad hoc for a long time before they all got together. It was kind of a group of people, I think the ones driving it I think were the kind of people who want to get together and talk, because they didn’t actually come up with anything until they met.

Whereas, if it were me, I would have tried to come up with it first and then got together in person to iron out differences. Because people work differently. But the fact that they didn’t actually try to come up with something they agreed with until they actually met kind of tells me something about the people who were pushing that initiative.

But what they came up with was pretty freaking good, but most people don’t realize they only came up with the values. They didn’t come up with the principles in that meeting, they came up with the principles later over email, some of them emailing back and forth.

Raj Nagappan: That’s actually true because that’s documented in Bob Martin’s book, Clean Agile, in the introduction. He does go into some detail about how, at Snowbird, they only created the four values and that the 12 principles were created by an email train back and forth in some weeks after.

That actually kind of negates one of the principles, which is that the best form of communication is face-to-face because the 12 principles of the original Agile Manifesto weren’t created that way, right?

Cliff Berg: I think that that principle came from Alistair Cockburn, because he essentially had written that before the meeting in many of his blog posts. I think he might have had a book about it. But he had his famous chart and so on and then it ended up in one of the principles, essentially what he had been saying. That’s the one I have the most problem with because it’s an absolute.

But they came up with these four values, which were good, but yes it was a pretty homogenous bunch of guys. Most were from the US, there were a few from the UK and one from the Netherlands. And they came up with four values and then they went home. Whereas the Agile 2 team worked pretty diligently for more than six months and started from the premise of what’s wrong and how do we fix it and then distilling consensus out of that.

The principles were what we got consensus on. So 15 experienced people all agreed to each of those 43 principles. That was a big lift, achieving that. We went through a lot of iterations, oh my god. We had Google Documents where we would have so deeply nested, because we couldn’t meet in person, we couldn’t even meet on Zoom because we’re all over the world. A guy in Vietnam, Raj in Australia. So there was no way to meet face-to-face, it just wasn’t possible.

We had to figure out how to do what GitLab likes to call asynchronous communication, and so we used every form available. We used Slack, we used email, we used Google Documents, and we had massively nested, complex, in like 20 different colors of back and forth discussions about different topics.

First we identified all the things that troubled us, and then we asked well why is that happening? What do we think? And then what should we do about it? Then finally we distilled the principles. Then finally we rolled those out and created a structure around it. Raj actually is the one who came up with the final structure. We had kind of a competition going.

So my point is that it was a major initiative. It wasn’t a ski weekend, it was a major initiative doing that and we included in the content all of those problems and insights that we had along the way. Not everybody agrees to all of those. It made the list of a problem or insight if at least two people thought it was a problem or insight. But what we agreed on altogether were the principles, but we included everything. Basically you can see the why. For each principle you can see why do they think that? Then you look at all the problems and insights and then you can see why and then you can realize hey, that doesn’t apply to my situation so forget that principle. Or now I understand what they’re getting at, so now I can apply the principle intelligently. Because these principles aren’t black and white. Maybe a little bit of this, a little bit of that.

Raj Nagappan: Yeah, so I think on the Agile 2 website you can click into each of those principles and it will take you to a much longer document and that longer document contains most, if not all of those points that Cliff was alluding to. So a lot of that stuff basically happened from many, many different back and forth conversations between two people or small groups of people. Then we took that and we nested it altogether and arranged it into groups and looked for common themes to drop out. And that’s how the 43 principles came about.

So if you have some time it is well worth looking through, clicking into some of those principles, rather than just learning the one headline and looking into some of the actual problems and solutions and insights that led to the generation of that summary. Because some of them are quite deep, quite deep the insights which we’ve realized there.

Cliff Berg: It actually was a criticism. There were a few people when we published it who said, “Well, it’s too long.” So would you say oh the encyclopaedia’s too long? I mean, this is complex stuff. Building products is not simple stuff. There’s on Agile coach who I know, I’m not going to name them, but very sharp guy. I just talked to him the other day but early on he said, “Well, the Agile Manifesto, it was short and emotional. I can get emotional about it, I can keep it in my head.” I said, “Well, that’s not what we tried to do. We’re not trying to create something emotional. We’re not trying to create a call to arms, let’s throw everything out.”

The Agile Manifesto was like let’s throw out waterfall, good riddance. Burn waterfall at the stake, definitely. But we’re not trying to do that, we’re not trying to throw something out. We’re trying to shore something up. So it’s not emotional by design. It’s not a short manifesto. It’s a thoughtful treatise on this is how you make that work. These are the ideas that if you really drill in you discover these nuances and so here’s food for thought. It’s a lot of food for thought, is what it is. That’s why it’s not short by design.

Shane Hastie: Thank you very much for that, gents. It’s been a really enjoyable conversation. If our listeners want to continue the conversation, where do they find this?

Cliff Berg: There’s the Agile 2 website, which is agile2.net. We also wrote a book, which was a major undertaking, seven of us. There were 15 people who developed the Agile 2 content, but then we basically called out who has time and interest in creating a book version and so we created a book. The book is not a textbook, it’s not like all the Agile 2 principles explained or something like that. It basically makes the case in a very readable way and kind of explains it. So it’s a different kind of thing. So either one.

Raj Nagappan: There’s also the LinkedIn group. We have an Agile 2 LinkedIn group where there’s a community there and you can come and ask questions about it and gain further clarification. We’ve already had quite a few people come along there and post their problems as to how their current day-to-day workplace problems and said, “Well, how would Agile 2 handle this?” So that’s a good resource to try. The Agile 2 community on LinkedIn.

Shane Hastie: And we’ll include all of these links in the show notes. Again, thank you so very much for taking the time to talk to us today.

Cliff Berg: Our pleasure.

Raj Nagappan: Thank you very much for having us.

Mentioned

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NoSQL Software Market Size 2021: By Growing Rate, Type, Applications, Geographical Regions …

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