Introducing Snapshot Distribution in MongoDB Atlas

Ashley Kuhwilm
September 29, 2022
#Atlas

Data is at the heart of everything we do and in today’s digital economy has become an organization's most valuable asset. But sometimes the lengths that need to be taken to protect that data can present added challenges and result in manual processes that ultimately slow development, especially when it comes to maintaining a strict backup and recovery strategy.

MongoDB Atlas aims to ease this burden by providing the features needed to help organizations not only retain and protect their data for recovery purposes, but to meet compliance regulations with ease. Today we’re excited to announce the release of a new backup feature, Snapshot Distribution. Snapshot Distribution allows you to easily distribute your backup snapshots across multiple geographic regions within your primary cloud provider with the click of a button.

You can configure how snapshots are distributed directly within your backup policy and Atlas will automatically distribute them to other regions as selected—no manual process necessary.

How to distribute your snapshots

To enable Snapshot Distribution, navigate to the backup policy for your cluster and select the toggle to copy snapshots to other regions. From there, you can add any number of regions within your primary cloud provider—including regions you are not deployed in—to store snapshot copies. You can even customize your configuration to copy only specific types of snapshots to certain regions.

Screenshot of the field to enable Snapshot Distribution in your backup policy
Copy snapshots to other regions

Restore your cluster faster with optimized, intelligent restores

If you need to restore your cluster, Atlas will intelligently decide whether to use the original snapshot or a copied snapshot for optimal restore speeds. Copied snapshots may be utilized in cases where you are restoring to a cluster in the same region as a snapshot copy, including multi-region clusters if the snapshots are copied to every cluster region. Alternatively, if the original snapshot becomes unavailable due to a regional outage within your cloud provider, Atlas will utilize a copy in the nearest region to enable restores regardless of the cloud region outage.

Screenshot of the point in time restore option in MongoDB Atlas
Perform point in time restore

Get started with Snapshot Distribution

Although storing additional snapshot copies in varying places may not always be required, this can be extremely useful in several situations, such as:

  • For organizations who have a compliance requirement to store backups in different geographical locations from their primary place of operation

  • For organizations operating multi-region clusters looking for faster direct-attach restores for the entire cluster

If you fall into either of these categories, Snapshot Distribution may be a valuable feature addition to your current backup policy, allowing you to automate prior manual processes and free up development time to focus on innovation. Check out the documentation to learn more or navigate to your backup policy to enable this feature.

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Built With MongoDB: Satori Streamlines Secure Data Access

Handling data imposes contradictory responsibilities upon organizations. On one hand, they need to protect data from unauthorized access. On the other hand, they need to extract value from data; otherwise, why collect it in the first place? The contradiction lies in the fact that to extract value from data, you have to grant access to it, but unregulated access to data can lead to its misuse. Data access service provider Satori enables organizations to accelerate their data use by simplifying and automating access policies while helping to ensure compliance with data security and privacy requirements. In addition to being a member of the MongoDB for Startups program, Satori has just added support for MongoDB workloads, so organizations running MongoDB can now take advantage of Satori's secure data access service. Balancing act Despite the immense volume of sensitive personal, financial, or health-related data within most organizations, managing access to that data is often a manual process handled by a small team struggling with other competing interests. Satori chief scientist Ben Herzberg says this task of managing data access at companies is slowing down innovation. "The majority of organizations are still managing access to data in a manual way," Herzberg says. "Everyone is feeling the bottleneck. The data analyst who wants to do their job in a meaningful way just wants to understand what data sets they can use and get access to it fast." Getting access to data can be an uphill battle, however. "Sometimes you have to go through three or four different teams to get access to data," Herzberg says. "It can take a week or two." Meanwhile, the data engineers who are primarily responsible for managing access to data are getting pulled away from their core responsibilities. "This places the company in an uncomfortable position of having time-intensive processes implemented by teams who would prefer to be working on other tasks," Herzberg says. Simple, fast, secure As a data access service, Satori streamlines access to data, accelerates time-to-value, improves engineering productivity, and reduces complexity and operational risk, all while protecting sensitive data and maintaining compliance with relevant data privacy regulations. The first job of protecting sensitive data is identifying it, but according to Satori's research , few companies have a system in place that continuously monitors for and discovers sensitive data. Organizations that do monitor sensitive data typically do so only quarterly or annually. Herzberg says Satori continuously discovers sensitive data as it's being accessed. "As one of our customers said: I want to remain continuously compliant. I want to know where my sensitive data is at all times. We do that," Herzberg says. Data users can request access to data over Slack, the Satori data portal, and through other integrations to get immediate access to data without any engineering effort, changes to infrastructure, schemas, or tables, or creating objects on the database. "When a lot of people want access to data, you need a simple, fast, and secure way to do it without exposing yourself to risk," Herzberg says. Instead of taking days or weeks to process data access requests, with Satori, it takes just minutes. Build the next big thing with MongoDB Satori chose MongoDB early on because of the inherent flexibility of the document data model. "We chose MongoDB to move quickly and without limitations," Satori software engineering manager Oleg Toubenshlak says. "We didn't know what type of data we would be storing or how we might want to extend objects, so we chose MongoDB because of the flexibility of the data model." "MongoDB is a core component of our infrastructure where we keep customer configurations," Toubenshlak says. "We started with MongoDB deployed on-prem and moved to MongoDB Atlas." Toubenshlak cites continuous backups, easy deployment, and scalability as additional Atlas capabilities he finds valuable. "MongoDB allows us to move fast with development so we can focus on other areas. It's very simple in terms of security and network access. In terms of clients, MongoDB Atlas helps us provide extended capabilities in order to map our Java objects to BSON. It's very compatible and does this very quickly. Once we moved to Atlas, all our problems were solved," he says. Toubenshlak also appreciates the help he received as a member of the startup program. "We had startup credits, and we used professional services to make sure everything was configured properly," he says. "Satori is a small cluster for MongoDB, but I'm very surprised at the time investment we've received." The company is also excited about adding MongoDB Atlas to its list of supported platforms. "Adding MongoDB support is very exciting for us," Herzberg says. "We're already working with some design partners in different industries and helping them with their deployment. It's a meaningful step for us in NoSQL databases. We're seeing a lot of traction with existing customers that want to expand their MongoDB deployments and with new customers." If you're running MongoDB and are interested in simplifying data access, visit Satori and set up a demo or test drive. Are you part of a startup and interested in joining the MongoDB for Startups program? Apply now .

September 28, 2022
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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