Month: January 2024
MMS • Steef-Jan Wiggers
Article originally posted on InfoQ. Visit InfoQ
Google recently announced that it will eliminate exit fees for customers who wish to stop using Google Cloud and migrate their data to another cloud provider and/or on premises.
The company is the first cloud provider to do so and calls for a renewed regulatory focus on the most prohibitive form of lock-in for customers: anticompetitive licensing. The change applies according to the company for all customers globally. In addition, the company states that some legacy providers leverage their on-premises software monopolies to create cloud monopolies, using restrictive licensing practices that lock in customers and warp competition.
Amit Zavery, GM/VP, Head of Platform at Google Cloud, writes in a Google blog post:
The complex web of licensing restrictions includes picking and choosing who their customers can work with and how charging 5x the cost if customers decide to use specific competitors’ clouds, and limiting interoperability of must-have software with competitors’ cloud infrastructure. These and other restrictions have no technical basis and may impose a 300% cost increase to customers. In contrast, the cost for customers to migrate data from a cloud provider is minimal.
Google feels that to enable customer choice and competition in the cloud market, there is a need to address and eliminate the restrictive licensing practices currently serving as the primary obstacle. Earlier, the company criticized its rivals on these practices to US and European Union officials.
In a recent cloud services market investigation by the Competition and Market Authority (CMA) in the UK, one of the highlights of harmful competition was that “Egress fees harm competition by creating barriers to switching and multi-cloud leading to cloud service providers entrenching their position.“
A respondent on a Hacker News thread commented:
I read through a couple of these responses to the CMA by MS, Google, AWS, and their smaller competitors; as expected, the hyper scalers refuse to acknowledge that the free ingress and expensive egress is a lock-in mechanism, and their smaller competitors complain bitterly about this.
And:
The hyper scalers say they have to charge egress fees to pay for the costs of building their networks, but for some reason, this doesn’t apply to ingress (which they’re silent on); if they want to play this game, then the CMA should simply make them charge the same for ingress and egress that way, they can “fund their network costs” without issue, and if they want to make them both free then that’s their decision.
Lastly, when customers like to exit from the Google Cloud Platform, they are eligible for free data transfer when data resides in Google Cloud data storage and data management products and other criteria mentioned on their Google Cloud exit page.
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Assetmark Inc. lifted its stake in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) by 247.7% in the 3rd quarter, according to its most recent disclosure with the Securities and Exchange Commission. The firm owned 18,952 shares of the company’s stock after buying an additional 13,502 shares during the period. Assetmark Inc.’s holdings in MongoDB were worth $6,555,000 at the end of the most recent quarter.
Several other institutional investors and hedge funds have also made changes to their positions in the stock. Simplicity Solutions LLC lifted its stake in shares of MongoDB by 2.2% during the second quarter. Simplicity Solutions LLC now owns 1,169 shares of the company’s stock worth $480,000 after buying an additional 25 shares during the period. AJ Wealth Strategies LLC lifted its position in MongoDB by 1.2% during the second quarter. AJ Wealth Strategies LLC now owns 2,390 shares of the company’s stock valued at $982,000 after purchasing an additional 28 shares during the period. Assenagon Asset Management S.A. lifted its position in MongoDB by 1.4% during the second quarter. Assenagon Asset Management S.A. now owns 2,239 shares of the company’s stock valued at $920,000 after purchasing an additional 32 shares during the period. Veritable L.P. lifted its position in MongoDB by 1.4% during the second quarter. Veritable L.P. now owns 2,321 shares of the company’s stock valued at $954,000 after purchasing an additional 33 shares during the period. Finally, Choreo LLC lifted its position in MongoDB by 3.5% during the second quarter. Choreo LLC now owns 1,040 shares of the company’s stock valued at $427,000 after purchasing an additional 35 shares during the period. 88.89% of the stock is currently owned by institutional investors and hedge funds.
Insider Buying and Selling at MongoDB
In other MongoDB news, CAO Thomas Bull sold 359 shares of the stock in a transaction that occurred on Tuesday, January 2nd. The shares were sold at an average price of $404.38, for a total value of $145,172.42. Following the sale, the chief accounting officer now directly owns 16,313 shares of the company’s stock, valued at approximately $6,596,650.94. The sale was disclosed in a legal filing with the SEC, which is available at the SEC website. In related news, CFO Michael Lawrence Gordon sold 7,577 shares of the stock in a transaction on Monday, November 27th. The shares were sold at an average price of $410.03, for a total value of $3,106,797.31. Following the transaction, the chief financial officer now directly owns 89,027 shares of the company’s stock, valued at approximately $36,503,740.81. The transaction was disclosed in a legal filing with the Securities & Exchange Commission, which is available at this link. Also, CAO Thomas Bull sold 359 shares of the stock in a transaction on Tuesday, January 2nd. The shares were sold at an average price of $404.38, for a total transaction of $145,172.42. Following the completion of the transaction, the chief accounting officer now directly owns 16,313 shares in the company, valued at $6,596,650.94. The disclosure for this sale can be found here. In the last three months, insiders have sold 147,029 shares of company stock valued at $56,304,511. Insiders own 4.80% of the company’s stock.
MongoDB Stock Down 0.3 %
NASDAQ:MDB opened at $391.59 on Friday. MongoDB, Inc. has a 1-year low of $179.52 and a 1-year high of $442.84. The company has a current ratio of 4.74, a quick ratio of 4.74 and a debt-to-equity ratio of 1.18. The company’s 50-day moving average is $397.23 and its two-hundred day moving average is $380.98.
