MongoDB Management Service Release Notes: MongoDB Backup via API

MongoDB
July 14, 2014 | Updated: August 16, 2023

MongoDB World is done, and after a quick holiday weekend, the MongoDB team was back at work wrapping up this release. There’s a lot to tell customers about, too - our release this week features:

An automated flow for resetting two-factor authentication
More Backup features in the Public API including pull (HTTP) restores and management of snapshots and snapshot schedules
Ability to add a comment when an alert is acknowledged and receive notification of the acknowledgement
Auditing of alert configuration changes, so any modifications to alerting criteria are shown in the Activity Feed

Our MongoDB Backup Service received some slight tweaking - we modified the initial sync settings somewhat so that now initial sync will not include hidden and delayed secondaries as choices for initial sync, and it won’t allow users to sync from a secondary with a different version than the primary.

The backup and monitoring agents also received updates:

The monitoring agent (now Version 2.3.1.89-1) received a fix for the Go driver to stop hung connections to replica set members that use authentication; also, HTTP proxy configuration can now be specified in the agent configuration file.
The backup agent (now Version 2.2.1.122) gained the ability to send a stacktrace of its current state to the MMS API, as well as the Go driver fix and some work to optimize the agent’s ability to handle rollbacks of replica sets.

We are also working on updates to the OnPrem version of the MongoDB Management Service. We added LDAP authentication support for the MMS server connecting to backing MongoDBs this iteration and hope to add even more in our next release.

Our automation beta is also continuing with select customers. You can read more about that (and sign up to receive private preview!) here.

Have an issue or a bug or a feature request? File a ticket in our feature request queue!

-Rachelle (@techbelle)

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Using MMS Backup to Seed New Environments

One of the benefits of using MMS to back up MongoDB is that you have unlimited restores, which means you can use these restores in ways that might not have imagine. For example, you can use MMS to seed a new replica set member. In fact, it can be faster with very large datasets or on replica sets under heavy load. It will only work if the latest snapshot (or the custom last 24 hour point in time snapshot) is still covered by the oplog window. Then you could seed the new member with the snapshot and then allow it to sync to the other replica set members. The instructions can be found in the docs . Please note: if you use “Excluded Namespaces” on your MMS Backup (these exclude collections or entire databases from the snapshots), you will not be able to use MMS Backup snapshots to seed. There are lots of other scenarios in which you might use MMS to build new environments. We covered some of them in a recent webinar. The slides and video are now available.

July 10, 2014

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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