Introducing Serverless Instances on MongoDB Atlas, Now Available in Preview

Since we first launched MongoDB Atlas in June 2016, we’ve been working towards building a cloud database that not only delivers a first-class developer experience, but also simply just works: no setup, tuning, or maintenance required. Over the years, this has led to features like auto-scaling and click-to-create index suggestions, along with numerous optimizations to our automation engine.

We’re excited to announce that we’re one more step closer to realizing this vision with the introduction of serverless databases on MongoDB Atlas.

Think less about your database, and more about your data

Serverless computing and NoOps have emerged as popular trends in modern application development. Cloud functions are commonly used to power business logic in applications, and many teams rely on completely automated IT operations.

The appeal of serverless technology is hard to deny: elastic scaling eliminates the need for upfront resource provisioning and ongoing maintenance, and consumption-based pricing means paying only for resources that are used. It abstracts and automates away many of the lower-level infrastructure decisions that developers don’t want to have to learn or manage so they can focus on building differentiated features.

When it comes to databases, compute and storage resources have traditionally been tightly coupled. Applying a serverless model to databases means decoupling them and changing the way engineering teams think about infrastructure. Rather than asking a developer to predict an application’s future workload patterns, break them down into individual resource requirements, and then map them to arbitrary units of database instance sizes, serverless databases offer a much simpler experience: define where your data lives, and get a database endpoint you can use.

This not only streamlines the database deployment process, it also eliminates the need to monitor and adjust capacity on an ongoing basis. Developers are free to focus on thinking about their data rather than their databases, and leave the lower-level infrastructure decisions to intelligent, behind-the-scenes automation.

Serverless instances on MongoDB Atlas

All customers now have the ability to create a serverless database on MongoDB Atlas with the introduction of serverless instances, announced at MongoDB.live 2021.

It’s incredibly easy to get started: simply choose a cloud region and you’ll receive an on-demand database endpoint for your application. Serverless instances always run on the latest MongoDB version so you never have to worry about backwards compatibility or upgrades. You can view and manage them using the same UI and API as your existing database deployment on Atlas (i.e., clusters), and they come with end-to-end security, continuous uptime, metrics, alerts, and backups.

Watch this demo of how to create a serverless instance on MongoDB Atlas

This new deployment type will be available in preview, so it doesn’t yet support all of the features and capabilities available on clusters today. It’s ideal for infrequent or sparse workloads, or development and testing workloads in the cloud. If you’re running a high-throughput production workload, dedicated clusters are still the recommended deployment option.

A hands-free database experience

This is the first of many releases, and we have an ambitious roadmap ahead. We will continue to invest in making working with data ever more seamless and delightful for developers, from adding support for newer Atlas capabilities like full-text search and native visualizations, to even more intelligent automation and optimization.

Create your own serverless instance on MongoDB Atlas.

If you have feedback or questions, we’d love to hear them! Join our community forums to meet other MongoDB developers and see what they’re building with serverless instances.

What's next for MongoDB Atlas

Serverless instances are just one of many new additions to Atlas that we hope will make developers’ lives easier. Earlier this year, we added index removal suggestions to Performance Advisor and released a quick start for creating and managing clusters via the command line with the MongoDB CLI.

We are also working on integrations with Vercel and Netlify, two popular serverless application platforms, to give developers an easy way to get started on MongoDB Atlas.

What would make your development experience better on MongoDB Atlas? Share your feature requests in our feedback forums.

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Launched Today: MongoDB 5.0, Serverless Atlas, and the Evolution of our Developer Data Platform