MongoDB (NASDAQ:MDB – Get Free Report) last released its earnings results on Tuesday, December 5th. The company reported $0.96 earnings per share (EPS) for the quarter, topping analysts’ consensus estimates of $0.51 by $0.45. The company had revenue of $432.94 million for the quarter, compared to analyst estimates of $406.33 million. MongoDB had a negative net margin of 11.70% and a negative return on equity of 20.64%. The firm’s quarterly revenue was up 29.8% on a year-over-year basis. During the same period in the prior year, the business earned ($1.23) EPS. As a group, equities analysts anticipate that MongoDB, Inc. will post -1.64 earnings per share for the current fiscal year.
Analysts Set New Price Targets
A number of research analysts recently issued reports on the stock. Piper Sandler boosted their target price on shares of MongoDB from $425.00 to $500.00 and gave the company an “overweight” rating in a research report on Wednesday, December 6th. Capital One Financial upgraded shares of MongoDB from an “equal weight” rating to an “overweight” rating and set a $427.00 target price for the company in a research report on Wednesday, November 8th. Truist Financial restated a “buy” rating and set a $430.00 target price on shares of MongoDB in a research report on Monday, November 13th. Tigress Financial upped their price objective on shares of MongoDB from $490.00 to $495.00 and gave the stock a “buy” rating in a research report on Friday, October 6th. Finally, UBS Group reiterated a “neutral” rating and issued a $410.00 price objective (down previously from $475.00) on shares of MongoDB in a research report on Thursday, January 4th. One analyst has rated the stock with a sell rating, three have issued a hold rating and twenty-one have issued a buy rating to the company’s stock. According to MarketBeat, the company presently has an average rating of “Moderate Buy” and a consensus target price of $430.41.
Check Out Our Latest Report on MongoDB
About MongoDB
MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
Further Reading
This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest and most accurate reporting. This story was reviewed by MarketBeat’s editorial team prior to publication. Please send any questions or comments about this story to contact@marketbeat.com.
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Article originally posted on mongodb google news. Visit mongodb google news
DoorDash Develops New Sessionization Platform with Flink to Improve Notification Delivery Timeliness
MMS • Patrick Zhang
Article originally posted on InfoQ. Visit InfoQ
Chen Yang and Fan Zhang at DoorDash’s Engineering team have recently developed an in-memory sessionization platform with Apache Flink that identifies user activities and user sessions in real time. The new system shown by the diagram below solved one of the many challenges DoorDash previously faced – identifying when a user had genuinely abandoned their cart versus merely browsing for more items or different merchants. This distinction was crucial for sending timely and relevant cart abandonment notifications. Traditional methods, such as batch processing, were not only resource-intensive but also lagged, making real-time detection nearly impossible.
Real-time session detection data flow, designed by DoorDash’s Engineering team.
The new sessionization platform is built with a large, stateful Flink job to monitor user sessions through mobile and web client events in memory. This approach allowed them to process user activity event stream without “having to load massive amounts of data from cold storage to memory prior to processing”, therefore “avoiding huge computational costs and latency” as well as “detecting periods of inactivity in short time frames, [in order to] send notifications at more opportune moments.” The new platform isn’t without its challenges. Since Flink processes all events in memory in real time, it needs to keep all user session events until the session ends. Given DoorDash’s current scale and each customer session is about an hour long, the local inflight state can be hundreds of gigabytes at any moment.
DoorDash’s adoption of Apache Flink for real-time session detection and notification delivery marks a significant advancement in enhancing user engagement and conversion rates. The new design has helped DoorDash greatly improve notification delivery timeliness and accuracy, resulting in a 40% higher send-to-open rate. The success has already led to a new series of experiments with the platform, including adding promotions to cart abandonment notifications and controlling the frequency of cart abandonment notifications.
OpenTofu 1.6.0 Now Generally Available: New Module Testing, Enhanced S3 Backend, and Many More
MMS • Almir Vuk
Article originally posted on InfoQ. Visit InfoQ
OpenTofu 1.6.0 is now generally available. A community-driven open-source fork of Terraform under the Linux Foundation, now offers a stable release with many features, including advanced testing features for configurations and modules, enhanced S3 state backend with new authentication methods, a new provider and module registry, and many more improvements and bug fixes.
The 1.6.0 release of OpenTofu introduces a range of new features aimed at enhancing stability and functionality. Notable among these is the testing feature, enabling users to assess OpenTofu configurations and allowing module authors to conduct module tests, therefore strengthening overall stability. Integration with the core of OpenTofu is complete, ensuring a seamless user experience.
Additionally, the S3 state backend has experienced a substantial update, featuring numerous new authentication methods while maintaining compatibility with S3-compatible object storage. The release also unveils a new provider and module registry adopting a Homebrew-like architecture, exclusively based on a git repository.
Hosted on CloudFlare R2, this registry is characterized by its responsiveness and high availability, with the process of publishing a new provider or module streamlined to a mere pull request.
Beyond these highlights, the release incorporates a multitude of minor improvements, bug fixes, and performance enhancements, detailed comprehensively in the changelog.
The release and work on OpenTofu are powered by the active community effort. Sebastian Stadl, Core OpenTofu Contributor stated the following:
This OpenTofu GA release is the culmination of 4 months of worldwide community efforts across 5 continents, from hundreds of contributors and over five dozen developers
Looking forward, the OpenTofu project acknowledges the importance of compatibility with Terraform, as reported the project commits to maintaining a reasonable level of compatibility, avoiding disruptive changes to DSL or provider protocols.
The original blog announcement of the GA version states that the 1.7 release has a roadmap which includes the introduction of client-side state encryption, as reported as a long-awaited feature by users for securing state and plan files end-to-end. Also, it is stated that this is valuable to projects working in a regulated environment, and ones going for maximum security.
