MongoDB 3.2.0-rc3 is released

MongoDB
November 17, 2015

MongoDB 3.2.0-rc3 is out and is ready for testing. This is the culmination of the 3.1.x development series.

Fixed in this release candidate:

  • SERVER-20164: Finish unit tests for CatalogManagerReplicaSet::addShard
  • SERVER-21287: $lookup should use $eq queries
  • SERVER-21298: rollback_index.js fails to wait for replication before continuing
  • SERVER-21292: replsets/remove1.js failed in replset_legacy suite
  • SERVER-20937: Add mode to FSM framework that drives greater amount of load on the system
  • SERVER-21099: Improve logging in SecureRandom and PseudoRandom classes
  • SERVER-20402: Add Election Failover JS tests
  • SERVER-21308: fsm-suite doesn’t wait long enough for the distributed lock when dropping a collection
  • SERVER-20867: Integrate mongobridge into ShardingTest
  • SERVER-21355: Coverity analysis defect 76731: Unchecked return value
  • SERVER-21305: Lock ‘timeAcquiringMicros’ value is much higher than the actual time spent
  • SERVER-21371: find_and_modify_concurrent_update.js join() is called after read
  • TOOLS-983: mongorestore panic when restoring a compressed archive without using –gzip

Want to test the release? Get involved in the MongoDB Bug Hunt and enter for a chance to win some prizes for your contributions.

3.2 Release Notes | Downloads | All Issues

As always, please let us know of any issues.

– The MongoDB Team

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MongoDB Authentication and Automation

MongoDB supports role-based authentication, so you can restrict access to your deployment for safety and security. Cloud Manager Automation makes enabling and managing your users easy. An important note before we begin: Authentication Settings made here apply to your entire Cloud Manager group. If you are using Automation, and it’s vital that different deployments in your group have different credentials, you will have to create a new Cloud Manager group for these deployment items and import them . Enabling Authentication If you already have authentication enabled, follow the normal importation into Automation methodolgy , especially noting the creation of a new automation-agent user, then you can skip this section and go on to the role and user management sections below. If you have an unauthenticated deployment: Click the “…” menu on your Deployment Page and choose “Authentication & SSL Settings” Click “Next” to get to the “Select Authentication Mechanisms” screen Select “Username/Password” and click “Next”. Click “Next” again to skip the SSL settings (a topic for this other post ). Now you will see the new users that will be automatically created for you. Click “Save” to create a new automation draft with your new users. Now you just have to “Review & Deploy” and “Confirm & Deploy” as normal. Beware: Clients without authentication will fail to connect after this point. Make sure your application is ready for this change. Check your drivers’ documentation on how to enable MongoDB authentication in your application. Role Management Let’s start with adding a new role: Head over to your “Authorization & Roles” tab When you click the “Add Role” button in the upper-right, you will be presented with a dialog to fill out: You can even add collection-level and other privileges if you want In my case, I’ve let my reader role also be able to do certain diagnostic actions Once the role is added, you just have to do the usual “Review & Deploy”/”Confirm & Deploy” to push this role out to your group. Once the role has been created, you can edit or remove it via the gear icon, as shown below. You can only edit custom roles, not built-in roles . Users Once you have the roles you need (if you need custom roles at all), you can start creating users. Head to your “Authentication & Users” tab Create a new user via the “Add User” button in the upper-right You can choose any custom or built-in roles you wish and enter the user’s password Once the user is added, you just have to do the usual “Review & Deploy”/”Confirm & Deploy” to push this user out to your group. Once the user has been created, you can edit or delete it via the gear. You cannot edit the built-in users for the agents. Removing Authentication Maybe you have moved your deployment into a private network and have decided to remove your authentication settings. Here’s how: Click the “…” menu on your Deployment page and select “Authentication & SSL Settings” Click “Next” to get to the “Authentication Mechanisms” screen and un-check “Username/Password” Click “Next” to skip the SSL settings, and then click “Save” When you next do a “Review & Deploy”/”Confirm & Deploy”, the Automation Agents will disable authentication. All your custom roles and users will remain cached in Cloud Manager in case you wish to re-enable authentication. You can edit them even when authentication is not enabled.

November 16, 2015
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