MongoDB Updates
The newest releases and freshest updates
How to Build Advanced GraphQL-based APIs With MongoDB Atlas and AWS AppSync Merged APIs
When businesses develop their own IT systems, sooner or later, the complexity of managing APIs becomes a challenge. Breaking down monolithic architectures into multiple microservices often results in a proliferation of APIs associated with each microservice. Each API, in turn, has versioning, leading to further fragmentation of the APIs and driving up maintenance costs. If your microservices diagram looks like a hairball you know you are living in API Hell. Conway’s Law , which states that systems mirror the communication structure of the organization, also applies to API development. Different teams build separate and, sometimes, overlapping APIs, further contributing to the fragmentation. While this is especially true for REST-based APIs , it's also a challenge for GraphQL -based APIs. GraphQL has emerged as a powerful tool for building flexible and efficient APIs that empower developers and elevate user experiences. AWS AppSync is the go-to service for customers looking to accelerate application development with serverless GraphQL and Pub/Sub APIs. AWS AppSync offers a managed GraphQL service with additional features and capabilities. It simplifies the development of scalable, real-time applications by seamlessly integrating with various data sources, providing offline support, enabling fine-grained authorization and security, and automating infrastructure management. By embracing AppSync, you can harness the full potential of GraphQL while leveraging the benefits of a comprehensive portfolio of services and products provided by AWS. MongoDB Atlas on Amazon Web Services (AWS) and AWS AppSync combined help developers build scalable, secure, and serverless applications. By seamlessly integrating MongoDB as a data source within AppSync, you're able to leverage MongoDB's flexible document model and AppSync's GraphQL-based querying to efficiently retrieve and manipulate data. And you can leverage AppSync's automatic scaling, ensuring optimal performance. This combined solution enables you to build high-performing serverless applications while simplifying application development. AWS AppSync recently added a feature called Merged APIs that allows you to compose multiple GraphQL source APIs into a single GraphQL API. Merged APIs give developers the ability to compose distinct APIs developed by different teams into a single, combined GraphQL schema. The merged API resolver function contains the logic to consolidate the source details. The resulting single GraphQL API can be cached for better performance. You can then present the unified API to the clients as a single API endpoint. AppSync Merged APIs combine MongoDB Atlas-backed APIs with other APIs, allowing you to enrich operational data residing in MongoDB Atlas with data coming from additional sources. You can serve data with a unified GraphQL schema across multiple data sources, including MongoDB. If you're interested in learning more about this powerful integration, check out our new tutorial that demonstrates two ways to combine MongoDB Atlas with AWS AppSync : leveraging the Drivers and the Atlas Data API. Both approaches work with the AWS AppSync Merged API as well. Checkout our tutorial on GitHub . Try out MongoDB Atlas on AWS ( Atlas GraphQL ) and AWS AppSync today. Sign up for MongoDB Atlas on AWS Marketplace Today
Improved Developer Experience with the Atlas Admin API
With MongoDB Atlas, we meet our developers where they are and offer multiple ways to get started and work with Atlas. One of the ways to get started programmatically with Atlas is through the Atlas Administration API. It provides programmatic access to Atlas resources such as clusters, database users, or backups to name a few, enabling developers to perform operational tasks like creating, modifying, and deleting resources. We are excited to announce two key capabilities that will improve the developer experience when working with the Atlas Administration API. Versioned Atlas Administration API If you use the Atlas Administration API today, you are working with the unversioned Administration API (/v1). We have heard your feedback on the challenges around the API changes not having a clear policy as well as communication gaps about the new features/ deprecations. To address this, we are excited to now introduce resource-level versioning with our new versioned Atlas Administration API ( /v2). Here is what you can expect: More predictability and consistency in handling API changes: With this new versioning, any breaking changes that can impact your code will only be introduced in a new resource version. You can rest assured that no breaking changes will affect your production code running the current, stable version. Also, deprecation will occur with the introduction of a new stable API resource version. This will give you at least 1 year to upgrade before the removal of the deprecated resource version. It adds more predictability to what’s coming to the API. Minimum impact with resource-based versioning: With the resource level versioning, whenever we talk about API versions we’re referring to the actual API resource versions represented by date. So once you migrate from the current unversioned Administration API (/v1) to the new versioned Administration API (/v2), this will point to version 2023-02-01. To make the initial migration process smooth and easy this first resource version applies to all API resources (e.g. /serverless, /backup, /clusters, etc.). However, moving forward, each resource can introduce a new version (e.g. /serverless can move to 2023-06-01, /backup can stay on 2023-02-01) independently from each other at various points in time. The advantage is that if you have not implemented the e.g. /serverless resource and say a new version is introduced, you will not need to take any action. You will only need to take action if and when the resources you are utilizing are deprecated. More time to plan your migration: Once a particular resource version