Atlas Mapped: New Cross-Region VPC Peering And 60 Regions
The MongoDB Atlas platform is constantly evolving and in this new, regular column, we're going to summarize what's launched in Atlas over the past few weeks to get you up to speed with its rapid evolution. In this edition, Atlas Cross-Region VPCs arrive, AWS Stockholm gets Atlas and M700s, Controlling maintenance times, custom database roles and workload isolation for analytics.
New 0.7 Release of the MongoDB Enterprise Operator for Kubernetes Beta
New 0.7 Release of the MongoDB Enterprise Operator for Kubernetes Beta
The MongoDB Enterprise Operator for Kubernetes enables you to automate your deployment of MongoDB in Kubernetes clusters. The operator leverages the power of MongoDB Ops Manager and MongoDB Cloud Manager providing you a simple single Kubernetes interface for MongoDB deployment and management.
In this release 0.7, we spent a significant amount of time in the plumbing dealing with state reconciliation. Our Operator can now manage state synchronization between Kubernetes and MongoDB making it easy to handle state changes and provide a more reliable operational experience. For a complete description of the changes see the release notes.
MongoDB Enterprise Operator for Kubernetes 0.7 Release Notes
For download and installation instructions:
GitHub Repository for MongoDB Enterprise Operator for Kubernetes
Want Ops Manager updates faster? Introducing Rapid Releases!
We're announcing an additional new Ops Manager release schedule: the Ops Manager Rapid Release, designed to let you test the latest updates to Ops Manager. Customers will be able to download and try out a new build of Ops Manager around every three weeks.
Official MongoDB Go Driver Now Available for Beta Testing
We’re pleased to announce that the official MongoDB Go driver is moving into beta, ready for the wider Go and MongoDB community to put it to the test – we think you’ll really like it.
In this blog, we will discuss:
- The growing importance of Go
- How we use it today at MongoDB
- Our rationale for building a new driver
- Resources to get you started with it.
Go Migration Guide
MongoDB has released an official driver for the Go language that is appropriate for all supported database operations. This driver implements the Core and API specs, and supports MongoDB 3.2 and above.
Many developers have been using community contributed golang drivers such as mgo and variants or forks of it. Developers who are interested in migrating to the official MongoDB Go driver have many considerations when approaching a migration of their application code. This migration guide is intended to provide guidance on some commonly found differences in client code when using the MongoDB Go Driver, and present potential actions to be taken during a migration.
MongoDB Go Driver Tutorial
With the official MongoDB Go Driver recently moving to beta, it's now regarded as feature complete and ready for a wider audience to start using. This tutorial will help you get started with the MongoDB Go Driver. You will create a simple program and learn how to:
- Install the MongoDB Go Driver
- Connect to MongoDB using the Go Driver
- Use BSON objects in Go
- Send CRUD operations to MongoDB
MongoDB Charts Beta, Now Available in Atlas
Earlier in the year, we announced the availability of MongoDB Charts Beta, the fastest and easiest way to build visualizations of MongoDB data. Today at Mongodb.local San Francisco, we are excited to announce that an update to the beta is now available and integrated into MongoDB Atlas, our hosted database as a service platform. This means that Atlas users can now visualize their data and share with their team, without the need to install or maintain any servers or tools.
Getting started with MongoDB Charts in Atlas couldn’t be simpler. After logging into Atlas, select the Project with the clusters containing the data you want to visualize and click the Charts link in the left navigation bar. After a one-time step to activate Charts, you will be ready to start charting!
If you’ve used MongoDB Charts before, the new Atlas-integrated version will be instantly familiar. The main difference is that you can easily add data sources from any Atlas clusters in your project without needing to enter a connection URI. You’re also freed from the burden of managing users separately, with all Atlas Project members able to access Charts with their existing Atlas credentials provided they have Data Access Read Only role or higher.
We’ve also been busy adding some of the most requested features to the charting experience. Charts has always been great at handling MongoDB’s flexible schema, allowing you to build charts from document-based data that contains nested documents or arrays. In this latest release, we’ve added a number of options for chart authors to customize their charts, including changing axis titles, colors, date formats and more.
After you’ve created a few charts, you can arrange them on a dashboard to get all of the information you need at a glance. Dashboards can be kept private, shared with selected individuals, or with everyone in your project team.
If you’re not currently using Atlas, we haven’t forgotten about you. MongoDB Charts Beta is also still available to install into your own server environment, allowing you to visualize data from any MongoDB server. We’ll be refreshing the on-premises beta to include the same charting enhancements as seen in the new Atlas version over the coming weeks.
