AtlasCLI

7 results

Perfect Your CI/CD Pipelines with MongoDB's New GitHub Action and Docker Image for the Atlas CLI

Do you use GitHub Actions for your CI/CD workflows? Or build using Docker containers? If so, you’ll probably be excited to hear that MongoDB has released: 1. An official GitHub Action and 2. A dedicated Docker image for the Atlas CLI. Together, these two releases make it easier than ever to develop applications with MongoDB Atlas. Since MongoDB announced the Atlas CLI at MongoDB World in 2022, it has become one of our most popular tools for building with the Atlas developer data platform. One of the great things about the Atlas CLI is that it not only caters to the individual developer wanting a mouseless terminal experience—it also makes it easy to programmatically manage Atlas resources throughout the entire development lifecycle. With the new releases for the Atlas CLI with GitHub Actions and Docker, you can easily use the Atlas CLI to build with Atlas while still working natively within your preferred CI/CD platforms. Within GitHub Actions, you now have access to a dedicated Action that allows you to seamlessly manage Atlas resources using your favorite Atlas CLI commands. You can use the predefined workflows available or create custom workflows leveraging native Atlas CLI commands. For example, with one of the predefined workflows you can: create a project, set up the Atlas CLI with an Atlas deployment, retrieve your connection string, and tear down your project and deployment. If you use a platform other than GitHub Actions to manage your CI/CD pipelines, or simply use Docker in your toolchain, you can now also use the Atlas CLI by pulling the Docker image with just one command: docker pull mongodb/atlas From there, you can enter an interactive shell to run Atlas CLI commands as you normally would: docker run --rm -it mongodb/atlas bash atlas --help You can also find detailed information in the MongoDB Documentation on how to run Docker in interactive mode or as a daemon (detached mode) for working with the Atlas CLI. Ready to get started? You can find the Atlas CLI GitHub Action in the GitHub Marketplace and the Atlas CLI Docker image on Docker Hub . If you have any feedback on either experience, share your thoughts with us in the Atlas CLI section of the MongoDB Feedback Engine .