is deprecated, there will be enough time ( 12 months) before it is removed, so this will give you ample time to plan and transition to the new version. Improved context and visibility: Our updated documentation has all the details to guide you through the versioning process. Whether it’s a release of a new endpoint, deprecation of an existing resource version, or a non-breaking change to a #stable resource - all of them are now tracked on a dedicated and automatically updated Changelog . Other than that we provide more visibility and context on any API changes through the API specification which presents information for all stable and deprecated resource versions enabling you to access documentation that’s relevant for your particular case. We have made it very simple for you to get started with the new versioned Administration API (/v2). To start using it you need to migrate from the current Unversioned Administration API (/v1) to the new Versioned Administration API (/v2). This migration can be done smoothly by making two changes in your code: Update the path of each endpoint from /v1 to /v2 . Add a version header to each endpoint: application/vnd.atlas.2023-02-01+json. The 2023-02-01 version will have a long support timeframe of 2 years from its deprecation, giving you ample time to transition. Read more about the versioned Admin API. To learn more about the transition process, read our migration guide . Go SDK for the Atlas Administration API One of the mechanisms that simplifies interaction with APIs is the availability of SDKs. To make it easy to get started and work with the Versioned Administration API, we are excited to introduce the new Go SDK for the Administration API. If you are a Go developer and have interacted with the Atlas Administration API, you must be familiar with our current Go client. We are now introducing the new Go SDK for the Atlas Admin API. This provides a significantly improved developer experience for Go developers as it supports full endpoint coverage, improves the speed of getting started with the versioned Admin API, provides you a consistent experience when working with the Admin API, and gives you the choice of version for better control of changes and the impact on the scripts. Let’s look at some of the benefits you can expect: Full Atlas Administration API endpoint coverage: The new Go SDK allows you to access all the features and capabilities that the Atlas Administration API offers today with full endpoint coverage. This ensures you can programmatically leverage the full breadth of the developer data platform. Flexibility in choosing the API resource version: When interacting with the new versioned Atlas Administration API through the Go SDK client, you can choose a particular version of the Admin API, giving you control over when you are impacted by breaking changes or always work with the latest version. Ease of use: Your getting started experience for Admin API through the Go SDK client is now much more simplified with fewer lines of code since it includes pre-built functions, structs, and methods that encapsulate the complexity of HTTP requests, authentication, error handling, versioning, and other low-level details. Immediate access to updates: When using the new Go SDK, you can immediately access any newly released Atlas Admin API capabilities. And every time a new version of Atlas is released, the SDK will be quickly updated and continuously maintained, ensuring compatibility with any changes in the API. Get started today with the GoSDK client. Also, refer to our migration guide to learn more.
New Online Archive with Performance Improvements and Enhanced Metrics
We are excited to announce several new features coming to Atlas Online Archive. With these improvements, customers will observe higher performance, be able to choose which region hosts their archival data, and have greater insight into the data stored in the archive through improved metrics. New storage engine We have optimized Online Archive through the introduction of a new storage engine that captures metadata during archival to power faster query performance. The new underlying storage service minimizes the overall data scan when querying the Online Archive. Additionally, the new storage engine delivers additional benefits in the form of storage optimizations like sorting as well as ongoing rebalancing to deliver consistent performance over time. With this feature, you will experience faster Online Archive querying performance while your overall costs are decreased when querying against the archives. Ability to choose a storage region With the new Online Archives, the users will be able to select the storage region at the time of creating an Online Archive. There will be a feature to choose one of the supported Data Federation regions from the dropdown during the creation process. In addition, we display the closest region so the users can make an informed decision about their storage region. Enhanced metrics With these new enhanced and improved metrics, we are helping customers better understand what data is in their archive such that they can connect to the appropriate endpoint for their use case and have insight into the performance of archival jobs. With these enhanced metrics, users can see a dashboard including the total # of documents in the archive and overall Archive data size (with a tooltip to explain metrics), what rate are archival jobs archiving, Min/Max Date Fields in the archive, and other statistics that are helpful and important for the users to increase the visibility of the archives. Newly created archives Note that only the newly created Online Archives on or after 06/07/2023 will see the performance improvements and enhancements initially. All existing archives created before 06/07/2023 will continue to function as-is (without the new improvements and enhanced metrics). Over the coming year, we will migrate all existing archives created before 06/07/2023 to the new backend storage service. See the documentation for additional information about creating new Online Archives and Enhanced Metrics .
