The MongoDB for VS Code Extension Is Now Generally Available

Shelby Carpenter
August 8, 2023

As of today, the MongoDB for VS Code Extension has been downloaded one million times! A huge thank you to all the developers who build with MongoDB and VS Code. We look forward to working with you to continue to improve the extension. Two million downloads, here we come!

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.

← Previous

Three Most Common Developer Skill Gaps Impacting Your Business

When we survey IT leaders about what's holding them back from adopting modern data platforms like MongoDB, skill gaps are a commonly cited top reason. And from our experience, most teams don't even realize that these skill gaps exist in the first place. The past few years have been a time of rapid change for developers, with teams looking to simplify their architecture and increase agility to build smarter apps that meet the needs of their users. To meet these demands and keep up with technology advancements like event-driven architectures, in-app analytics, and now AI, organizations have begun to look towards transformation and modernizing their legacy systems. It's critical that when organizations do these transformations, they bring their people along with them. But according to Deloitte Insights , that doesn’t always happen. They reported only 30% of workers feel supported by their company’s skill development opportunities. Figure 1: Dissatisfaction with professional development investments The skills developers are equipped with are widening from what companies require, creating a skill gap and creating risk in their businesses — leading to increased costs through performance, productivity, and security issues. To help companies close these skill gaps, MongoDB’s Instructor-Led Training team created a tool called MongoDB Skill Scanner . This tool has helped companies across industries to identify skill shortages and create data-driven training programs to improve MongoDB proficiency, increase productivity, and reduce risk and errors. Skill Scanner also helps save time and money spent on training by making these programs extremely efficient. Now that several hundred developers at a variety of organizations have used Skill Scanner, we have early data on 3 of the most common skill gaps in developers that your team should be looking out for (and providing upskill opportunities for). Skill gap #3: Aggregation The third most common skill gap identified through MongoDB Skill Scanner is aggregation . An aggregation pipeline consists of one or more stages that process documents: Each stage performs an operation on the input documents. For example, a stage can filter documents, group documents, and calculate values. The documents that are output from a stage are passed to the next stage. An aggregation pipeline can return results for groups of documents. For example, return the total, average, maximum, and minimum values. Lack of knowledge on aggregations severely limits the type of queries that developers can create with MongoDB. This means developers end up creating more logic in the application server instead of the database server making applications become harder to maintain. So what does this mean for your business? A skill shortage in this area can cause slow applications and operations by increasing the hardware size, which also creates more expenses for your team. Aggregation pipelines, especially for non-JavaScript back-ends, may seem complex at first, but with native mapping in each driver, this takes processing capabilities to the next level, without having to leave your usual language. Skill gap #2: Indexes and optimization Indexes and Optimization are the second most common skill deficit we see among developers. When an application is slow, teams will jump into action trying to diagnose what the problem might be. A common missed step is taking a step back and re-evaluating their indexing strategy, which is a fundamental element of managing any database. MongoDB supports a wide variety of index types and language-specific sort orders to support complex access patterns. Understanding how to create the right indexes for your data structure (and when to remove unnecessary indexes) is crucial for efficient query operations. A lack of knowledge in indexing and optimization can lead to a variety of technical issues including: Lack of indexes, leading to slower queries Excess or redundant indexes, which impact write performance and disk consumption These issues are a common culprit to rising TCO and slower applications. Skill gap #1: Security Lastly, by far the most common developer skill gap we saw from Skill Scanner results is Security. This is also one of the most costly errors a team can make. Compliance with security regulations avoids expensive audit findings and greatly reduces risk. Insufficient knowledge of proper security measures may lead to: Non-compliance with industry regulations resulting in fines and legal penalties Outages or disruptions, leading to downtime Reputational damage Data loss or breach Ensuring developers know the basics of the applied security best practices ensures that no one accidentally opens up security loopholes. Identifying team skill gaps Before jumping into upskilling the team, it’s critical to understand where your team stands and what skills areas they need to improve on so that not only can you close the gap, but close it in a productive, data-driven way. MongoDB Skill Scanner asks a series of multiple choice questions and then provides you with a clear understanding of each individual’s level of expertise across a set of technical skills that are critical for success working with MongoDB in their role. To get started with MongoDB Skill Scanner, contact our team here to retrieve access for yourself or your team. Closing the skill gap Instructor-Led Training empowers teams through highly relevant training content, delivered live by expert instructors to maximize productivity and equip developers and DBAs with the skills they need to succeed — leading to higher employee retention, a better user experience, and reduced errors and inefficiencies. Instructor-Led Training has courses for all skill levels and roles, meaning your team only learns what they need when they need it. We have multiple training delivery methods to match your organization's needs including Private Training (classes are delivered on your schedule, onsite or remotely), Public Training (remote-only and open to the public), and Precision Learning Programs (white-glove MongoDB training initiatives with individualized learning plans). For more information on course details, learning paths, and training schedules, view our Training Catalog . If you're interested in trying out MongoDB Skill Scanner or want to explore the MongoDB Training programs further, you can reach out to your account representative or contact us directly.