Today we welcome you to our annual MongoDB .Live developer conference. Through our keynote and conference sessions we'll show you all the improvements, new features, and exciting things we've been working on since last year’s conference. What I want to do in this blog post is provide you with a summary of what we are announcing, and resources to help you learn more. While it's easy to focus on what we are announcing at this year's event, we actually started out on this journey 12 years ago by releasing the world’s most intuitive and productive database technology to develop with — MongoDB. And we believe the applications of the NEXT 10 YEARS will be built on data architectures that continue to optimize for the developer experience, allowing teams like yours to innovate at speed and scale. So how are we building on this vision? Today I am incredibly proud to announce three big things: The General Availability (GA) of MongoDB 5.0, the latest generation of our core database. It includes native support for time series workloads, new ways to future-proof your applications, multi-cloud privacy controls, along with a host of other improvements and new features. The preview release of serverless instances on MongoDB Atlas, which makes it even easier for development teams who don’t want to think about capacity management at all to get the database resources they need quickly and efficiently. Major enhancements to Atlas Data Lake, Atlas Search, and Realm Sync, which allow engineering teams to reduce architectural complexity and get more value out of their data. MongoDB 5.0 GA MongoDB 5.0 is the latest generation of the database most wanted by developers . Our new release makes it even easier to support a broader range of workloads, introduces new ways of future-proofing your apps, and further enhances privacy and security. This major jump in version number from MongoDB 4.4 – our prior GA version – to 5.0 reflects a new era for MongoDB's release cadence: We want to get new features and improvements into your hands faster. Starting with MongoDB 5.0, we will be publishing new Rapid Releases every quarter, which will roll up into Major Releases once a year for those of you that want to maintain the existing annual upgrade cadence. You can learn more about the new MongoDB release cadence from our blog post published last October. Digging into MongoDB 5.0, here is what’s new and improved: Native Time Series Designed for IoT and financial analytics, our new time series collections, clustered indexing, and window functions make it easier, faster, and lower cost to build and run time series applications, and to enrich your enterprise data with time series measurements. MongoDB automatically optimizes your schema for high storage efficiency, low latency queries, and real-time analytics against temporal data. Running your time series applications on MongoDB eliminates the time and the complexity of having to stitch together multiple technologies yourself. You can manage the entire time series data lifecycle in MongoDB – from ingestion, storage, querying, real-time analysis, and visualization through to online archiving or automatic expiration as data ages. Time series collections can sit right alongside regular collections in your MongoDB database, making it really easy to combine time series data with your enterprise data within a single versatile, flexible database – using a single query API to power almost any class of workload. Our new time-series collections blog post gives you everything you need to get started. Future-proof with the Versioned API and Live Resharding Update January 31, 2022: "Versioned API" has been rebranded as "Stable API." Learn more about Stable API here . Starting with MongoDB 5.0, the Versioned API future-proofs your applications. You can fearlessly upgrade to the latest MongoDB releases without the risk of introducing backward-breaking changes that require application-side rework. Using the new versioned API decouples your app lifecycle from the database lifecycle, so you only need to update your application when you want to introduce new functionality, not when you upgrade the database. Future-proofing doesn’t end with the Versioned API. MongoDB 5.0 also introduces Live Resharding which allows you to easily change the shard key for your collections on demand – with no database downtime – as your workload grows and evolves. The way I like to think about this is that we’ve extended the flexibility the document model has always given you down to how you distribute your data. So as things change, MongoDB adapts without expensive schema or sharding migrations. Next-Gen Privacy & Security MongoDB’s unique Client-Side Field Level Encryption now extends some of the strongest data privacy controls available anywhere to multi-cloud databases. And with the ability in 5.0 to reconfigure your audit log filters and rotate x509 certificates without downtime you maintain a strict security posture with no interruption to your applications. Run MongoDB 5.0 Anywhere MongoDB 5.0 is available today as a fully-managed service in Atlas . You can of course also download and run MongoDB 5.0 on your own infrastructure, either with the community edition of MongoDB, or with MongoDB Enterprise Advanced . The Enterprise Advanced offering provides sophisticated operational tooling via Ops Manager, advanced security controls, proactive 24x7 support, and more. MongoDB Ops Manager 5.0 enhancements include: Support for the automation, monitoring, and backup/restore of MongoDB 5.0 deployments. Improved load performance with parallelized client-side restores. A quick start experience for deploying MongoDB in Kubernetes with Ops Manager. And lastly, a guided Atlas migration experience that walks users through provisioning a migration host to push data from their existing environment into the fully managed Atlas cloud service. You can learn more about MongoDB 5.0 from our What’s New guide . New to MongoDB Atlas — Serverless Instances (Preview) We want developers to be able to build MongoDB applications without having to think about database infrastructure or capacity management. With serverless instances on MongoDB Atlas, now available in Preview, you can automatically get the database resources you need based on your workload demand. It’s really simple: the only decision you need to make is the cloud region hosting your data. After that, you’ll get an on-demand database endpoint that dynamically adapts to your application traffic. Serverless instances will support the latest MongoDB 5.0 GA release, Versioned API, and upcoming Rapid Releases so you never have to worry about backwards compatibility or upgrades. Pay only for reads and writes your application performs and the storage resources you use (up to 1TB of storage in preview) and leave capacity management to MongoDB Atlas’s best-in-class automation. We invite you to try it out today with a new or existing Atlas account. And the Preview release is just the beginning – we will be working with partners such as Vercel and Netlify to deliver an integrated serverless development experience in the coming months. In the longer term, we will continue to evolve our cloud-native backend architecture to abstract and automate even more infrastructure decisions and optimizations to deliver the best database experience on the market. The New MongoDB Shell GA The new MongoDB Shell has been redesigned from the ground up to provide a modern command-line experience with enhanced usability features and powerful scripting environment. It makes it even easier for users to interact and manage their MongoDB data platform, from running simple queries to scripting admin operations. A great user experience, even on a command-line tool, should always be a major consideration. With the new MongoDB Shell we have introduced syntax highlighting, intelligent auto-complete, contextual help and useful error messages creating an intuitive, interactive experience for MongoDB users. Check out this blog post for more information. MongoDB Charts and Atlas Data Lake: Better Together MongoDB Charts intuitive UI and ability to quickly create & share charts and graphs of JSON data is now integrated with Atlas Data Lake . You can now easily visualize JSON data stored in Amazon AWS S3 without any data movement, duplication or transformation. Furthermore, you can run Atlas Data Lake’s federated query to blend data across multiple Atlas databases and AWS S3, and visualize the results with Charts. By adding Atlas Data Lake as a data source in Charts, you can discover deeper, more meaningful insights in real time. Check out this blog post for more information. Atlas Search — More Relevance Features It’s incredibly important for modern applications to deliver fast and relevant search functionality: it powers discoverability and personalization of content, which in turn drives user engagement and retention. Atlas Search , which delivers powerful full-text search functionality without the need for a separate search engine, has several new capabilities for building rich end user experiences. We’ve recently added support for function scoring, which allows teams to apply mathematical formulas on fields within documents to influence their relevance, such as popularity or distance — e.g. closer restaurants with more or better reviews will show up higher in a list of results. In addition, you can now define collections of synonyms for a particular search index. By associating semantically equivalent terms with each other, you can respond to a wider range of user-initiated queries in your applications. Realm Realm lets you have simple, powerful local persistence on mobile phones, tablets and IoT devices like Raspberry Pi. The Realm SDKs provide a set of APIs that let developers store and interact with native objects directly, reducing the amount of code required as there is no need for ORMs or learning cryptic database syntax. In addition, we made MongoDB Realm Sync generally available earlier this year, making it easy to synchronize data between local storage on your devices and MongoDB Atlas on the backend. No need to worry about networking code or dealing with conflict resolution as we handle all of that for you. Today, we’re excited to announce support for Unity. You can now use Realm to store your game data, like scores and player state, and sync it automatically across devices. Realm's support for Unity is now Generally Available and ready for production workloads. We're also investing in support for more cross-platform frameworks — the Kotlin Multiplatform and Flutter/Dart SDKs are now both available in Alpha. And finally, the team is working towards Realm Flexible Sync, a new way to synchronize data with more granular control. Flexible Sync will allow you to — Build applications that respond dynamically to user's needs. Let your end users decide what data they need, and when. Use more precise permissions that can adapt over time. Check out this dedicated blog on our upcoming plans for Flexible Sync to learn more. Getting Started With everything we announced today, you can imagine it was a packed keynote! And there is so much more that we didn’t cover. You can get all of the highlights from our new announcements page where you will also find all the resources you need to get started.