Using MongoDB Skill Scanner to Build Better Training Programs
Technology leaders know that transformation is about more than just adopting modern technologies like MongoDB. The entire organization has to rally behind change — which is no easy task. The skills that modern development teams need are evolving faster than ever, and hiring to fill skills gaps can be too time-consuming and expensive of a process for many organizations. So it’s imperative that we plan for how we want to bring our people with us on our modernization journey, and proactively upskill them on the technologies we’re betting on. Because what happens if you choose MongoDB, but your developers don’t know how to use it? CIOs know that training programs are easier said than done. EY reported that 30% of CIOs acknowledge that their training programs are ineffective, and that they’re struggling to retain talent because of it. These leaders come to us to help them build and execute their MongoDB training programs , and seek advice on two extremely common yet critical challenges: How do we get away from the less effective one-size-fits-all approach? How do we measure the ROI of our training program and connect it to business impact? How we use MongoDB Skill Scanner to overcome training challenges Our Professional Services team uses a tool called MongoDB Skill Scanner to address both of these challenges. This tool helps us provide these three benefits to our customers looking to build a training program: Improve MongoDB proficiency: Teams can use Skill Scanner to quickly and easily assess the MongoDB skill gaps of their team members and gain a comprehensive understanding of their team’s MongoDB skills baseline. Increased productivity and accuracy: When team members have a comprehensive understanding of MongoDB, they are able to work more quickly and accurately on projects, leading to increased productivity and a higher quality of work. Save time and money with targeted Training: Using Skill Scanner, customers can avoid wasting time and money on trial-and-error learning. Instead, they can focus on improving their skills in a more targeted and efficient way with right-sized training plans. By leveraging this data, our customers’ engineers can engage in the right training at the right time, targeted for their job role and specific skill shortages. When a training program is built this way, engineers maximize their knowledge retention and minimize time away from their projects. Skill Scanner includes three role-based assessments, one for developers, database administrators, and DevOps respectively. Through a series of multiple choice questions, Skill Scanner provides customers with a clear understanding of their level of expertise across a set of technical skills that are critical for success in their role. After submitting the assessment, engineers will get results in each skill area outlining if they are beginner, intermediate, or advanced. Why data-driven training programs matter We’ve learned that it’s not enough to just tell teams to go watch training videos or webinars on their own, or to place everyone in the same one-size-fits-all program. Skills gaps vary from team to team, and individual to individual. The one-size-fits-all approach of some programs may not address individual learners' needs, wasting time and making it difficult for them to acquire new skills. By using Skill Scanner, we’re able to interpret this data to help determine which training courses your team should take. But we don’t only capture this data before doing training; we use Skill Scanner again after training programs are completed to see where immediate improvements have been made. This helps technology leaders prove the impact and ROI of their training, and gives them the confidence that their teams are ready to be successful with MongoDB. Developing a Precision Learning Program To go even further, our team can work with you to build a Precision Learning Program, where we use Skill Scanner data to build learning schedules that are unique to each individual. These schedules include a variety of short, blended, learning events such as classes, technical workshops, self-paced exercises, and project coaching. We’ve seen PLP lead to higher knowledge retention and of course, measurable project results. A customer who recently concluded their PLP saw a 43% increase in knowledge retention. Getting started building a personalized training program Skill gaps aren’t a novel problem IT leaders are facing. But with new digital courses, training, and technologies, the resources to close these gaps are at your fingertips. Skill Scanner and Precision Learning Program have been specifically designed to empower teams by offering targeted training that enhances their understanding of MongoDB. These short training events are carefully crafted to close skill gaps without compromising developer productivity. We’ve seen a variety of customers use this tool to help train their team’s individual needs, from needing to upskill new hires on their teams, projects with new MongoDB products, migrating to MongoDB Atlas, and more. It also saves your business the hours developers would've wasted searching for answers (and developers don’t want to spend their time that way, either). “We need help getting from point A to point B and feel MongoDB is uniquely positioned to help” — CTO at large insurance firm If you're interested in trying out MongoDB Skill Scanner or want to explore the MongoDB Precision Learning Program further, you can reach out to your account representative or contact us directly .