November 15, 2023

Ways to Integrate MongoDB Atlas in Your DevOps Processes

MongoDB Atlas - the industry-leading developer data platform integrates all of the data services you need to build modern applications in a unified developer experience. We want to meet you where you are and offer various ways to begin with Atlas and make the most of its features. Starting with the Atlas User Interface is a good initial step. Now what if your requirement is to automate the deployment of Atlas clusters at scale, and by leveraging tools that are already integral to your application ecosystem? Through this blog, we will address this question. We will discuss the programmatic methods for starting with Atlas and deploying Atlas resources and infrastructure according to your specific needs. The tools we provide cover most of the control plane management ( easily deploy, manage, scale) Atlas clusters. Thereby, enabling you to create the building blocks of Atlas such as clusters, database users, projects, Atlas Search indexes, backups, alerts, and more. You can interact directly with the data plane through the command line or programmatically using tools like MongoDB Shell , Compass , language drivers , etc., to work with data and perform CRUD operations. 1. Atlas Administration API: Leveraging your choice of client No matter what your choice of client: be it cURL commands, Postman, Insomnia etc. You can use a client of your choice to directly interact with Atlas through the Atlas Administration API . The Atlas Administration API gives you a RESTful interface to interact with Atlas resources and perform various actions within MongoDB Atlas. Each endpoint represents a specific resource in Atlas ( e.g. cluster). You can programmatically deploy and manage all of the Atlas resources from an administrative standpoint such as creating a cluster, database user, projects, advanced clusters, backups, monitoring etc. All of the tools that we will cover below are built on top of the Atlas Administration API and abstract away the complexities of using the Atlas Atlas Administration API directly. 2. GoSDK Client: A simplified way to get started with the Atlas Admin API One of the mechanisms that simplify the interaction with the API is the availability of SDK (Software Development Kit). If you are a Go developer, the GoSDK client gives you a much simpler experience of getting started with the Atlas Administration API. It also has full endpoint coverage of the Administration API and improves the speed of getting started with the Atlas Administration API. Getting started with the Admin API through the Go SDK client only takes a few lines of code since the SDK includes pre-built functions, structs, and methods that encapsulate the complexity of HTTP requests, authentication, error handling, versioning, and other low-level details. We will be adding SDK support for more languages in the future. Feel free to add feedback on what other languages you would like to see supported. 3. MongoDB Atlas CLI: Simple command-line tool to easily deploy Atlas resources If you prefer to manage your Atlas resources using simple commands in the terminal, the MongoDB Atlas Command-Line Interface (CLI) is your answer. With the Atlas CLI, you can seamlessly manage your clusters, automate database user creation, control network access, and perform various other administrative tasks, all from the command line. You can also script these actions out with the CLI for even easier repeatability. It is available for multiple operating systems, including Windows, Linux, and macOS. It is often used in conjunction with other command-line tools to automate workflows and integrate with CI/CD pipelines. An easy way to get started with the Atlas CLI is through the quickstart . 4. Infrastructure as Code (IaC) integrations: Automating deployment of Atlas using Infrastructure as Code tools There are several advantages of using Infrastructure as Code ( IaC) tools to provision application infrastructure. By treating your infrastructure code similar to your application code, IaC tools offer benefits such as version control, scalability, security, repeatability etc. What if you could easily deploy your Atlas resources using your preferred IaC tools? MongoDB Atlas gives you that flexibility. Whether you're an AWS CloudFormation or a HashiCorp Terraform enthusiast, you can provision and manage Atlas resources using these tools with ease through the integrations we offer: AWS CloudFormation integration: MongoDB Atlas supports three ways to provision resources using AWS CloudFormation The first is by leveraging Atlas resources directly from the CloudFormation Public Registry . We have 33+ resources available today. The configurations are defined in JSON/ YAML and can be executed using the AWS CLI/ AWS management console. If you want a faster way to get started, you can explore our AWS Partner Solutions ( formerly known as quickstarts), which have pre-built Cloudformation templates to help you provision a group of Atlas resources for specific use cases instead of deploying them one by one. And if you are passionate about using languages you are comfortable with such as JavaScript/TypeScript, Python, Java, C#, and Go instead of learning YAML/JSON, you can leverage the AWS Cloud Development Kit (CDK) to deploy Atlas resources. Under the hood, when your AWS CDK applications are run, they translate your code to CloudFormation templates which use the CloudFormation service for provisioning. HashiCorp Terraform integration: If you are already using Terraform as your IaC tool of choice, we have integrations with Hashicorp Terraform as well. There are two easy ways to get started with Hashicorp Terraform By directly provisioning Atlas resources on AWS, Azure, and Google Cloud using the Terraform MongoDB Atlas provider . If you prefer to use your favorite language, e.g. Typescript, Python, C#, Java, Go, you can use CDKTF (Cloud Development Kit for Terraform) , which will allow you to deploy Atlas using Terraform under the hood without knowing the specifics of Terraform’s configuration language 5. Atlas Kubernetes Operator: Use your existing Kubernetes tooling to manage Atlas resources For organizations leveraging Kubernetes for container orchestration, the Atlas Kubernetes Operator provides seamless integration between Kubernetes and MongoDB Atlas. This operator allows you to deploy and manage Atlas resources using your existing Kubernetes tooling, streamlining the process of spinning up and scaling databases alongside your applications. You can manage Atlas in exactly the same way you manage your applications running in Kubernetes. This is done by managing Atlas directly via custom resources in Kubernetes. These custom resources can be created, managed, and stored as the source of truth in your repository. You can then leverage a Continuous Deployment tool of your choice such as ArgoCD to apply them into Kubernetes. Whether you prefer working with the command line, a RESTful API, Kubernetes, or IaC tools, MongoDB Atlas provides a diverse set of tools to help you achieve your automation goals. By embracing these methods, you can streamline your operations, improve efficiency, and pave the way for a more agile and responsive development process. Learn more from our Atlas Programmatic Access documentation page

October 11, 2023

New Intelligent Developer Experiences for Compass, Atlas Charts, Relational Migrator, and Docs