July 13, 2021
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Collaborating to Build AI Apps: MongoDB and Partners at Google Cloud Next '24

From April 9 to April 11, Las Vegas became the center of the tech world, as Google Cloud Next '24 took over the Mandalay Bay Convention Center—and the convention’s spotlight shined brightest on gen AI. Check out our AI resource page to learn more about building AI-powered apps with MongoDB. Between MongoDB’s big announcements with Google Cloud (which included an expanded collaboration to enhance building, scaling, and deploying GenAI applications using MongoDB Atlas Vector Search and Vertex AI ), industry sessions, and customer meetings, we offered in-booth lightning talks with leaders from four MongoDB partners—LangChain, LlamaIndex, Patronus AI, and Unstructured—who shared valuable insights and best practices with developers who want to embed AI into their existing applications or build new-generation apps powered by AI. Developing next-generation AI applications involves several challenges, including handling complex data sources, incorporating structured and unstructured data, and mitigating scalability and performance issues in processing and analyzing them. The lightning talks at Google Cloud Next ‘24 addressed some of these critical topics and presented practical solutions. One of the most popular sessions was from Harrison Chase , co-founder and CEO at LangChain , an open-source framework for building applications based on large language models (LLMs). Harrison provided tips on fixing your retrieval-augmented generation (RAG) pipeline when it fails, addressing the most common pitfalls of fact retrieval, non-semantic components, conflicting information, and other failure modes. Harrison recommended developers use LangChain templates for MongoDB Atlas to deploy RAG applications quickly. Meanwhile, LlamaIndex —an orchestration framework that integrates private and public data for building applications using LLMs—was represented by Simon Suo , co-founder and CTO, who discussed the complexities of advanced document RAG and the importance of using good data to perform better retrieval and parsing. He also highlighted MongoDB’s partnership with LlamaIndex, allowing for ingesting data into the MongoDB Atlas Vector database and retrieving the index from MongoDB Atlas via LlamaParse and LlamaCloud . Guillaume Nozière - Patronus AI Andrew Zane - Unstructured Amidst so many booths, activities, and competing programming, a range of developers from across industries showed up to these insightful sessions, where they could engage with experts, ask questions, and network in a casual setting. They also learned how our AI partners and MongoDB work together to offer complementary solutions to create a seamless gen AI development experience. We are grateful for LangChain, LlamaIndex, Patronus AI, and Unstructured's ongoing partnership. We look forward to expanding our collaboration to help our joint customers build the next generation of AI applications. To learn more about building AI-powered apps with MongoDB, check out our AI Resources Hub and stop by our Partner Ecosystem Catalog to read about our integrations with these and other AI partners.

April 23, 2024