Introducing the Certified MongoDB Atlas Connector for Power BI
This is a collaborative post from MongoDB and Microsoft. We thank Alexi Antonino, Natacha Bagnard, Jad Jarouche from MongoDB, and Bob Zhang, Mahesh Prakriya, and Rajeev Jain from Microsoft for their contributions. Introducing MongoDB Atlas Connector for Power BI, the certified solution that facilitates real-time insights on your Atlas data directly in the Power BI interfaces that analysts know and love! Supporting Microsoft’s Intelligent Data Platform , this integration bridges the gap between Developers and Analytics teams, allowing analysts who rely on Power BI for insights to natively transform, analyze, and share dashboards that incorporate live MongoDB Atlas data. Available in June , the Atlas Power BI Connector empowers companies to harness the full power of their data like never before. Let’s take a deeper look into how the Atlas Power BI Connector can unlock comprehensive, real-time insights on live application data that will help take your business to the next level. Effortlessly model document data with Power Query The Atlas Power BI Connector makes it easy to model document data with native Power BI features and data modeling capabilities. With its SQL-92 compatible dialect, mongosql, you can tailor your data to fit any requirements by transforming heavily nested document data to fit your exact needs, all from your Power Query dashboard. Gain real-time insights on live application data By using the Power BI Connector to connect directly to MongoDB Atlas, you can build up-to-date dashboards in Power BI Desktop and scale insights to your organization through Power BI Service with ease. With no delays caused by data duplication, you can stay ahead of the curve by unlocking real-time insights on Atlas data that are relevant to your business. Empower cross-source data analysis The Power BI Connector's integration with MongoDB Atlas enables you to seamlessly model, analyze, and share insightful dashboards that are built from multiple data sources. By combining Atlas's powerful Data Federation capabilities with Power BI's advanced analytics and visualization tools, you can easily create comprehensive dashboards that offer valuable insights into your data, regardless of where it is stored. See it in action Log in and activate the Atlas SQL Interface to try out the Atlas Power BI Connector ! If you are new to Atlas or Power BI, get started for free today on Azure Marketplace or Power BI Desktop .
The MongoDB for VS Code Extension Is Now Generally Available
Three years ago, we introduced the MongoDB for VS Code Extension to the world in Public Preview. VS Code is the most popular Integrated Development Environment (IDE) for developers, and we were excited to bring the power of MongoDB, one of the world’s most-loved databases, to developers right in their favorite IDE. Since that time, we’ve seen skyrocketing growth in adoption of the extension, which now has over 800k installs and an average rating of 4.5 stars in the VS Code Extension store. The verdict is in: people love not only VS Code and MongoDB, but love a unified experience in the form of the MongoDB for VS Code Extension. Given the popularity of the tool and innovations we’ve continued to make in the experience, we are delighted to announce that the MongoDB for VS Code Extension is now generally available. Why use the extension? This free, downloadable extension makes it easy for developers to build applications and work application data in MongoDB directly from VS Code. Not only do you get the benefit of interacting with MongoDB data in a familiar IDE experience you’ve likely already customized to your preferences—you also can work with your application data and your application code all in one place. And with the extension now generally available (GA), you can have increased confidence in the extension and MongoDB’s long-term commitment to ongoing improvements to the experience. What the extension can do With the MongoDB for VS Code Extension, you get a single unified interface (VS Code) that you already know and love. Within the extension, you can work with your application data from MongoDB side-by-side with your application code for a more streamlined software development experience. Let’s take a look at what you can do with the extension. Connect to MongoDB After you’ve installed the extension , the first thing you’ll want to do is connect to MongoDB using a connection string. If you’re using MongoDB Atlas, you can find your connection string in the Atlas Web UI under the “Database” view by clicking the “Connect” button and then choosing VS Code as your connection option. Data exploration Within the extension, it’s easy to look at your data on MongoDB while working on your code. In the left-hand sidebar, you can easily click through databases, collections, and documents, as well as see relevant schema and indexes. Referencing both schema and indexes here during development can be helpful because: 1. By looking at the schema, you can see what fields you can query on and what their types are, and 2. You can confirm if your query is covered by an index for faster reads against the database. Playgrounds The MongoDB for VS Code Extension gives you a fully-featured JavaScript Playgrounds experience for rapid scripting and prototyping. In Playgrounds you can prototype queries, aggregations, and MongoDB commands with syntax highlighting and intelligent autocomplete. After you write your