We hope you enjoy this update and that it helps you get the insight you need from your data. If you have any questions or feature requests, you can always send a note to the Charts team by clicking the support button on the bottom of every page.
New to MongoDB Atlas — Get Started with Free Fully Automated Databases on Microsoft Azure
We’re excited to announce that teams can now use MongoDB Atlas — the global cloud database for MongoDB — for free on Microsoft Azure. The newly available free tier on Azure Cloud, known as the M0, grants users 512 MB of storage and is ideal for learning MongoDB, prototyping, and early development.
The Atlas free tier will run MongoDB 4.0 and grant users access to some of the latest database features, including multi-document transactions, which make it even easier to address a complete range of use cases with MongoDB; type conversions, which allow teams to perform sophisticated transformations natively in the database without costly and fragile ETL; and updated security defaults (SHA-256 and TLS 1.1+).
Like larger MongoDB Atlas cluster types, M0 clusters grant users optimal security with end to end encryption, high availability, and fully managed upgrades. M0 clusters also enable faster development by allowing teams to perform CRUD operations against their data right from their browsers via the built-in Data Explorer.
Finally, free tier clusters on Azure can be paired with MongoDB Stitch — a powerful suite of serverless platform services for apps using MongoDB — to simplify the handling of backend logic, database triggers, and integrations with the wider Azure ecosystem.
At launch, the MongoDB Atlas free tier will be available in 3 Azure regions:
- East US (Virginia)
- East Asia (Hong Kong)
- West Europe (Netherlands)
Creating a free tier is easy. When building a new Atlas cluster, select Azure as your cloud of choice and one of the regions above.
Next, select M0 in the “Cluster Tier” dropdown.
Then, give the cluster a name and hit the “Create Cluster” button. Your free MongoDB Atlas cluster will be deployed in minutes.
MongoDB Atlas: Connector for Apache Spark now Officially Certified for Azure Databricks
We are happy to announce that the MongoDB Connector for Apache Spark is now officially certified for Microsoft Azure Databricks. Databricks, founded by the original creators of Apache Spark, provides the Databricks Unified Analytics platform. MongoDB Atlas users can integrate Spark and MongoDB in the cloud for advanced analytics and machine learning workloads by using the MongoDB Connector for Apache Spark which is fully supported and maintained by MongoDB.
The MongoDB Connector for Apache Spark exposes all of Spark’s libraries, including Scala, Java, Python, and R. MongoDB data is materialized as DataFrames and Datasets for analysis with machine learning, graph, streaming, and SQL APIs. The MongoDB Connector for Apache Spark can take advantage of MongoDB’s aggregation pipeline and rich secondary indexes to extract, filter, and process only the range of data it needs – for example, analyzing all customers located in a specific geography. This is very different from simple NoSQL data stores that do not offer secondary indexes or in-database aggregations and require the extraction of all data based on a simple primary key, even if only a subset of that data is needed for the Spark process. This results in more processing overhead, more hardware, and longer time-to-insight for data scientists and engineers.
Additionally, MongoDB’s workload isolation makes it easy for users to efficiently process data drawn from multiple sources into a single database with zero impact on other business-critical database operations. Running Spark on MongoDB reduces operational overhead as well by greatly simplifying your architecture and increasing the speed at which analytics can be executed.
MongoDB Atlas, our on-demand, fully-managed cloud database service for MongoDB, makes it even easier to run sophisticated analytics processing by eliminating the operational overhead of managing database clusters directly. By combining Azure Databricks and MongoDB, Atlas users can make benefit of a fully managed analytics platform, freeing engineering resources to focus on their core business domain and deliver actionable insights quickly.
New to MongoDB Atlas — Data Explorer Now Available for All Cluster Sizes
At the recent MongoDB .local Chicago event, MongoDB CTO and Co-Founder, Eliot Horowitz made an exciting announcement about the Data Explorer feature of MongoDB Atlas. It is now available for all Atlas cluster sizes, including the free tier.
The easiest way to explore your data
What is the Data Explorer? This powerful feature allows you to query, explore, and take action on your data residing inside MongoDB Atlas (with full CRUD functionality) right from your web browser. Of course, we've thought about security; Data Explorer access and whether or not a user can modify documents is tied to her role within the Atlas Project. Actions performed via the Data Explorer are also logged in the Atlas alerting window.
Bringing this feature to the "shared" Atlas cluster sizes — the free M0s, M2s, and M5s — allows for even faster development. You can now perform actions on your data while developing your application, which is where these shared cluster sizes really shine.
Check out this short video to see the Data Explorer in action.