Initially, support will be extended for user-provided keys and select key management services. Future developments may include a plugin system for introducing additional key management services, depending on community feedback and usage patterns.
Furthermore, in responding to general community requests, OpenTofu is exploring the implementation of parameterizable backends, providers, and modules. As stated this involves the possibility of parameterizing module versions using variables and instantiating providers through for_each parameters on a static list of values. The project aims to address these needs in due course.
In addressing the demand for new state backends, the project aims for the introduction of a plugin system similar to providers. This approach, focusing on third-party extensibility, aligns with the project’s commitment to enhancing the overall ecosystem and offering users a variety of choices.
While these substantial improvements are on the horizon, OpenTofu remains attentive to the diverse needs of its user base. The project actively encourages community participation, welcoming suggestions, and contributions. Users are encouraged to submit issues for any features or enhancements in OpenTofu, ensuring a collaborative and user-centric evolution of the platform.
Lastly, the guide for migrating to OpenTofu from Terraform is available for interested readers for exploration and guidance.
MMS • Renato Losio
Article originally posted on InfoQ. Visit InfoQ
AWS recently announced that Amazon CloudWatch alarms now support AWS Lambda functions as an action for state changes. This new feature enables developers to automate remediation actions when detecting an unhealthy resource.
Designed to be the easiest way to automate custom actions on alarm state changes, the new option allows developers to invoke a Lambda function directly when a CloudWatch alarm changes to an OK, ALARM, or INSUFFICIENT_DATA state.
The PutMetricAlarm now supports invoking the latest version of a Lambda function (arn:aws:lambda:region:account-id:function:function-name), a specific version of the function (arn:aws:lambda:region:account-id:function:function-name:version-number) or using an alias (arn:aws:lambda:region:account-id:function:function-name:alias-name). According to the documentation, when a Lambda function is configured as an alarm action, CloudWatch delivers a JSON payload to the Lambda function when it invokes it, including alarmData, previousState, and configuration information.
Invoking a Lambda function is not the sole option available in CloudWatch Alarms: notifying one or more people or services by sending a message to an SNS topic remains the most popular choice. Additionally, alarms can perform actions to scale an Auto Scaling group and alarms based on EC2 metrics can execute EC2 actions, such as stopping, terminating, rebooting, or recovering an instance. Finally, when alarms go into an ALARM state, they can create operational work items in Systems Manager Ops Center or incidents in the Systems Manager Incident Manager.
The cloud provider emphasizes the ability to combine this new option with existing ones:
You can use the fact that multiple actions are allowed for an alarm to send an email when a threshold is breached, and then another when the breaching condition ends. This helps you verify that your scaling or recovery actions are triggered when expected and are working as desired.
The community’s response has been overwhelmingly positive, with Luc van Donkesgoed, Principal Engineer at PostNL, writing:
Another loooooong (like 9 years long) awaited feature is here: CloudWatch Alarms can now directly call Lambda Functions!
Antonio Lagrotteria, principal cloud engineer and architect at Nordea, describes it as one of the “top 3 post-reinvent announcements that people have been waiting for almost a decade and should shadow most of reinvent announcements.” On a Reddit thread, user yourparadigm suggests instead that the change is not significant and emphasizes that it was already possible to trigger a Lambda function indirectly:
Is putting an SNS Topic in front that big of a deal?
In a separate announcement, the cloud provider revealed that CloudWatch Network Monitor is now generally available. This new feature facilitates monitoring network availability and performance between AWS and on-premises environments and it supports hybrid monitors for networking built with AWS Direct Connect and AWS Site-to-Site VPN.
CloudWatch Alarms support for Lambda actions is available in all regions and standard Cloudwatch pricing applies.
MMS • Sergio De Simone
Article originally posted on InfoQ. Visit InfoQ
OpenAI has started rolling out its new GPT Store, announced a few months ago along with GPTs, to provide a mechanism for ChatGPT Plus, Team and Enterprise users to share custom ChatGPT-based chatbots they create.
According to OpenAI, since GPTs were announced, users have created over three million custom versions of ChatGPT in a diverse range of categories, including DALL·E, writing, research, programming, education, and lifestyle. In addition to category search, the GPT Store makes it possible to browse popular and trending GPTs on the community leaderboard.
Examples of GPTs OpenAI is currently highlighting include personalized trail recommendations from AllTrails, synthesized search results from 200 million academic papers from Consensus, learning math and science with the CK-12 Flexi AI tutor, and more.
The GPT Store does not support monetization yet, but OpenAI says they will launch a revenue program in the next few months:
As a first step, US builders will be paid based on user engagement with their GPTs. We’ll provide details on the criteria for payments as we get closer.
Initial reactions to the announcement include some skepticism rooted on the quality of the GPTs that are currently available, but it is not clear yet whether the GPT Store will end up looking like Apple’s App Store or the Google Play Store, with their review process and editorial vetting, or will follow a distinctive model.
On a related note, it is worth noting that researchers from safety firm Adversa AI showed that GPTs may be tricked into leaking how they were built, including prompts, API names, and uploaded document metadata and content. OpenAI has promptly patched all the vulnerabilities uncovered by Adversa AI researchers, but users should be aware that security is a concern in the ChatGPT world, too.
GPTs provide a mechanism to combine ChatGPT with custom instructions, external knowledge, and any combination of skills. They provide a way to customize ChatGPT for specific uses, as exemplified above. One major advantage of GPTs, says OpenAI, is they do not require coding skills. Rather, you engage with ChatGPT itself to describe what you want to create, then define instructions, conversation starters, and external knowledge bases. If required, you can also integrate capabilities, i.e., external tools, and actions, i.e., calls to external services.