code, just hit the “play” button or use your favorite keyboard shortcut to instantly see the results of code execution. Within Playgrounds you can: Create new databases and collections Execute Create-Read-Update-Delete (CRUD) operations against your MongoDB database Prototype queries and aggregations using MongoDB’s powerful and expressive Query API Export the syntax for a given query or aggregation to your chosen programming language (including language driver syntax) You can also save Playground files together with your application code and version them in git. This is a great option for documenting all the queries and aggregations your application runs, for scripts that generate or import sample datasets to seed your development clusters, or for scripts that create indexes or define schema migrations. And because Playgrounds use the shell syntax, you can then run them programmatically with the MongoDB Shell. Access the MongoDB Shell Sometimes you just want to run a quick query or command in your terminal rather than using a fully-featured UI. The MongoDB Shell is the perfect tool for these kinds of quick data interactions, and you can access the Shell without ever leaving VS Code. Just right-click on your cluster and select “Launch MongoDB Shell” to get started with the Shell. Terraform If your team uses Terraform, you’ll probably be interested in the MongoDB Atlas Terraform Provider for building with MongoDB. The MongoDB for VS Code Extension gives you access to snippets of code for common tasks you might want to accomplish—including managing your Terraform configuration for Atlas. To use this feature, just open a Terraform file, type atlas , go through the predefined placeholders, and configure your credentials. The MongoDB for VS Code Extension lets you do all of the above - and more. To learn about all the different capabilities of the extension, check out the documentation here . New features Here’s what’s new in the extension now that it’s generally available: Autocomplete support with IntelliSense for using the MongoDB Query API, making it more intuitive to type queries and aggregations for your data on MongoDB Improvements to the Playgrounds experience to make them more reflective of a traditional JavaScript environment, including the ability to integrate them with common tools for the JavaScript ecosystem such as ESLint and Prettier Time series collections can now be created right from Playgrounds You can create column store indexes to support your analytics queries Get started today If you haven’t tried it yet, now is the time to start using the MongoDB for VS Code Extension! To install it, simply search for it in the Extensions list inside VS Code or download it from the VS Code Marketplace . Or if you’re a current user, be sure to check for updates so you get the latest version of the extension and access to the new features that come with it. As you build with the MongoDB for VS Code Extension, feel free to give us feedback on your product experience in the MongoDB Feedback Engine , so we can continue to take the pulse of the community and further optimize the extension for users.
MongoDB Atlas Expands Globally with AWS
We’re proud to announce our global expansion of MongoDB Atlas on AWS (Amazon Web Services) in the Middle East, Europe, and APAC. The launch of regions in the United Arab Emirates (UAE), Zurich, Spain, Hyderabad, and Melbourne expands availability of MongoDB Atlas to 27+ AWS regions around the world. The UAE region is an AWS Recommended Region , meaning it has three Availability Zones (AZ), bringing significant infrastructure to the Middle East. When you deploy a cluster in the UAE, Atlas automatically distributes replicas to the different AZs for higher availability. If there’s an outage in one zone, the Atlas cluster will automatically fail over to keep running in the other two. And you can also deploy multi-region clusters with the same automatic failover built-in. We’re delighted that — as with customers in Bahrain, Cape Town, and more — United Arab Emirates organizations will now be able to keep data in their own country, delivering low-latency performance and ensuring confidence in data locality. UAE customers in government, financial services, and utilities in particular will benefit from this expansion. In addition to the launch in the UAE region, MongoDB Atlas is now available in Zurich and Spain, expanding to our already strong presence in the EMEA and giving our customers the ability to build and run applications with data sovereignty requirements for the region. MongoDB was awarded AWS Marketplace Partner of the Year - EMEA for 2022, and we are committed to continuing to make Atlas easily accessible across the region. Our expansion in APAC is also particularly exciting given the recent momentum of MongoDB Atlas on AWS in the region. Increased availability in India and Australia will help to secure the opportunity for APAC developers to have wider access to build with high performance. Companies like Open Government Products, Bendigo&Adelaide, Cathay Pacific, Dongwha, and Kasikorn will benefit from closer availability zones. We’re confident our developers around the world will appreciate this capability as they build tools to improve citizens’ lives and better serve their local users. Get started with MongoDB Atlas for free today on AWS Marketplace Learn more about MongoDB Atlas on AWS
What's New in Atlas Charts: Suggested Charts, Auto Activation, and Contextual Help