August 7, 2023
Next →

MongoDB Database Observability: Integrating with Monitoring Tools

This post is the final in a three-part series on leveraging database observability. Welcome back to our series on Leveraging Database Observability! Our previous post showcased a real-world use case highlighting how MongoDB Atlas’s observability tools effectively tackle database performance challenges. Whether you’re a developer, DBA, or DevOps engineer, our mission is to empower you to harness the full potential of your data through our observability suite . Integrating Atlas metrics with your central enterprise observability tools can simplify your operations. By seamlessly working with popular observability tools, our approach helps teams streamline workflows and enhance visibility across systems. Integrating MongoDB Atlas with third-party monitoring tools MongoDB’s developer data platform combines all essential data services for building modern applications within a unified experience. Our purpose-built observability tools for Atlas environments offer automatic monitoring and optimization, guiding diagnostics tailored specifically for MongoDB. Additionally, we extend Atlas metrics into your existing enterprise observability stack, enabling seamless integration without replacing your current tools. This creates a consolidated, single-pane view that unifies Atlas telemetry with other tech and application metrics, ensuring comprehensive visibility into both database and full-stack performance. This integration empowers you to monitor, receive alerts, and make data-driven decisions within your existing workflows, driving greater efficiency. Below is a quick guide to modifying integration settings through the Atlas UI and the popular integrations we support: Navigate to the Project Integrations page in Atlas. Choose the organization and project you want to configure from the navigation bar. On the Project Integrations page, select the third-party services you’d like to integrate. Configure the chosen services with the required API keys and regions. Critical integrations for your observability platform With Atlas’s Datadog and Prometheus integrations, you can send critical MongoDB metrics to these platforms, empowering detailed, real-time monitoring. Through Datadog , you can track database operation counts, query efficiency, and resource usage, ideal for pinpointing bottlenecks and managing resources. Similarly, Prometheus enables you to monitor essential metrics like query times, connection rates, and memory usage, supporting flexible tracking of database health and performance. Both integrations facilitate proactive detection of issues, alert configuration for resource thresholds, and a cohesive view of Atlas data when visualized in Grafana. Atlas’s integration with PagerDuty streamlines incident management by sending metrics like performance alerts, billing anomalies, and security events directly to PagerDuty. This integration records incidents automatically, notifies teams upon alerts, and supports two-way syncing, ensuring resolved alerts in Atlas are reflected in PagerDuty. It enables efficient incident response and resource allocation to maintain system stability. With Atlas integrations for Microsoft Teams and Slack, you can route key metrics—such as query latency, disk usage, and throughput—to these channels for timely updates. Teams can use these insights for real-time performance monitoring, incident response, and collaboration. Notifications through these platforms ensure your team stays informed on database performance, storage health, and user activity changes as they occur. Use case: Centralized observability with MongoDB Atlas, Datadog, and Slack Let’s walk through a hypothetical scenario for ShopSmart, an e-commerce company that leverages MongoDB Atlas to manage its product catalog and customer data. As traffic surges, the DevOps team faces challenges in monitoring application performance and database health effectively. To tackle these challenges, the team leverages MongoDB Atlas’ integration with Datadog and Slack, creating a powerful observability ecosystem. Integrating MongoDB Atlas with Datadog: The team pushes key MongoDB Atlas metrics into Datadog, such as query performance, connection counts, and Atlas Vector Search metrics. With Datadog, they can visualize these metrics and correlate overall MongoDB performance with their other applications. Out-of-the-box monitors and dedicated dashboards allow the team to track metrics like throughput, average read/write latency, and current connections. This visibility helps pinpoint bottlenecks in real time, ensuring optimal database performance and improving overall application responsiveness. Setting up alerts in Datadog: The team configures alerts for critical metrics like high query latency and increased error rates. When thresholds are breached, Datadog instantly notifies the team. This proactive approach allows the team to address potential performance issues before they impact customers. Integrating Datadog with Slack: To ensure fast communication, alerts are sent directly to the dedicated Slack channel, “ShopSmart-Alerts.” This integration fosters seamless collaboration, enabling the team to discuss and resolve issues in real-time. With these integrations, ShopSmart’s engineering team can monitor performance quickly and address issues efficiently. The unified observability approach enhances operational efficiency, improves the customer experience, and supports ShopSmart’s competitive edge in the e-commerce industry. By leveraging MongoDB Atlas, Datadog, and Slack, the team ensures scalable performance and drives continuous innovation. Conclusion MongoDB Atlas empowers developers and organizations to achieve unparalleled observability and control over their database environments. By seamlessly integrating with central enterprise observability tools, Atlas enhances your ability to monitor performance metrics and ensures you can do so within your existing workflows. This means you can focus on building modern applications confidently, knowing you have the insights and alerts necessary to maintain optimal performance. Embrace the power of MongoDB Atlas and transform your approach to database management—because your applications can thrive when your data is observable. And that wraps up our Leveraging Database Observability series! We hope you learned something new and found value in these discussions. Sign up for MongoDB Atlas , our cloud database service, to see database observability in action. To dive deeper and expand your knowledge, check out this learning byte for more insights on the MongoDB observability suite and how it can enhance your database performance.

November 14, 2024