When Kubernetes components like nodes, pods, or containers change state—for example, if a pod transitions from pending to running—they automatically generate objects called events to document the change. Events provide key information about the health and status of your clusters—for example, they inform you if container creations are failing, or if pods are being rescheduled again and again. Monitoring these events can help you troubleshoot issues affecting your infrastructure.

By storing copies of your content in geographically distributed servers, content delivery networks (CDNs) enable you to extend the reach of your app without sacrificing performance. CDNs lessen the demand on individual web hosts by increasing the number and regional spread of servers that are able to respond to incoming requests for cached content. As a result, they can deliver web content faster and provide a better experience for your end users.

Twingate is a network access platform that enables customers to deploy a zero trust authentication layer with their infrastructure as code (IAC) provider of choice. Using this model, you can program strict access control rules that can be updated and co-deployed alongside changes to your infrastructure. Each time a user establishes or closes a connection to a resource, Twingate documents the event with details such as the port, the volume of data transferred, and user identification.

A foundational component of monitoring Google Cloud environments with Datadog is our Google Cloud Platform integration. This integration continuously collects metrics from all of your Google Cloud services and enriches them with tags, enabling you to scope dashboards and monitors to the relevant resources and seamlessly pivot across logs, metrics, and traces inside the Datadog platform.

NetFlow is a network protocol that enables devices to report key traffic flow data such as origin, direction, and overall volume.

GitLab is a DevSecOps platform that helps engineering teams automate software delivery. Using GitLab, teams can easily collaborate on projects and quickly deliver application code with robust CI/CD, security, and testing features. Datadog’s GitLab integration enables you to monitor your GitLab instances alongside the rest of your infrastructure by collecting GitLab metrics, logs, and service checks.

With the growing utilization of AI, modern business applications rely more and more on machine learning (ML) models. But the complexity of these models poses significant challenges to data scientists, engineers, and MLOps teams seeking to maintain and optimize performance.

Classless Inter-Domain Routing (CIDR) is the dominant IP addressing scheme in the modern web. By enabling network engineers to create subnets that encapsulate a set range of IP addresses, CIDR facilitates the flexible and efficient allocation of IPs in virtual private clouds (VPCs) and other networks.

When you first onboard to a monitoring and security platform, it can be difficult to know where to start. Which services should you monitor? What thresholds should you set? How often should you alert your team, and where’s the best starting point for investigations?

As a new Datadog customer, your top priority is figuring out how to maximize the platform’s potential and deliver value to your organization quickly and seamlessly. But with a plethora of options and configurations available at your disposal, it can be overwhelming to determine where to begin. With Datadog, you don’t need to be an expert in observability or monitoring to get up and running efficiently.

Testing enables you to proactively identify and resolve issues before they break critical functionality in your application, which is essential to ensuring an optimized user experience (UX). However, if you don’t know how users are actually interacting with your application, key user journeys may go untested. This lack of visibility can lead to a proliferation of unoptimized features in your UI, causing users to drop off before completing important actions.

Rising container usage has fueled a growing reliance on container orchestration systems such as Kubernetes, EKS, and ECS. As organizations increasingly opt to run these systems in the cloud, their cloud spend tends not only to grow but also to become more opaque due to the dynamic complexity of these environments. Typically, various services, teams, and products share cluster resources, and as nodes are added and removed, those resources continuously shift.

The dynamic nature of cloud costs can make it difficult to fully understand your cloud spend and embrace cost ownership at all levels of your organization. To establish cost governance, FinOps teams need a complete view of cloud costs, including allocation by team, service, and product. And DevOps teams need to detect, investigate, and quickly mitigate unexpected costs to minimize overruns, even as they continue to build features and operate their services.

Datadog provides you with a comprehensive and highly customizable platform for monitoring the performance and security of your applications. Through Datadog components deployed in your environment—including the Agent, tracing libraries, and Observability Pipelines workers—you can easily configure monitoring across your hosts and services, regardless of the particular technology you’re using.

Developer, SRE, IT, and security teams often perform complex and error-prone processes in response to disruptions and changes in their systems. Relying on these processes requires a significant amount of time switching between tools to gather the relevant context needed for remediation, domain expertise, and the manual execution of tasks for incident management—which can significantly prolong disruptions and downtime.

Modern continuous integration (CI) practices enable development teams to quickly and efficiently build and deploy application code to a shared codebase. However, deploying new code is typically accompanied by tests, and as the codebase expands, this results in a proportionately larger test suite.

Datadog dashboards and notebooks can be powerful tools for troubleshooting, enabling you to analyze telemetry from across your stack with visualizations customized by service owners, data analysts, and engineers. Many organizations also rely on dashboards and notebooks for key business processes, such as generating reports, creating postmortems, and managing SLOs. This makes it important to keep track of any unintended changes that may result from others accessing your content.