Atlas Charts is the native data visualization tool for quickly and easily analyzing your data in MongoDB Atlas. Today, we’re announcing a collection of updates that further streamline the Charts experience: Suggested charts: a quicker way to build visualizations More contextual help in the chart builder Automatic Charts activation for all project members Suggested charts Charts has always offered a simple UI with an easy to use, drag and drop interface that lets you quickly build charts and visualize your application data. However, we still found that some users could benefit from extra help when building out new charts. Rather than starting from an empty screen where you need to drag appropriate fields into the chart type selected, what if you could simply select an automatically suggested chart, and start applying customization from there? That’s exactly what suggested charts offer. We experimented with this feature late last year and now we have turned it on for everyone! Simply add a chart into one of your dashboards to try it out today. Figure 1: Using the new auto suggested charts in the chart builder. Help button in the chart builder As you might expect, the chart builder is where you do your chart creation. Similar to suggested, last year we experimented with ways to provide more contextual help for users when building new charts. Now, we are surfacing helpful docs articles to educate users on key chart building topics like: filtering, adding fields, selecting the right chart type, and more. Sometimes it can be intimidating to know exactly what chart to use and how to achieve the style and customization you want – the help button in chart builder will make this much easier. Building a chart and have a question? Just click into the Get help button and check out one of our highlighted topics, or choose View all topics to read the main Charts documentation. Streamlining Charts activation We’re constantly looking for ways to help Atlas users with data visualization quicker. So starting with this latest release, when you click into the Charts tab from the Atlas UI, you will automatically be set up to start visualizing your data – no activation required. Additionally, Atlas users browsing collections within a specific cluster, can now more quickly navigate directly into Charts for quick visualization. When viewing a collection, the Visualize your data button, seamlessly opens in the chart builder with the current collection selected as the chart’s data source. Paired with the new suggested chart, users see a list of chart suggestions to quickly and easily build a relevant chart based on their collection data. Note: you may see a “Charts” tab in the collection view instead of the Visualize your data button, as shown below. This is due to an experiment we are currently running. FIgure 3: Seamlessly navigate from an Atlas collection into the chart builder in Atlas Charts. This is a continuation of our effort to optimize the overall Charts experience. Last year we made strides in this area by introducing features like streamlined data sources and org-wide sharing . Keep on the lookout for more Charts features that further simplify your experience visualizing Atlas data across your team. New to Atlas Charts? Get started today by logging into or signing up for MongoDB Atlas , deploying or selecting a cluster, and activating Charts for free.
What's New in Atlas Charts: Schedule Dashboard Reports to Share Data with Your Team
Today, we’re introducing an exciting feature addition for teams using Atlas Charts . Charts project owners can now schedule dashboard reports to be sent via email to keep team members informed about key data. This feature has been heavily requested by some of our largest users as there are many use cases where dashboards may be valuable to your team, but you don’t necessarily want to require anyone to do extra work to access and view data. Enter scheduled dashboard reports in Atlas Charts! In any dashboard that your team relies on for regular data review, simply schedule a dashboard report. The new Schedule button can be found at the top right of the dashboard screen: Once you’ve chosen a dashboard from which to create a report, you will see a variety of options letting you customize the content and frequency of your report before you schedule. A report requires basic fields like a name or subject line, recipient list, and optionally, a message for the body of the email. In addition to a link to the dashboard in Charts, you can choose whether to attach an image or PDF for quick reference in the message itself. Finally, you can set a schedule of daily, weekly, monthly, or quarterly delivery. You can also simply send a single email if you have a one-time need to share a report. And once you’ve set everything up, your email will be sent on your defined schedule. As you use scheduled dashboard reports more and more, we created a Reports page where you can manage all reports in your project. Note that if you’re on an free tier, you can try one scheduled report. If you’re on an M2 cluster or higher, you can create up to 100 reports per project. To learn more, please check out our documentation . We’re always listening to feature requests that will enhance using Charts across teams, so if you have any requests or feedback, please share them with us here . Log in to Atlas Charts today to schedule your first report! If you’re new to Atlas Charts, get started today by logging into or signing up for MongoDB Atlas.