In an unrelated announcement, OpenAI has launched a new plan for smaller teams which includes a shared workspace supporting DALL·E 3, GPT-4 with Vision, Browsing, Advanced Data Analysis, and user management through separate admin tools. Similarly to the ChatGPT Enterprise plan, the ChatGPT Team plan includes a guarantee that OpenAI will not use customers’ data and conversations to train their model, nor to learn from customer interaction with ChatGPT.
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MongoDB is a source-available document-oriented database program. MongoDB is a a NoSQL database solution that uses JSON-like documents with optional schemas. Many organizations are opting to run MongoDB in the Amazon Web Services (AWS) cloud to gain improved scalability and reliability for their MongoDB deployment.
AWS offers a range of services that can be integrated with MongoDB, including computing power and multiple storage options. Running MongoDB on AWS can be done in a few different ways:
- You can manually install and manage MongoDB on an AWS instance.
- You can use MongoDB Atlas, a fully-managed database-as-a-service from the makers of MongoDB, that automatically takes care of your database operations.
In this article, we will cover the benefits of running MongoDB on AWS and show how to get started with MongoDB Atlas on AWS.
Benefits of Running MongoDB on AWS
Infrastructure Flexibility
With MongoDB on AWS, you can choose the instance that best fits your workload. For example, if you need more computing power, you can select a compute-optimized instance. If your workload requires more memory, you can opt for a memory-optimized instance. This flexibility extends to storage as well, with AWS offering both SSD and HDD storage options for your MongoDB database.
Scalability
Whether you’re dealing with a small application or a large enterprise-level operation, AWS allows you to quickly scale up or down to handle changes in requirements or spikes in popularity. AWS’s auto-scaling feature, combined with MongoDB’s sharding capabilities, provides you with a database solution that can grow with your business.
Integrated Security
Running MongoDB on AWS also offers robust security measures. AWS provides various security features, such as AWS Identity and Access Management (IAM), which allows you to set user permissions and policies. This means that you can have granular control over who can access your MongoDB databases and what actions they can perform.
Backup and Disaster Recovery
Finally, the combination of MongoDB and AWS provides robust options for backup and disaster recovery. AWS offers Amazon S3 for object storage, which is known for its durability and is well-suited to NoSQL workloads. You can also use AWS Snapshots to create backups of your MongoDB databases. In the event of a disaster, you can quickly launch more resources in AWS to ensure business continuity.
What is MongoDB Atlas?
MongoDB Atlas is a cloud-based, fully managed database service offered by MongoDB Inc. It provides an integrated suite of advanced features such as automated backups, monitoring, scaling, and security to run MongoDB in the cloud.
MongoDB Atlas handles the operational aspects of running MongoDB, eliminating the need for manual interventions. Some primary characteristics of MongoDB Atlas include:
- Managed Service: MongoDB Atlas offloads the tasks of installation, configuration, maintenance, and scaling from the user, making it a go-to option for those who want to focus more on database operations and less on administration.
- Platform-Agnostic: While MongoDB Atlas operates seamlessly on AWS, it is also available on other cloud platforms, including Google Cloud Platform (GCP) and Microsoft Azure. Users can choose their preferred cloud provider and region.
- Security: MongoDB Atlas comes with built-in security measures, including end-to-end encryption, VPC peering, and enterprise-grade authentication mechanisms.
- Automated Backups: Atlas provides continuous backups with point-in-time recovery. This means you can restore your data to any second in the past without significant downtime.
- Performance Insights: MongoDB Atlas offers real-time monitoring and alerts. Users can gain insights into queries, resource utilization, and other metrics directly from the Atlas dashboard.
Migrating MongoDB to Atlas on AWS
Here are the high-level steps involved in migrating a self-hosted MongoDB database to MongoDB Atlas on AWS Cloud. For more details, see Amazon’s prescriptive guidance.
Step One: Discovery and Assessment
The first phase involves understanding your current MongoDB setup and preparing for the migration. Begin by evaluating your existing MongoDB environment, including the database size, configuration, and performance metrics. This assessment will help you determine the right size and configuration for your MongoDB Atlas cluster on AWS. It’s also crucial to analyze your application’s dependencies on the database to understand how the migration will impact your application.
During this phase, you should also identify any potential challenges or limitations that might arise during migration. These could include compatibility issues, data integrity concerns, or performance implications. By addressing these issues upfront, you can mitigate risks and plan for a smoother migration.
Step Two: Configure Security and Compliance
Security and compliance are paramount in any migration process. Start by configuring the network settings in MongoDB Atlas to ensure secure connectivity. This typically involves setting up VPC peering or AWS Direct Connect between your AWS environment and MongoDB Atlas.
Next, focus on configuring the security features in MongoDB Atlas. These include setting up encryption at rest and in transit, identity and access management, and auditing and monitoring features. Ensure that these settings align with your organization’s security policies and compliance requirements.
It’s also vital to understand the shared responsibility model in AWS and MongoDB Atlas. While MongoDB Atlas manages the security of the cloud, you are responsible for security in the cloud, which includes securing your data and controlling access.
Step Three: Migrate Data
With the preparations complete, you can start migrating your data to MongoDB Atlas. MongoDB Atlas offers a live migration service, which allows you to migrate your data with minimal downtime. To use this service, you will need to provide details about your source MongoDB environment and initiate the migration through the MongoDB Atlas interface.
Monitor the migration process closely to ensure that the data is transferred accurately and efficiently. It’s advisable to perform validation checks during and after the migration to ensure data integrity. Also, be prepared to address any issues that arise during this phase promptly.