This post is also available in: Deutsch , Français , Español , Português , 日本 . Today, MongoDB announced a range of innovations in its developer data platform, creating new, intelligent developer experiences in familiar tools like MongoDB Compass, Atlas Charts, Relational Migrator, and MongoDB Documentation that radically simplify and accelerate how developers build modern applications. These new experiences provide developers with guided and intelligent assistance for their development processes in: MongoDB Compass: Where developers can use natural language to compose everything from simple queries to sophisticated, multi-stage aggregations. MongoDB Relational Migrator: Where developers can convert SQL queries to MongoDB Query API syntax. MongoDB Atlas Charts: Where developers can use natural language to generate basic data visualizations. MongoDB Documentation: Where developers can ask questions to an intelligent chatbot, built on top of MongoDB Atlas and Atlas Vector Search, to enable lightning-fast information discovery and troubleshooting during software development. Developer time is one of the most precious commodities in any organization, and with business and customer expectations continuing to rise, developers are under increasing pressure to deliver applications quickly. With more intelligent experiences across the MongoDB developer data platform, it is now simpler and easier than ever to build modern applications for virtually any use case. Check out our AI resource page to learn more about building AI-powered apps with MongoDB. Natural Language Queries in Compass Building queries and aggregations is one of the most prominent developer use cases for Compass , MongoDB’s popular, downloadable GUI tool. Compass’ new, intelligent experience allows developers to use natural language to compose sophisticated aggregations to query, transform, and enrich data, reducing the complexity and learning curve to build queries into application code. The new experience is being released in Public Preview in version 1.40.0 and will be rolled out incrementally to users starting today until the end of October. To get started, make sure you have 1.40.0 downloaded on your machine and have access to the feature. Then you can navigate to the Documents tab and click on the Generate Query button in the query bar, which opens a second bar below the standard query bar where you can enter natural language prompts to generate the Query API syntax for you to execute against your data. Be sure to hit the “thumb’s up” or “thumb’s down” button to rate the helpfulness of the query generated. SQL Query Conversion in Relational Migrator Migrations are part of many developers’ journeys with MongoDB. Earlier this summer at MongoDB.Local NYC, we announced Relational Migrator to help teams with these projects, and we’re continuing to make it easier to modernize application code. Many legacy systems have hundreds, if not thousands of SQL queries that must be modernized as part of any migration effort, and that can be a time-consuming, if not daunting task. Now in Private Preview, developers can use Relational Migrator to convert existing SQL queries and stored procedures into development-ready MongoDB Query API syntax. With SQL query conversion, developers can leverage Relational Migrator to eliminate the manual effort of creating MongoDB queries at scale - speeding up migration projects. SQL query conversion is currently available in Private Preview, and access can be requested directly from the latest version of Relational Migrator. Natural Language Support in Atlas Charts Atlas Charts is the best way for developers to visualize Atlas data. By offering an effortless and powerful solution for gaining data-driven insights, Charts empowers developers and the businesses they help scale. What has always been easy is now becoming more intelligent too! Available in Private Preview, a new natural language mode allows developers to visualize their data through a simple language query, for example: “show me a comparison of annual revenue by country and product.” This is just the start. Later this year, natural language support will extend to more complex queries and chart types. Sign up today to try out natural language support for building charts! Stay tuned for more updates from the team and check out our documentation to learn more about what’s supported by natural language during Private Preview! Intelligent Chatbot for MongoDB Documentation Documentation is critical to the developer experience, making it easier to discover product features and capabilities and troubleshoot common challenges during software development. MongoDB is now super-charging your experience with an intelligent chatbot that improves information discovery by surfacing and summarizing the most relevant documentation. Built with MongoDB Atlas and Atlas Vector Search, the chatbot allows you to ask questions in natural language like “How do I get started with MongoDB Atlas?” or “How do I add a new IP address to the IP access list for my Atlas project?” and receive a response with reference articles, code examples, and other relevant information. MongoDB will also be open-sourcing and providing educational materials about how we built the intelligent chatbot, making it that much easier for others in the community to use the power of MongoDB Atlas and Atlas Vector Search to create dynamic and educational experiences for their end users. Data Privacy and Security MongoDB is trusted by some of the world's most security-conscious organizations, who use the developer data platform’s robust data security and privacy controls to manage their most sensitive data assets. To maintain this trust, these new developer experiences will always be transparent about what data is accessed and used, allowing customers to make informed decisions within the boundaries of their unique security, privacy, and compliance concerns. Get Started Today With new, intelligent features that allow developers to interact with their data using natural language in Compass, Relational Migrator, and Charts, as well as an intelligent chatbot for MongoDB Documentation, it’s easier than ever to take advantage of the flexibility and scalability of MongoDB's document data model to build any class of application. If you have feedback on these experiences, you can enter a suggestion in our user feedback portal .