MongoDB Releases “Focus Mode” in Compass GUI
We’re excited to announce an improvement to the aggregation-building experience in MongoDB Compass. Compass already makes it easy to view and manage your MongoDB databases, and with the addition of Focus Mode you now have the option to dial in on specific stages within your aggregation pipeline. Overview MongoDB's Query API and Aggregation Pipelines enable easy retrieval and processing of data from collections. They also facilitate complex operations such as filtering, grouping, and transforming, making computation and analysis effortless. MongoDB Compass' intuitive interface simplifies the process of building aggregations by enabling developers to easily create, test, and refine aggregation pipelines, and the introduction of Focus Mode takes this a step further. When constructing pipelines, having to simultaneously view and consider multiple stages can make it challenging to analyze the impact of a specific stage, leading to increased cognitive load. Now, developers can toggle Focus Mode on stages, opening a view that focuses exclusively on the contents of the specific stage they are working on. This view can also be used to view sample input (before the aggregation stage is applied) and output (after the stage is applied) documents, aiding in the understanding, troubleshooting, and optimizing of the data pipeline. Developers can also switch between different stages by accessing a drop-down menu at the top of their screen. This makes identifying inefficiencies and optimizing performance easier, as well as providing deeper insights from the output documents for data-driven decision making. Focus Mode offers a streamlined and distraction-free environment for working with stages, improving the efficiency and precision of testing, debugging, and analyzing the impact of each stage on the data, ultimately simplifying the creation and management of pipelines. Conclusion The addition of Focus Mode is part of our continued refresh of the query and aggregation experience in Compass. These improvements are made possible thanks to the feedback of our developer community, so we encourage you to try out this new feature and let us know what you think! To learn more about Aggregation Pipeline Builder in Compass, visit our documentation .
Visualizing Your MongoDB Atlas Data with Atlas Charts
MongoDB Atlas is the leading multi-cloud developer data platform. We see some of the world’s largest companies in manufacturing , healthcare , telecommunications , and financial services all build their businesses with Atlas at their foundation. Every company comes to MongoDB with a need to safely store operational data. But all companies also have a need to analyze data to gain insights into their business and data visualization is core to establishing that real-time business visibility. Data visualization enables the insights required to take action, whether that’s on key sales data, production and operations data, or product usage to improve your applications. The best way to do this as an Atlas user is by using Atlas Charts – MongoDB’s first-class data visualization tool, built natively into MongoDB Atlas. Why choose Charts First, Charts is natively built for the document model. If you’re familiar with MongoDB, you should be familiar with documents. The document model is a data model made for the way developers think. And with Charts, you can take your data from documents and collections in Atlas, and visualize them with no ETL, data movement or duplication. This speeds up your ability to discover insights. Second, Charts supports all cluster configurations you can create in Atlas, including dedicated clusters, serverless instances, data stored in Online Archive, as well as federated data in Atlas Data Federation. Typically when you learn about a company’s integrated products and services, you find some “gotchas” or limitations that make any benefits come at a significant cost. In the case of a MongoDB Atlas customer, that could come in the form of someone finding out that a cluster configuration option isn’t supported by Charts. But that will never be the case. If you create and manage your application data in Atlas, you can visualize it in Charts. That’s it. Third, Charts is a robust data visualization tool with a variety of chart types, extensive customization options, and interactivity. Compared to other options in the business intelligence market, you get the same key benefits, without all the complexity. You can learn how to use Charts in a few hours and you can easily teach your team. It’s the simplest data visualization solution for most teams. Fourth, the value of Charts can extend beyond individual use cases, with sharing and embedding . This lets you both flexibly share charts and dashboards with your team, as well as embed them into contexts that matter most to your data consumers, such as in a blog post or inside your company’s wiki. Finally, Charts is free for Atlas users up to 1GB per project per month, which covers moderate usage for most teams. There are no seat-based licensing fees associated with Charts, so no matter how many team members you have, Charts will remain a low-cost, if not zero cost solution for your data visualization needs. Beyond the included free usage, it’s just $1/GB transferred per month. You can check out more pricing details here . How to use Charts The best way to learn how to use Charts is to simply give it a try. It’s free to use and we have a variety of sample dashboards you can use to get started. But let’s walk through some basics to help illustrate the kinds of visualizations that Charts can enable. Charts makes visualizing your data easy by automatically making