Step Four: Configure Operational Integration
Once your data is migrated, the next step is to integrate MongoDB Atlas into your operational processes. This involves updating your application configuration to point to the new MongoDB Atlas cluster. You will need to update your application’s database connection strings and test the application thoroughly to ensure it is interacting correctly with MongoDB Atlas.
Additionally, configure monitoring and alerting in MongoDB Atlas to keep track of your database’s performance and health. MongoDB Atlas provides various tools and metrics that can help you monitor your database effectively.
Finally, consider implementing any necessary changes to your backup and recovery procedures. MongoDB Atlas offers automated backup solutions, but you should align these with your data protection policies and test your backup and recovery process to ensure it meets your requirements.
Conclusion
In conclusion, running MongoDB on AWS offers a combination of flexibility, scalability, security and robust backup and disaster recovery options. By leveraging AWS’s diverse infrastructure, you can tailor your MongoDB environment to meet specific workload demands, be it compute, memory, or storage-centric requirements.
The migration process to MongoDB Atlas on AWS involves discovery and assessment, configuring security and compliance, data migration and operational integration. By following this process, organizations can effectively migrate and optimize their MongoDB deployments in the AWS Cloud, reaping the benefits of a fully managed, scalable and secure database environment.
Article originally posted on mongodb google news. Visit mongodb google news
The 10 Most Upvoted SaaStr Workshops!! Tunguz, MongoDB, Nick Mehta, Bessemer and More!!
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So what were the best attended and most upvoted SaaStr Workshop Wednesdays? The ones you actually just have to catch up?
The 2023 list below! And sign up for FREE Workshop Wednesdays here.
The Impact of Generative AI on Software : Where Opportunity Will Exist for Software Startups with Redpoint Ventures with Tomasz Tunguz, Former Managing Director @ Redpoint Ventures
How to Grow Revenue Faster with Sam Blond, Partner @ Founders Fund
10 Things That Always Work in SaaS Marketing with SaaStr with Jason Lemkin, Founder & CEO @ SaaStr
Things you think as a first-time founder that just ain’t so with Jack Altman, CEO @ Lattice
Selling. The Seven Things all Founders Should Know About Sales. with Dave Kellog EIR @ Balderton Capital
Lessons from Ramp, Gorgias, and Drift: Secrets to Sustainable Low CAC Growth after Series B and Beyond with Guillaume Cabane, Co-Founder and President @ HyperGrowth Partners
What you need to change at $10M to scale to $100M with Sameer Dholakia, Partner @ Bessemer Venture Partners
My Top 10 Mistakes In 10 Years with Gainsight with Nick Mehta, CEO @ Gainsight
For B2B Generative AI Apps, Is Less More with Kristina Shen, General Partner @ A16z
Rethinking Sales Compensation for a Consumption-Based GTM with Meghan Gill, SVP Sales Operations & Sales Development @ MongoDB
Article originally posted on mongodb google news. Visit mongodb google news
MMS • Brit Myers
Article originally posted on InfoQ. Visit InfoQ
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Transcript
Shane Hastie: Hey folks. It’s Shane Hastie here. Before we start today’s podcast, I wanted to tell you about QCon London 2024, our flagship international software development conference that takes place in the heart of London. Next April 8 to 10, learn about senior practitioners experiences and explore their points of view on emerging trends and best practices across topics like software architecture, generative AI, platform engineering, observability, and secure software supply chains. Discover what your peers have learned, explore the techniques they are using, and learn about the pitfalls to avoid. Learn more at QConLondon.com. We hope to see you there.
Good day, folks. This is Shane Hastie for the InfoQ Engineering Culture Podcast. Today I’m sitting down with Brit Myers. Brit is the VP of engineering with System Initiative. Brit, welcome. Thanks for taking the time to talk to us today.
Brit Myers: Thank you so much for having me, Shane.
Shane Hastie: So the way I like to start these conversations is, who’s Brit? Tell me a little bit about your background.
Introductions [01:13]
Brit Myers: Yeah, thanks. As you mentioned, I’m the VP of engineering at System Initiative. I’m a software engineer by trade, though I would say I’m sort of an accidental engineering executive, because I did not have quite a long plan leading up into becoming and entering the tech space, but I’m one of those managers who loves managing engineers. I love managing software engineering teams. I love delivering great products to market, and I’m incredibly relentless that so much of how we are doing things and have done things can be better, and I’m on the pursuit to figure out what those ways are, to invent what I can along the way, and share what I’ve learned.
Shane Hastie: Cool. So you love management. You love managing people. Many people in the engineering space struggle with having to look after and manage people, so what is it that gave you that frisson?
Brit Myers: Yeah, that’s a good question. I say I love managing people, but I love leading, and part of that is because I love seeing the potential in what an individual can do or what a group of people can do. Helping them realize what that thing is, I get a lot of intrinsic value, and that is incredibly motivating for me, so it’s this selfish thing to be in management for me, because sort of the wins that you experience and the growth that you can see somebody achieve, it feels great, and so I love doing it.
Shane Hastie: What is a great engineering culture?
Brit Myers: Your engineering culture is great if your engineers believe that it is
I think there’s not a single answer. I think I can tell you that a great engineering culture is one that everybody and enough people are willing to say it’s great, and so it’s sort of like the eye of the beholder a bit with this, in my opinion, and you can imagine I’ve made many mistakes like this along my career. I might think that a change that I make or a decision that I make is going to improve the engineering culture, when in fact it has the opposite effect, right and so my desire for an amazing engineering culture is separate from the tactics that I take to try to influence what that engineering culture is, but whether or not it actually is great, you have to ask the people, “Do you love your engineering culture? Would you recommend another engineer joining your team or working in this organization?”