September 26, 2023

Introducing a Local Experience for Atlas, Atlas Search, and Atlas Vector Search with the Atlas CLI

This post is also available in: Deutsch , Français , Español , Português . Today, MongoDB is pleased to announce in Public Preview a new set of features for building software locally with MongoDB Atlas, giving developers greater flexibility and reducing operational overhead throughout the entire software development lifecycle. Developers can now develop locally with MongoDB Atlas deployments, including Atlas Search and Vector Search , using the Atlas CLI , empowering them to create full-text search or AI-powered applications no matter their preferred environment for building with MongoDB. Developers can use the Atlas CLI to set up, connect to, and automate common management tasks from early development through testing, staging, and production. For full-text search use cases, developers can now use the Atlas CLI to create and manage Atlas Search indexes regardless of whether they are working locally or in the cloud. Similarly, developers building applications powered by semantic search and generative AI on MongoDB can now use the Atlas CLI to create and manage local development instances with Vector Search indexes regardless of their development environment. Developer time is one of the most precious commodities in any organization building innovative new application experiences. But all too frequently, developers are burdened with managing repeatable tasks such as setting up development environments. They also often have to wrestle with the cognitive overhead of switching between different user experiences for local versus cloud development, distracting from delivering value. By giving developers the power of Atlas at their fingertips no matter their preferred development environment, MongoDB continues to expand the scope and capabilities of its developer data platform while placing a premium on developer experience. Create a Local Atlas Database Ready to create a local Atlas database, but don’t have the Atlas CLI yet? It’s easy to install with your favorite package manager. To install the Atlas CLI with Homebrew, use the following command: brew install mongodb-atlas In addition to installing via the Homebrew package manager, you can install the MongoDB Atlas CLI via Apt, Yum, Chocolatey, directly downloading the binary, or pulling the Docker image (learn more about our documentation ). You can also download it directly from the MongoDB Download Center . To create a local Atlas deployment with default settings in interactive mode, enter: atlas deployments setup --type local If you want to list your Atlas deployments enter: atlas deployments list If you’re authenticated to Atlas, you will see both your local and cloud Atlas deployments. If you aren’t authenticated to Atlas, you will only see your local deployments. Get Started with Local Atlas Search Building an application with a full-text search feature powered by Atlas Search? If you’re a developer who tends to build and prototype locally, you may be interested in using the Atlas CLI to work with Atlas Search in your local environment. To get started, first, connect to the local deployment on which you’d like to create a Search index: atlas deployments connect Next, you can use the MongoDB Shell to create your Search index. Below you’ll see an example of how to create an Atlas Search index: db.YOURCOLLECTION.createSearchIndex( "example-index", { mappings: { dynamic: true } } ) Then, if you want to run a query you can use the $search stage of an aggregation pipeline. You can learn more about managing Atlas Search indexes in our documentation . Get Started with Local Vector Search If you’re building an application with generative AI or semantic search and MongoDB Atlas, chances are you’ll be interested in our Atlas Vector Search offering. And now with the Atlas CLI, you can work with Vector Search in the cloud and your local environment. To get started with Vector Search locally you can use MongoDB Shell to create a Vector Search index. Notice that this is similar to the Atlas Search example above, except that in this case there is a vector embedding accounted for in search index creation. db.YOURCOLLECTION.createSearchIndex({ "mappings": { "dynamic": true, "fields": { "plot_embedding": { "type": "knnVector", "dimensions": 1536, "similarity": "euclidean" } } } } ) To learn more about running Vector Search queries visit our documentation . Additionally, if you're already familiar with handling your cloud Search indexes using the Atlas CLI, you'll appreciate a fresh set of interactive commands designed to help you efficiently manage Atlas Search and Vector Search indexes both locally and in the cloud: atlas deployments search indexes create From there you can move through an interactive flow that guides you through index creation. For detailed instructions visit our tutorial . Ready to Move to the Cloud? If you’re ready to create an Atlas database in the cloud, that is easy to do with the Atlas CLI. Simply use the following command: atlas deployments setup --type atlas From there, the setup wizard will guide you to: Register for an Atlas account or authenticate to an existing account Create a free MongoDB Atlas database Load sample data Add your IP address to the access list Create a database user and password Connect to the cluster using the MongoDB Shell ( mongosh ) so you can begin interacting with your data To learn more about the Atlas CLI, visit our documentation . And be sure to let us know what you think of the Atlas CLI in our user feedback portal . With the new local experience with the Atlas CLI, it’s easier than ever to work with your data on Atlas no matter your preferred development environment. Get started today with the Atlas CLI as the ultimate developer tool to manage MongoDB Atlas, including Atlas Search and Vector Search, throughout the entire software development lifecycle, from your local environment all the way to the cloud. Head over to our <a href="https://www.mongodb.com/docs/atlas/atlas-vector-search/tutorials/vector-search-quick-start/?tck=ai_as_web to get started with Atlas Vector Search today.

