Operations | Monitoring | ITSM | DevOps | Cloud

OpenShift monitoring with Datadog

In Part 1, we explored three primary types of metrics for monitoring your Red Hat OpenShift environment: We also looked at how logs and events from both the control plane and your pods provide valuable insights into how your cluster is performing. In this post, we’ll look at how you can use Datadog to get end-to-end visibility into your entire OpenShift environment.

OpenShift monitoring tools

In Part 1 of this series, we looked at the key observability data you should track in order to monitor the health and performance of your Red Hat OpenShift environment. Broadly speaking, these include cluster state data, resource usage metrics, and information about cluster activity such as control plane metrics and cluster events. In this post, we’ll cover how to access this information using tools and services that come with a standard OpenShift installation.

Configuring a Custom Agent Check to Run on IoT Devices (Raspberry Pi) | Datadog Tips & Tricks

In this video, you'll learn how to create, configure, and deploy a custom check for your Datadog agent to run on a Raspberry Pi. The results are custom metrics sent into your Datadog account which track your service provider's network speeds over time.

Monitor ECS applications on AWS Fargate with Datadog

AWS Fargate allows you to run applications in Amazon Elastic Container Service without having to manage the underlying infrastructure. With Fargate, you can define containerized tasks, specify the CPU and memory requirements, and launch your applications without spinning up EC2 instances or manually managing a cluster. Datadog has proudly supported Fargate since its launch, and we have continued to collaborate with AWS on best practices for managing serverless container tasks.