New to MongoDB Atlas: Pause/Resume Clusters, M200 Instance Size on AWS

Leo Zheng
December 22, 2017 | Updated: January 10, 2018

MongoDB Atlas, the managed MongoDB service, now allows you to pause and restart your database clusters. This makes it easy and affordable for you to integrate MongoDB into DevOps workflows where always-on access to the underlying data is not required — e.g. development or testing.

When combined with Atlas’s fully managed backup service, this new functionality allows you to seamlessly create multiple environments for development and testing while keeping infrastructure and operational costs to a minimum.

For example, you could restore a subset of your production data (using queryable snapshots) to a smaller database to try out new features introduced in MongoDB 3.6. You can even restore to different Atlas Projects, regions, or clouds to give different members of your organization local access. And now with the pause cluster feature, your development and testing teams can easily stop any databases when they’re not being used.

Pausing and resuming a cluster requires just a few clicks in the Atlas UI or a single call with the Atlas API. When the cluster is paused, you are charged for provisioned storage and any associated backups, but not for compute instance hours associated with your Atlas cluster. Clusters can be paused for up to 7 days. If you do not resume a paused cluster within the 7 day window, Atlas will automatically resume the cluster.

The pause/resume feature is now available for all dedicated instance sizes (M10 and above) in every supported region on AWS, Microsoft Azure, and Google Cloud Platform.

Larger Max Instance Size on AWS (M200)

MongoDB Atlas now supports a larger instance size on Amazon Web Services. The new M200 clusters are designed for the most demanding production workloads and peak hours of activity. Each instance features 64 vCPUs, 256 GB of RAM, and 1500 GB of storage included, with 25 Gigabit network connectivity.

M200 instances are available in all 14 AWS regions supported by MongoDB Atlas.

Not an Atlas user yet? Get started with a 512MB database for free.

← Previous

Internal Mobility: Changing Roles, not Companies

What’s the first thing you would do if you started to feel a lack of fulfillment or challenge in your current role? You might begin investigating opportunities at other companies. Perhaps you’d start researching your current organization’s competitors, or the company your colleague left for last quarter, or change your LinkedIn status so recruiters know you’re willing to having a discussion. Why do employers let their best talent get to the point where they enter the rabbit hole of potential opportunity, instead of finding a way to retain them? Internal mobility, or the opportunity to move teams and roles within one organization, is still not as feasible an option as some may like it to be. In fact, according to a recent Gartner study, 61% of employees think it would be beneficial for their careers to work in different parts of the organization, and future career opportunity is consistently one of the top reasons employees leave. Tenured employees have already proven themselves, so you can assume they’re able to take on bigger projects and encourage greater collaboration between departments. Over the last few years, we as an organization acted on this conjecture, providing opportunities for our employees to develop new skills. Jay Gordon is a MongoDB Developer Advocate and a major asset in providing information and assistance regarding all things MongoDB. He enables our developer community by creating technical content, answering questions, attending events, and providing as much assistance as possible to those using (or learning to use) MongoDB. Jay was hired in 2016 as a Technical Account Manager on the Cloud Team to provide MongoDB customers with onboarding and integration assistance. While tackling his daily responsibilities, Jay became involved in helping the MongoDB user community understand new releases, products, and tools, acting as an advocate and evangelist. A little over a year into his role as a TAM, a Developer Advocate role opened up and Jay was the perfect fit. “It was a difficult transition because I was taking on an entirely new role. There was some self-doubt that I was really capable of the position I had taken on, but in the end, much of that was just worry for the sake of worry. The MongoDB team was by my side to help with the shift, which had a lot to do with why I stayed instead of looking elsewhere for an opportunity, and the culture had a lot to do with my decision. Being part of MongoDB is a special experience and I was not ready to walk away from that quite yet. I love my job, I love the people I work with, and I love the opportunities to be part of something huge.” Angshuman Bagchi joined the MongoDB team in 2013 as a Technical Service Engineer in Palo Alto. For over three years he worked on front line customer support helping customers become successful with MongoDB, but once he was struck with a desire to do something different, Angshuman went back to his development roots as a lead on our Technical Services Tools team, which is responsible for all tools used by our Technical Services Engineers. The role not only allowed him to do something different, it also provided the opportunity to learn managerial and administrative skills. “My management was very supportive of my desire for a change. They gave me the freedom to explore opportunities both outside and within the broader Technical Services organization with the emphasis that I should be allowed to work on something I want. The move has afforded me a tremendous amount of personal and professional growth.” Marie Vito is now the Program Lead and Coordinator for our award-winning Sales Enablement team – responsible for training, process implementation, tools, and coaching to make sales representatives and leaders the most productive they can be in their roles. Marie plans and leads the monthly MongoDB Sales Bootcamp training for all sales new hires, as well as anyone else in the company interested in learning about our sales strategy. When she first joined MongoDB as a Recruiting Coordinator, Marie supported our sales organization by scheduling, coordinating, and facilitating interviews for all sales-related roles. During that time, she was able to form strong relationships with the sales team and quickly became interested in their goals and initiatives. An initial conversation with the Senior Director of Sales Enablement helped to flesh out the role and determine that it was a position Marie wanted to pursue. “Following that meeting I spoke with my then manager to express my aspirations. Once it was determined I was a good fit for the role, we developed a transition plan to ensure I would be leaving the recruiting team with a more than capable replacement, while still dedicating enough time to enablement training to make the ramp process as efficient as possible. It was incredible to have so much support from my new team, old team, and everyone else in the company.” Providing employees the opportunity to try new things, explore new roles, and broaden their skills is a great way to foster both professional and personal growth. At MongoDB, we’ve found that supporting internal mobility is a key factor in retaining our best people and keeping them content. Interested in learning more about what we’re doing at MongoDB? Click here .