September 26, 2023

MongoDB Gives Users a Simple Way to Install Atlas Kubernetes Operator and Import MongoDB Atlas Clusters via the Atlas CLI

As time to market and rapid innovation get ever more critical to business success, the last thing your team needs is to spend more time than necessary managing infrastructure. In our most recent update to the MongoDB Atlas Kubernetes Operator , we’ve made it even easier to manage Atlas through the same mechanism that your team is using to manage their applications in Kubernetes. The Atlas Operator enables teams to deploy simple yaml configuration to Kubernetes, where the Operator automates the use of the Atlas Admin APIs to make the changes. It's now possible to install the Atlas Operator through a single command via a tool they already have: the Atlas CLI. Additionally, we’ve given users the optional ability to import existing Atlas projects and deployments into management through the Operator, as part of the installation or as a stand alone operation, making it easy to adopt existing Atlas deployments into management through the Operator. Keep reading to learn how your team can automate the installation and import of Atlas projects in order to enable easy self-service use of Atlas for your engineering teams. But first, a little context The MongoDB Atlas Kubernetes Operator enables teams to manage Atlas from within Kubernetes the same way they would any other service in their Kubernetes stack. By doing this, the Operator removes the need for custom scripts and switching between UIs in order to use the two together. Instead, teams are able to manage their Atlas projects, deployments and database users through yaml that can either live in their Kubernetes cluster, or, more commonly, in a repository alongside their other infrastructure as code configuration. Many customers choose to use a deployment tool like ArgoCD or Flux to automate applying those into Kuberentes, where the Atlas Operator picks them up and uses APIs to make the changes to Atlas. All your teams need to worry about is the yaml in their repo! Previously, setting up the Atlas Kubernetes Operator was a multi-step, manual process. First teams had to use Kubernetes tooling to install the Atlas Kubernetes Operator within a Kubernetes cluster. Teams then had to create an API key in Atlas and a corresponding Kubernetes secret required to authenticate the Atlas Kubernetes Operator to Atlas. It was only after all of that work that they could then create a database or import existing Atlas deployments into the Atlas Kubernetes Operators control. While exporting Atlas configuration into Kubernetes was generally a simple process, it still required some manual steps to bridge the Atlas CLI (which offered a compatible export of Atlas configuration) and Kubernetes (where the configuration needed to be imported). Because of this, secrets either had to be exported in plaintext onto the user’s machine, or entered manually later. All of this to say, it was possible… it just wasn't a piece of cake. Enter a more simplified approach Now, it’s easier than ever to get started with Kubernetes-native management of Atlas. First, we’ve made the installation of the Atlas Kubernetes Operator a simpler process by enabling teams to use the Atlas CLI to install the Atlas Kubernetes Operator. Through a single command in the CLI, Atlas users are able to easily install the Atlas Kubernetes Operator into their currently connected Kubernetes cluster. Including the automated creation of an Atlas API key and storing it in a Kubernetes secret for use by the Operator. Additionally, users can now export Atlas configuration for projects, deployments and users directly into Kubernetes, either as part of the install or as a separate operation. This saves users from needing to always having to export to their own machine before applying to Kubernetes, though exporting like this is still available to support GitOps workflows. With these options, it’s much easier for teams to take control of their projects and clusters and manage them through the Atlas Operator. By simplifying the use of the Atlas Kubernetes Operator with these updates, we have significantly reduced the amount of toil that went into getting started with Atlas. Get started with the Atlas Kubernetes Operator today. Head to the MongoDB.local hub to see where we'll be showing up next.

