Amazon Elastic Container Service (ECS) is a managed compute platform for containers that was designed to be simple to configure, with opinionated defaults to help users get started quickly. ECS customers can run containerized workloads on either Amazon EC2 instances or the serverless Fargate platform without having to maintain a control plane—and can easily integrate ECS with other AWS resources, like Network Load Balancers, to architect their infrastructure.

AWS Lambda extensions enable you to seamlessly integrate third-party tooling with your Lambda environment so you can run custom code or monitoring agents alongside your functions. We’ve partnered with AWS to create a Lambda extension that offers a more cost-effective, simplified process for collecting data from your functions.

Datadog’s infrastructure list provides a central, high-level view of every host in your environment and pulls together metadata and relevant metrics from across Datadog to help you get the full picture of each one. You can easily filter and sort the list using any host tags, letting you quickly view the status of the parts of your infrastructure you need.

Dashboards are a crucial tool in your monitoring arsenal, as they allow you to visualize and correlate telemetry data from across your stack in a single place. Historically, Datadog offered two dashboard types: Screenboards, for pixel-level control on a canvas, and Timeboards, for troubleshooting a specific point in time. Now, we’re excited to introduce a new dashboard layout that combines the best of Timeboards and Screenboards in a single, seamless editing experience.

When Kubernetes launches and schedules workloads in your cluster, such as during an update or scaling event, you can expect to see short-lived spikes in the number of Pending pods. As long as your cluster has sufficient resources, Pending pods usually transition to Running status on their own as the Kubernetes scheduler assigns them to suitable nodes. However, in some scenarios, Pending pods will fail to get scheduled until you fix the underlying problem.

Datadog Notebooks simplify the way teams across an organization find and share knowledge. By bringing together live data and rich Markdown text, Notebooks help teams create powerful, data-driven documents—from runbooks and support playbooks to incident postmortems and data reports. And with collaboration functionalities like real-time editing and commenting, team members can simultaneously make changes to a document and gather feedback along the way.

Your users access your application from a wide range of browsers, which have their own implementations of HTML, CSS, and JavaScript. For instance, many modern JavaScript features such as Promises and Arrow Functions are unsupported by some browsers. These inconsistencies can lead to missing elements and malfunctioning workflows that affect some—but not all—of your user base.

Knowing how to deploy and run applications has become a key part of modern app development, meaning that developers need expertise in a number of areas beyond their core application code. Whether it’s container orchestration, networking, scaling, or load balancing, there is a steep learning curve to being able to deploy and run an application at scale.

Apache JMeter is an open source tool for load testing Java applications in both development and CI environments in order to ensure that sudden spikes in traffic won’t cause latency in production. But because load testing involves sending thousands of requests per minute in order to simulate real traffic, it can be difficult to parse outcomes and read patterns—especially for large organizations that test and deploy new code several times a day.

Your applications rely on third-party software running throughout your infrastructure, and it can be challenging to monitor each of these technologies individually. To give you the visibility you need, Datadog Live Processes now monitors all of your third-party workloads in one place.