December 21, 2017
Next →

Hanabi Technologies Uses MongoDB to Power AI Assistant, Hana

For all the hype surrounding generative AI, cynics tend to view the few real-world implementations as little more than “fancy chatbots.” But for Abhinav Aggarwal, CEO of Hanabi Technologies, the idea of a generative AI-powered bot that is more than just an assistant was intriguing. “I’d been using ChatGPT since it launched,” said Aggarwal. “That got me thinking: How could we make a chatbot that was like a team member?” And with that concept, Hana was born. The problem with bots “Most generative AI chatbots do not act like people; they wait for a command and give a response,” said Aggarwal. “We wanted to create a human-like chatbot that would proactively help people based on what they wanted—automating reminders, for example, or fetching time zones from your calendar to correctly schedule meetings.” Hanabi’s flagship product, Hana, is an AI assistant designed to enhance team collaboration within Google Chat, working in concert with Google Workspace and its suite of products. “Our target customers are smaller companies of between 10 and 50 people. At this size you’re not going to build your own agent from scratch,” he said. Hana integrates with Google APIs to deliver a human-like assistant that chimes in with helpful interventions, such as automatically setting reminders and making sure meetings are booked in the right time zone for each participant. “Hana is designed to bring AI to smaller companies and help them collaborate in a space where they are already working—Google Workspace,” Aggarwal explained. The MongoDB Atlas solution For Hana to act like a member of the team, Hanabi needed to process massive amounts of data to support advanced features like retrieval-augmented generation (RAG) for better information retrieval across Google Docs and many other sources. And with a rapidly growing user base of over 600 organizations and 17,000+ installs, Hanabi also required a secure, scalable, and high-performing data storage solution. MongoDB Atlas provided a flexible document model, built-in vector database, and scalable cloud-based infrastructure, freeing Hanabi engineers to build new features for Hana rather than focusing on rote tasks like data extract, transform, and load processes or manual scaling and provisioning. Now, MongoDB Atlas handles a variety of responsibilities: Scalability and security: MongoDB Atlas’s auto-scaling and automatic backup features have enabled Hanabi to seamlessly grow its user base without the need for manual database management. RAG: MongoDB Atlas plays a critical role in Hana’s RAG functionality. The platform enables Hanabi to split Google Docs into small sections, create embeddings, and store these sections in Atlas’s vector database. Development Processes: According to Aggarwal, MongoDB’s flexibility in managing changing schemas has been essential to the company’s fast-paced development cycle. Data Visualization: Using MongoDB Atlas Charts has enabled Hanabi to create comprehensive dashboards for real-time data visualization. This has helped the team track usage, set reminders, and optimize performance without needing to build a manual dashboard. Impact and results With MongoDB Atlas, Hanabi can successfully scale Hana to meet the demands of its rapidly expanding user base. The integration is also enabling Hana to offer powerful features like automatic interactions with customers, advanced information retrieval from Google Docs, and manually added memory snippets, making it an essential tool for teams around the world. Next steps Hanabi plans to continue integrating more tools into Hana while expanding its reach to personal Gmail users. The company is also rolling out a new automatic-interaction feature, further enhancing Hana’s ability to proactively assist users without direct commands. MongoDB Atlas remains a key component of Hanabi’s stack, alongside Google Kubernetes Engine, NestJS, and LangChain, enabling Hanabi to focus on innovating to improve the customer experience. Tech Stack MongoDB Atlas Google Kubernetes Engine NestJS LangChain Are you building AI apps? Join the MongoDB AI Innovators Program today! Successful participants gain access to free MongoDB Atlas credits, technical enablement, and invaluable connections within the broader AI ecosystem. If your company is interested in being featured, we’d love to hear from you. Connect with us at ai_adopters@mongodb.com.

November 21, 2024