June 28, 2023

MongoDB Announces the New Atlas CLI

We are pleased to announce the release of the new MongoDB Atlas Command-Line Interface (CLI). The MongoDB Atlas CLI is the fastest way to create and manage an Atlas database, automate ongoing operations, and scale your deployment for the full application development lifecycle. The Atlas CLI gives users a streamlined experience for both onboarding and ongoing management of your Atlas database in the cloud. It gives you a unified and powerful control plane to manage and automate tasks around your cloud resources all from a single interface. The Atlas CLI provides helpful guardrails, such as intelligent autocomplete, so you can easily view all available commands and syntax, and reduce time spent looking up commands and fixing errors. And with the ability to automate repetitive management tasks like spinning up or pausing clusters, you can improve developer productivity and optimize your CI/CD pipelines with MongoDB. For new MongoDB Atlas customers, the Atlas CLI gives you the power to get started quickly and streamline the most complex database management jobs. With just two terminal commands, you can start to programmatically manage MongoDB databases, automate user creation, control network access, and much more. To get started using the Atlas CLI, use the following two commands: $ brew install mongodb-atlas-cli This command installs the Atlas CLI via the Homebrew package manager $ atlas setup This command launches an interactive wizard that lets you: Sign up and authenticate to Atlas Create a free forever MongoDB database hosted in the cloud Load sample data Create a database user and password Add your IP address to the access list Connect to the cluster using the MongoDB Shell mongosh In addition to installing via the Homebrew package manager, you can install the MongoDB Atlas CLI via apt-get, yum, and a direct download of installers and binaries. There’s so much more you can do with the Atlas CLI, including creating serverless instances on Atlas, managing Atlas Search indexes, and setting up Atlas Online Archive. To see a list of all the available commands with the Atlas CLI, enter the command $ atlas --help in the Atlas CLI. Take the Atlas CLI for a spin today! You can give us any feedback in UserVoice . To learn more about what you can do with the Atlas CLI, check out the documentation page .

June 7, 2022

Introducing: MongoDB CLI Atlas Quick Start

Expedite your intro to Atlas with MongoDB CLI quick start Atlas is built by developers for developers, and where do developers work? In the terminal. But the terminal can feel like a bit of black box (no pun intended) because there’s often little to no guidance when getting started. Developers are often left jumping in and out of the terminal to visit documentation for next steps and critical commands creating a flawed workflow that’s draining on productivity. But not anymore — The MongoDB CLI Atlas quick start provides a guided, interactive workflow that lets developers work from where they both need and want. The MongoDB CLI Atlas quick start allows you to spin up a fully functional, new cluster on Atlas in minutes without ever leaving your terminal. This guided experience streamlines the set up process in the CLI so you can begin working within Atlas, faster. For more information, check out our MongoDB CLI page and documentation . Demo Watch this short demo from our most recent MongoDB .live event to help you get started. Stay tuned We look forward to sharing more updates with you in the near future! We encourage you to share your suggestions and feedback with us in our CLI feedback engine so we can prioritize working on what helps you work best. Get started with MongoDB Atlas today!

August 30, 2021