Arm processors have long been at the center of mobile computing, powering billions of smartphones, tablets, smartwatches, and other IoT devices. Today, these processors are beginning to see broader adoption in the cloud as they promise better performance, higher energy efficiency, and lower costs than their x86-based predecessors. Just this week, Oracle announced its new Oracle Cloud Infrastructure Ampere A1 Compute platform, built on the Ampere Altra Arm processor.

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.

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.

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.

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.

The more tools that your teams need to execute their workflows, the more friction and lost productivity there can be, especially if each tool requires a different CLI or set of APIs. Retool is a low-code platform that allows you to build internal web applications using a drag-and-drop interface. By integrating with a number of key backend databases and APIs, Retool enables you to create custom, centralized management tools to serve a wide range of employee-facing use cases.

A dark launch is a deployment strategy for testing new versions of a service in production. When running a dark launch, you deploy a new version of a service and route a copy of production traffic to it without returning responses to users. This lets you see how a new version of a service handles production load, watch for errors, and compare performance between the old and the new versions—without affecting users.

Cloudflare is a content delivery network (CDN) that organizations across industries use to secure the reliability of their websites, applications, and APIs. With a wide array of security, networking, and performance-management tools, millions of web applications employ Cloudflare’s DDoS protection, load balancing, and serverless compute-monitoring features to maintain high performance and uptime.

Template variables enable you to use tags to filter your Datadog dashboards to the hosts, containers, or services you need for faster troubleshooting. However, there are some cases where it may be difficult to use a standard set of template variables to aggregate all of the data you need without creating a complicated, difficult to manage set of variables. For example, you may use tag values that are a subset of another tag.

Single-page applications (SPAs) provide some significant benefits over multiple-page apps. For JavaScript developers using frameworks like React or Vue, they offer flexibility in moving application logic to the frontend, reducing the need for complex backend operations. For users, SPAs can provide a smooth experience with a highly interactive UI and fewer page loads. But, with increased sophistication, there are some tradeoffs.

In order to manage complex containerized applications, modern devops teams need to have deep visibility into the status of their Kubernetes resources. By listening directly to the Kubernetes API, the open source kube-state-metrics service generates key metrics about your Kubernetes objects, including pods, nodes, and deployments, which are essential for understanding the status and performance of your clusters.

Google Cloud Platform is growing quickly, providing solutions for everything from cloud storage to managed Kubernetes to serverless computing. Since Google App Engine launched in 2008, Google’s suite of serverless products has expanded to help enterprises accelerate application development without having to manage or scale their own infrastructure.

Protecting your applications from abuse of functionality requires understanding which application features and workflows may be misused as well as the ability to quickly identify potential threats to your services. This visibility is particularly critical in cases where an adversary finds and exploits a vulnerability—such as inadequate authentication controls—to commit fraud.

Kubernetes enables teams to deploy and manage their own services, but this can lead to gaps in visibility as different teams create systems with varying configurations and resources. Without an established method for provisioning infrastructure, keeping track of these services becomes more challenging. Implementing infrastructure as code solves this problem by optimizing the process for provisioning and updating production-ready resources.