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Datadog

How to Import Kubernetes Labels as Tags | Datadog Tips & Tricks

In this video, you’ll learn how to turn Kubernetes node labels and pod labels into tags in Datadog in order to correlate metrics, traces, and logs back to Kubernetes deployments. Using labels for Kubernetes objects—such as pods or nodes—is key to organizing and making sense of your deployments. Datadog can automatically bring your Kubernetes labels from your clusters into the Datadog platform as tags, regardless of whether you’re using on-prem Kubernetes or a cloud-based service such as AKS, EKS, or GKE.

How to Use Browser Tests to Monitor Web App User Journeys | Datadog Tips & Tricks

In part 2 of this 2 part series, you’ll learn how to create Datadog Browser Tests to replicate user journeys and verify both that your web applications are responsive and functioning properly at all times. In part 1 of this series (link), you learned how Datadog’s API tests can be used to check API and website uptime. Datadog Browser Tests take this a step further, allowing you to replicate entire user journeys and transactions through your web applications. This is done with our browser recorder: simply click “Start Recording” and click through your application to record a test.

Introducing template variable saved views for dashboards

Datadog dashboards provide immediate visibility and insight into your environments. Setting template variables enables you to filter your dashboard graphs on the fly to visualize specific sets of tagged objects. Now, with saved views, you can save sets of frequently used template variables in order to easily find the data you most care about with just a few clicks.

How to implement log management policies with your teams

Logs are an invaluable source of information, as they provide insights into the severity and possible root causes of problems in your system. But it can be hard to get the right level of visibility from your logs while keeping costs to a minimum. Systems that process large volumes of logs consume more resources and therefore make up a higher percentage of your overall monitoring budget. Further, log throughput can be highly variable, creating unexpected resource usage and financial costs.

Introducing the Datadog Operator for Kubernetes and OpenShift

As more environments run on Kubernetes—including our own— Datadog has been making it easier to get visibility into clusters of any scale. To minimize load on the Kubernetes API server, the Datadog Agent runs in two different modes. The node-based Agent queries local containers or external endpoints for data, while the Cluster Agent fetches cluster-level metadata from the API server.

Monitor ProxySQL with Datadog

ProxySQL is a MySQL/MariaDB protocol–compliant load balancer and reverse proxy with native support for a range of popular backends including ClickHouse, Amazon Aurora, and Amazon RDS. ProxySQL efficiently distributes queries to your database servers and caches results, improving resource management and boosting database performance. You can also configure ProxySQL for high availability to reduce downtime.

Monitor Sidekiq with Datadog

Sidekiq is a Ruby framework for background job processing. Developers can use Sidekiq to asynchronously run computationally intensive tasks—such as bulk email sending, payment processing, and data importing—to help speed up the response times of their applications. If you’re using Sidekiq Pro or Enterprise, Datadog’s integration helps you monitor the progress of your jobs and the applications that depend on them, all in a single platform.