I think, if you just ask the people on your teams whether or not they think that your engineering culture is amazing, you’ll learn, and if they say no, and I am sort of at the leadership level, asking them, they are right. I’m wrong. It doesn’t matter what I think it is. If they don’t tell me what I think, and they’re sort of, “Ah,” if what they think is great, but I think it’s horrible, and I make a change that gives them sort of a different reaction, then I’m not doing my job. So it’s just a long way to say, your engineering culture is great if your engineers believe that it is.
Shane Hastie: So what are some of the tactics that you’ve tried in order to improve cultures over your experience?
Tactics and experiments [04:04]
Brit Myers: Oh my gosh. So many. So, so, so many. One of the stories I can share that sort of stands out for me, a number of years ago I stumbled across a blog that was titled, “These are the signs that You’re working in a feature factory,” and at that time, if I had asked by engineers, “What do you think about our engineering culture?” not all of them felt great about it, and a lot of that was partially due to the sort of back and forth between engineering and product, which is natural, and it’s expected to be sort of a compromise and a conversation, and that you’re making these decisions together.
One thing that I experienced here was that if there’s too much imbalance in the conversation, what you end up with is engineers who believe that they’re just taking tickets and just taking tasks, and that you’re ultimately not treating them as knowledge workers. So one of the things that I did to try to influence that, and create an environment that was more conducive to what the engineers wanted and what they needed, while still delivering what the business expected, in that case, it was process changes around how we talk about the work. Instead of saying, “Put the button on the bottom left,” it’s “This is the problem that we need to solve. This is the problem the customer has.” One solution might be that the button goes in the bottom left.
The button could also go in the bottom. By sort of changing the conversation that happened, now that back and forth about where the button should be was a more tactical conversation, and you got sort of the strategic, “This is the problem we want to solve, and this is the priority that it is.” That was fed in much more clearly by separating sort of the problem that you want to solve in the solution. The result was the team members did no longer felt, or I should say felt less like they were working in a feature factory, because now the conversation of what to build was a conversation that didn’t exist before.
Shane Hastie: So bringing some, I want to say, almost autonomy into the conversation.
Brit Myers: Precisely, and to be honest with you, throughout a lot of my career, I think you can sort of generalize what I’ve done, which is bringing some autonomy to the engineers. What’s been interesting is that, at every sort of step that you take towards sort of a more autonomous team, what you have to have in order for that to thrive is alignment alongside, and this is something that, at System Initiative, I’m incredibly proud of, and sort of love how these conversations happen across engineering and product, where to some degree, the old Spotify videos of you cannot have, what is it? High alignment or high autonomy without alignment. Then, everybody’s kind of going in different ways, right?
It’s true. It is actually true that you can have more autonomy if you have more alignment. The question is, are you willing to put in the work to gain that alignment, and do you have the mechanisms? Do you have the psychological safety to get alignment? And sometimes getting alignment is really messy, and it feels like conflict, when in fact it is conflict, but it’s productive and it’s conducive conflict, and that is the work. If you’re willing to put in the work and to focus on getting alignment across, whether it’s across teams or across business domains, across departments at your organization, the outcome of autonomy can have an amazingly positive impact on your engineering culture, but you have to be able to handle both.
Shane Hastie: So if people don’t want to work in a feature factory, and the factory metaphor does get in the way, what are some better ways of thinking about the engineering environment, and how do we move towards those?
Moving away from feature factories towards winning collaborative games [07:28]
Brit Myers: An analogy that I’ve started to use more explicitly lately is, instead of engineers working at a factory, your engineers are athletes on a team, and you’re playing a game. The goal is to win the game, and winning the game in that moment might mean getting usage of a new feature at this level in this way. It might be hitting some launch milestone. I mean, what winning is a bit fluid here, but if you think about what is required for a group of people to come together, where they all have different skills, there is no single game that’s played the same, and that, I think, is where the factory analogy really breaks down. How many times are you writing the exact same lines of code in the exact same order for the work that you’re doing? It’s, hopefully, never or maybe a max of three, right? So if you do it once, do it twice, on the third time, maybe you don’t ever want to do it again, in which case you’re not doing the same thing over and over again.
Where, by using sort of that analogy of these are team members that they’re playing together to win a game, they have a shared outcome, they have shared stake in what the outcome is, they have different skills, they have different strengths, they maybe are feeling different ways on certain weeks, or they have different priorities. That mechanism makes it so much easier to sort of describe, how then can I influence the environment so that the team has the greatest chance of winning? As a manager, as a leader, what can I control so that they win the game? Because I’m not out there playing with them. If I was a collegiate athlete, and basketball is my chosen sport, there are some coaches who will yell out calls from the sidelines, and sometimes if a player doesn’t run that call at that moment they’re getting yanked. They’re like, “You didn’t do what I said, and so you’re not playing.”
Other coaches have a different style, where they teach the plays, they give all the tools to the team that they have, and they rely on the point guard or the guards to call the plays and call the shots live, right? So you get into all of the intricacies of how a different coach with a team, a different team member with everybody else, and how those dynamics impact each other, it fits quite well while also holding true the perspective that, as a leader, you’re not on the court. You’re not on the field. You’re on the sidelines, and your goal is to do whatever you can so that they win the game. Knowing how deep you can go is incredibly important. It’s humbling in terms of how much power or how much authority somebody actually has, when all I can do is yell out the play, and hope that if they do run it, it works.
Shane Hastie: How do we help those players get better?