your Atlas deployments (any cluster configuration) available for visualization. If you’re a project owner, you can manage permissions to data sources in Charts. We could write an entire blog post on data sources, but if you’re just getting started, just know that your data is made easily available in Charts unless your project owner intentionally hides it. Create a dashboard Everything in Charts starts with a dashboard and creating a dashboard is easy. Simply select the Add Dashboard button at the top right of the Charts page in Atlas . From there, you’ll fill in some basic information like a title and optional description, and you’re on your way. Here’s what one of our new sample dashboards looks like. They are a great place to start: Build a chart Once you have a dashboard created, you can add your first chart. The chart builder gives you a simple and powerful drag and drop interface to help you quickly construct charts. The first step is selecting your data source: Once you have a data source selected, simply add desired fields into your chart and start customizing. The example below uses our IoT sample dashboard dataset to create a bar chart displaying the total distance traveled by different users. From there you can add filters and further customize your chart by adding custom colors, data labels, and more. The chart builder even allows you to write, save, and share queries and aggregation pipelines as shown below. You can learn more in our documentation. Play around with the chart builder to get familiar with all of its functionality. Share and embed A chart can be useful in itself to individual users, but we see users get the most benefit out of Charts when sharing visualizations with others. Once you have created a dashboard with one or more charts, we offer a variety of options letting you share your dashboards with your team, your organization, or via a public link if your data is not sensitive. If you would rather embed a chart or dashboard where your team is already consuming information, check out Charts embedding functionality. Charts lets you embed a chart or dashboard via iframe or SDK, depending on your use case. Check out our embedding documentation to learn more. That was just a brief overview of how to build your first charts and dashboards in Atlas Charts, but there’s a lot more functionality to explore. For a full walkthrough, watch our product demo here: Atlas Charts is the only native data visualization tool built for the document model and it’s the quickest and easiest way to get started visualizing data from Atlas. We hope this introduction helps you get started using Charts to gain greater visibility into your application data, helping you to make better decisions on your data. Get started with Atlas Charts today by logging into or signing up for MongoDB Atlas , deploying or selecting a cluster, and navigating to the Charts tab to activate for free.
MongoDB Atlas Integrations for CDKTF are now Generally Available
Infrastructure as Code (IaC) tools allows developers to manage and provision infrastructure resources through code, rather than through manual configuration. IaC have empowered developers to apply similar best practices from software development to application instructure deployments. This includes: Automation - helping to ensure repeatable, consistent, and reliable infrastructure deployments Version Control - check in IaC code into GitHub, BitBucket, or GitLab for improved team collaboration and higher code quality Security - create clear audit trails of each infrastructure modification Disaster Recovery - IaC scripts can be used to quickly recreate infrastructure in the event of availability zone or region outages Cost Savings - prevent overprovisioning and waste of cloud resources Improved Compliance - easier to enforce organizational policies and standards Today we are doubling down on this commitment and announcing MongoDB Atlas integrations with CDKTF (Cloud Development Kit for Terraform). These new integrations are built on top of the Atlas Admin API and allow users to automate infrastructure deployments by making it easy to provision, manage, and control Atlas infrastructure as code in the cloud without first having to create in HCL or YAML configuration scripts. CDKTF abstracts away the low-level details of cloud infrastructure, making it easier for developers to define and manage their infrastructure natively in their programming language of choice. Under the hood, CDKTF is converted into Terraform config files on your behalf. This helps to simplify the deployment process and eliminates context switching. MongoDB Atlas & HashiCorp Terraform: MongoDB began this journey with our partners at HashiCorp when we launched the HashiCorp Terraform MongoDB Atlas Provider in 2019. We then have since grown to 10M+ downloads over all time and our provider is the number one provider in the database category. Today we are delighted to support all CDKTF supported languages including JavaScript, TypeScript, Python, Java , Go, and .NET. In addition, with CDKTF users are free to deploy their MongoDB Atlas resources to AWS, Azure and Google Cloud enabling true multi-cloud deployments. Learn how to get started via this quick demo . Start building today! MongDB Atlas CDKTF integrations are free and open source licensed under Mozilla Public License 2.0 . Users only pay for underlying Atlas resources created and can get started with Atlas always free tier ( M0 clusters ). Getting started today is faster than ever with MongoDB Atlas and CDK for HashiCorp Terraform . We can’t wait to see what you will build next with this powerful combination! Learn more about MongoDB Atlas and CDK for Hashicorp Terraform