Operations | Monitoring | ITSM | DevOps | Cloud

Datadog

Consul monitoring tools

In Part 1, we looked at metrics and logs that can give you visibility into the health and performance of your Consul cluster. In this post, we’ll show you how to access this data—and other information that can help you troubleshoot your Consul cluster—in four ways: Consul provides a built-in CLI and API that you can use to query the most recent information about your cluster, giving you a high-level read into Consul’s health and performance.

Kubernetes Control Plane monitoring with Datadog

In a Kubernetes cluster, the machines are divided into two main groups: worker nodes and master nodes. Worker nodes run your pods and the applications within them, whereas the master node runs the Kubernetes Control Plane, which is responsible for the management of the worker nodes. The Control Plane makes scheduling decisions, monitors the cluster, and implements changes to get the cluster to a desired state.

Lessons learned from running Kafka at Datadog

At Datadog, we operate 40+ Kafka and ZooKeeper clusters that process trillions of datapoints across multiple infrastructure platforms, data centers, and regions every day. Over the course of operating and scaling these clusters to support increasingly diverse and demanding workloads, we’ve learned a lot about Kafka—and what happens when its default behavior doesn’t align with expectations.

Explore your data in full-screen graph mode

As you navigate through Datadog, you may find that you want to dive into a graph to explore your timeseries data more deeply, or make quick changes to a graph without permanently altering it. To make it easier to explore the data in your graphs, we’re excited to introduce a newly revamped full-screen view for our timeseries graphs. You can now quickly and easily apply functions, navigate through time to find anomalies, and save and share your work.

Monitor IBM DB2 with Datadog

IBM DB2 is a database management system that runs on a wide range of technologies, including Linux, UNIX, Windows, mainframes, and IBM Power Systems. You can use DB2 as a managed service in the cloud or deploy it in a cluster to provide high availability, making it suitable for a wide range of enterprise and customer-facing applications.

Java runtime monitoring with JVM metrics in Datadog APM

Whether you’re investigating memory leaks or debugging errors, Java Virtual Machine (JVM) runtime metrics provide detailed context for troubleshooting application performance issues. For example, if you see a spike in application latency, correlating request traces with Java runtime metrics can help you determine if the bottleneck is the JVM (e.g., inefficient garbage collection) or a code-level issue.