In this video, you’ll learn how to generate metrics using log events attributes to filter your logs more effectively and begin monitoring, graphing and alerting on the new metric immediately. Generating metrics from logs is a powerful tool for monitoring attributes which are parsed from your logs.

When 2 years ago Datadog decided to move its infrastructure platform to Kubernetes we didn’t expect to find so many roadblocks, but ingesting trillions of datapoints per day in a reliable fashion requires pushing the limits of cloud computing. Creating and managing dozens of clusters, with thousands of nodes each and operating in several clouds was a challenging but rewarding learning experience. In this episode Ara Pulido, Developer Advocate, will chat with Laurent Bernaille, Staff Engineer at Datadog and part of the team that created Datadog’s Kubernetes platform. We’ll cover the challenges we found creating and scaling Datadog’s Kubernetes platform and how we overcame them.

As a company, Datadog ingests trillions of data points per day. Kafka is the messaging persistence layer underlying many of our high-traffic services. Consequently, our Kafka usage is quite high: double-digit gigabytes per second bandwidth and the need for petabytes of high performance storage, even for relatively short retention windows. In this episode, we’ll speak with two engineers responsible for scaling the Kafka infrastructure within Datadog, Balthazar Rouberol and Jamie Alquiza. They'll share their strategy in scaling Kafka, how it’s been deployed on Kubernetes, and introduce kafka-kit; our open source toolkit for scaling Kafka clusters. You'll leave with lessons learned while scaling persistent storage on modern orchestrated infrastructure, and actionable insights you can apply at your organization

In this session, we start with the basics of SRE, including some common terminology and theory, then dive into practical examples—including lessons learned from our own journey here at Datadog. We discuss the relationship between SRE and DevOps, what success looks like (and how to measure it), and how to identify and nurture both internal and external talent in order to build a cross-functional team. SRE is a large, complex topic, so the session ends with a live Q&A and deep-dive into some great topics.

In this video, you’ll learn how to use tag-based grouping and time aggregation (with the rollup function) to create actionable time-series graphs. Datadog offers various ways to manipulate your metric graphs so that you can create graphs that are specific and actionable for all of your use cases. Two methods of doing this—as explored in this video—are tag-based grouping and time aggregation.

In this video, you’ll learn how to utilize Datadog’s Live Container View to monitor and troubleshoot container performance underlying your applications. Datadog makes it easy to monitor ephemeral, containerized infrastructure. In this video you’ll learn how to leverage Datadog’s Live Container View to effectively dive into your container health. Using this view, you can sort and group your containers by tags or labels imported from Kubernetes, such as container name.

In this video, you’ll learn how to use the Amazon EventBridge integration to send Datadog alerts directly to your event bus and kick off auto-remediation pipelines.

Datadog Security Monitoring allows you to detect threats in real time and investigate security signals across your infrastructure, applications, and network. This video shows you the capabilities and how you can be up and running in just a few minutes.

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.

In part 1 of this 2 part series, you’ll learn how to use API tests to proactively monitor the uptime and performance of your web applications.