Leadership is about helping teams get better [09:57]
Brit Myers: If I stick with the basketball analogy, you have your LeBron, James. You have your top 10 world athletes, but by and large, everybody in the league has some base level amount of skill. Some are higher in some areas, and some are lower in some areas, but it is incredibly dependent what team they’re playing on, where they actually need to grow. And so the answer that sort of came to mind was like, “Well, it depends,” and it does, because the question is both, how does that player want to grow? How does that engineer want to grow? Where do they see themselves going? Are they somebody who sees themselves coaching someday, or are they going to be a lifer, and they just want to be the best that they can be at the job that they have? That would change, then, how you can help them grow. How do you need them to grow?
So there’s conflict or there’s tension sometimes, where an organization needs people to grow in this way, but they want to grow in this other way, and what do you do in that situation? Sometimes the right thing to do is to say, “Well, you should find a place where you can grow and where you can be supported, because you’re not going to grow in that way here.” The most basic examples of, if there’s a specific technology stack that you want to use, and that technology stack is not the one that your organization uses, you’ve got to find other ways to get exposure and to grow in that area, right? It really just depends, but it’s a combination of, what is that person’s potential, where do they want to go, where do you need them to go, and what does the team need from them? Then, over the course of understanding all of those axes, then ideally, together, you can navigate the conversation, so whether you’re setting goals or tuning the feedback that you’re giving, assuming that you’re giving constant feedback, then the question is how do you know what to tune the feedback to?
Shane Hastie: What about when the organization wants to change direction? You mentioned leading organizations through transformations. How do we make those smoother?
Tackling organisation transformation [11:52]
Brit Myers: I think the only way to make them smoother is to do them more often. If you lean more into the factory example, once you have a factory, assuming the product that you’re building is the same, you probably don’t really make many changes to that factory, right? But the reality is the product that we’re building are changing by the minute, by the second, by the hour. The question I think is less about how do you make it smoother to transition.
I think it’s more about how do you encourage, whether you call it continuous improvement, or I don’t know if there’s another word, but you can call it continuous improvement. How do you account for continuous improvement, and how do you build enough sort of flexibility in your organization so that it can evolve the way it naturally will, as a result of the technology and the work that you’re doing evolving? To some degree, the fact that transformation is hard is more a result of how rigid we’ve made certain aspects of organizations. It’s not because change is hard. It’s because we made it hard on purpose, so there’s just a lot of undoing that you end up having to do as you sort of go on that journey.
Shane Hastie: As a leader, how do I build that ability to change easily into the organization and into the culture?
Brit Myers: I think I have a fundamental belief that the organization will change organically if you let it, and so if your culture, if the environment is not supportive of making changes, that’s where it sort of becomes hard. So I guess the answer is, if you can lean more into autonomy, if you can seek that alignment about what types of change are okay, and how do you sort of process them if they need to be processed, then by giving the teams the autonomy to do the work, what you will end up with is this organic changing system.
Shane Hastie: You’ve used the term “psychological safety” a couple of times. It’s become almost a hackneyed phrase. How do we make it real?
Making psychological safety real [13:53]
Brit Myers: I don’t know. I don’t know that I’m qualified to answer that question, but I can say what I have done to do the most that I can to create some psychological safety, and that is how an organization, how a leader reacts to questions, pushback, or even how a leader navigates conflict, hard conversations, or disagreements. All of those things are opportunities for leader to send signals about, is this the type of conversation that is safe? Is this topic off limits or is it on limits? And so, I focus a lot on managing my own reactions and being intentional about how I communicate so that I’m constantly sending these signals that, “Yeah, I want the questions. I want you to disagree. I want to hear when you disagree. I want to be able to tell you that, even if you disagree, this is what we’re doing and we’re going to commit to it.”
And knowing that you’re able to do that, all of those things sort of add up to, I think, what can result in a more psychological safe environment than otherwise. You have to model it in your reactions. You have to model it in conversations. You have to model it even in, for example, skip level conversations, or when the proverbial boss is in the room, are there things that you don’t talk about? Because that’s a signal about how safe certain types of conversation and certain types of topic are. And so, I think just by being very intentional, and knowing that all of those are signals that influence whether or not somebody’s willing or feels safe to confide, safe to disagree, safe to question, all of those things, they all add up. You have to be on, very on, all of the time. When you’re not, you own it and say, “Hey, I reacted poorly. That is not what I intended. My reaction was because of this. I love that you asked the question. Please ask that again.”
Shane Hastie: So what advice would you have for the new manager leader, somebody who has stepped into a leadership role in that technical space? So I’m an engineer. I’ve moved into a technical leadership space. How do I do this?
Advice for new technical leaders [15:57]
Brit Myers: So one piece of advice I would have is to give yourself some grace, because this now explicit authority that you have, regardless of how big it is or what sort of context you have around it, the new authority you have, you’re going to make mistakes, and it’s okay. I feel like I did not hear that enough early. I mean, you hear you’re not expected to have all the answers and sort of those types of things, but it’s different than saying, “You’re going to make mistakes. You’re going to learn from them. It’s okay.” That would be sort of my first advice, is to expect to make mistakes. My second piece of advice is to sort of remember what your role is. One of the things that was pretty easy for me, that I’ve seen others sort of fall down on is, as an engineer, you are making decisions every single day.
You’re defending decisions every single day, to some degree or another, accountable to those decisions every single day, even if it’s just to your team, because you’re the person who wrote the code. If somebody’s going to ask you a question, you’re accountable to answering them if you’re there. The shift in I, as an engineer, I am individually contributing to what we are trying to do. As a manager, as a leader, it’s not about what you personally are doing. It’s about what your whole team is doing, so you have to think so much less about the impact of just your behavior and starting to say, “Okay. How can I impact the outcomes of all of these people, whereas before you were very focused on the outcomes that I was producing myself.”
That can be a shift, but one of the reasons they can end up incredibly happy, or maybe their team isn’t happy is if they’re trying to hold onto the idea that you are both individually contributing to something, and contributing through the team or through the people that you’re leading. I think the more you lean into and give up that you’re individually not contributing, I’m not producing artifacts myself, then the faster you will grow as a leader, because it kind of pushes you more into the leadership space and where you end up spending more time focusing on how you can help others and how you can support others at the cost of how you individually are adding to something.
Shane Hastie: Some really interesting points and good advice in there. If people wanted to continue the conversation, how do they get hold of you?
Brit Myers: You can find me on LinkedIn. Go ahead and search for my name. If you’re interested in exploring more how engineering culture is influenced by DevOps culture and how DevOps culture comes to be, we have a Discord at System Initiative. We’d love for you to join and bring all of your questions and ideas there as well.
Shane Hastie: Wonderful. Thank you so much for taking the time to talk to us today.
Brit Myers: Thanks for having me, Shane.
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Commonwealth Equity Services LLC decreased its position in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) by 40.3% during the 3rd quarter, according to the company in its most recent disclosure with the SEC. The fund owned 11,611 shares of the company’s stock after selling 7,832 shares during the quarter. Commonwealth Equity Services LLC’s holdings in MongoDB were worth $4,016,000 as of its most recent filing with the SEC.
Other hedge funds also recently made changes to their positions in the company. Atika Capital Management LLC lifted its position in MongoDB by 5.3% in the second quarter. Atika Capital Management LLC now owns 31,500 shares of the company’s stock valued at $12,946,000 after purchasing an additional 1,575 shares during the period. Raymond James & Associates boosted its position in MongoDB by 227.2% during the 2nd quarter. Raymond James & Associates now owns 39,361 shares of the company’s stock worth $16,177,000 after purchasing an additional 27,331 shares during the period. Mirae Asset Global Investments Co. Ltd. acquired a new position in MongoDB in the 2nd quarter worth $6,704,000. American Trust acquired a new position in MongoDB in the 2nd quarter worth $349,000. Finally, Empower Advisory Group LLC acquired a new position in MongoDB in the 1st quarter worth $7,302,000. Hedge funds and other institutional investors own 88.89% of the company’s stock.
Insider Activity
In other MongoDB news, CEO Dev Ittycheria sold 100,500 shares of the company’s stock in a transaction that occurred on Tuesday, November 7th. The stock was sold at an average price of $375.00, for a total value of $37,687,500.00. Following the completion of the sale, the chief executive officer now owns 214,177 shares of the company’s stock, valued at $80,316,375. The sale was disclosed in a legal filing with the SEC, which can be accessed through this link. In related news, CEO Dev Ittycheria sold 100,500 shares of the firm’s stock in a transaction on Tuesday, November 7th. The stock was sold at an average price of $375.00, for a total value of $37,687,500.00. Following the completion of the sale, the chief executive officer now owns 214,177 shares of the company’s stock, valued at $80,316,375. The sale was disclosed in a legal filing with the Securities & Exchange Commission, which is accessible through this hyperlink. Also, CAO Thomas Bull sold 359 shares of the firm’s stock in a transaction on Tuesday, January 2nd. The shares were sold at an average price of $404.38, for a total value of $145,172.42. Following the transaction, the chief accounting officer now owns 16,313 shares of the company’s stock, valued at $6,596,650.94. The disclosure for this sale can be found here. Insiders have sold a total of 147,029 shares of company stock worth $56,304,511 over the last ninety days. Company insiders own 4.80% of the company’s stock.
Analyst Ratings Changes
A number of equities research analysts have recently issued reports on MDB shares. Bank of America started coverage on shares of MongoDB in a research note on Thursday, October 12th. They issued a “buy” rating and a $450.00 target price on the stock. Piper Sandler upped their target price on shares of MongoDB from $425.00 to $500.00 and gave the company an “overweight” rating in a research note on Wednesday, December 6th. Tigress Financial upped their target price on shares of MongoDB from $490.00 to $495.00 and gave the company a “buy” rating in a research note on Friday, October 6th. TheStreet raised shares of MongoDB from a “d+” rating to a “c-” rating in a research report on Friday, December 1st. Finally, Truist Financial reaffirmed a “buy” rating and set a $430.00 price objective on shares of MongoDB in a research report on Monday, November 13th. One research analyst has rated the stock with a sell rating, three have assigned a hold rating and twenty-one have assigned a buy rating to the company. According to data from MarketBeat, MongoDB has an average rating of “Moderate Buy” and a consensus price target of $430.41.
View Our Latest Stock Analysis on MongoDB
MongoDB Stock Down 0.1 %
NASDAQ:MDB opened at $392.60 on Friday. The firm’s 50 day simple moving average is $396.26 and its 200 day simple moving average is $380.90. The company has a market cap of $28.34 billion, a PE ratio of -148.71 and a beta of 1.23. The company has a debt-to-equity ratio of 1.18, a current ratio of 4.74 and a quick ratio of 4.74. MongoDB, Inc. has a one year low of $179.52 and a one year high of $442.84.
MongoDB (NASDAQ:MDB – Get Free Report) last announced its quarterly earnings results on Tuesday, December 5th. The company reported $0.96 EPS for the quarter, beating analysts’ consensus estimates of $0.51 by $0.45. The business had revenue of $432.94 million during the quarter, compared to analyst estimates of $406.33 million. MongoDB had a negative net margin of 11.70% and a negative return on equity of 20.64%. MongoDB’s quarterly revenue was up 29.8% on a year-over-year basis. During the same quarter in the previous year, the business posted ($1.23) EPS. On average, research analysts anticipate that MongoDB, Inc. will post -1.64 earnings per share for the current year.
MongoDB Profile
MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
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