Amazon Elastic Container Service for Kubernetes, or Amazon EKS, is a hosted Kubernetes platform that is managed by AWS. Put another way, EKS is Kubernetes-as-a-service, with AWS hosting and managing the infrastructure needed to make your cluster highly available across multiple availability zones. EKS is distinct from Amazon Elastic Container Service (ECS), which is Amazon’s proprietary container orchestration service for running and managing Docker containers.

In Part 1 of this series, we looked at key metrics for tracking the performance and health of your EKS cluster. Recall that these EKS metrics fall into three general categories: Kubernetes cluster state metrics, resource metrics (at the node and container level), and AWS service metrics. In this post, we will go over methods for accessing these categories of metrics, broken down by where they are generated.

In this post, we’ll explore how Datadog’s integrations with Kubernetes, Docker, and AWS will let you track the full range of EKS metrics, as well as logs and performance data from your cluster and applications. Datadog gives you comprehensive coverage of your dynamic infrastructure and applications with features like Autodiscovery to track services across containers; sophisticated graphing and alerting options; and full support for AWS services.

Logging your Java applications is essential to getting visibility into application performance and troubleshooting problems. But, with a variety of available libraries and configuration options, getting started logging in Java can be challenging.

Data drives every decision we make at Datadog. That includes decisions about when to leave the office to catch the train! A few years ago, Datadog engineers created MTAServiceChecker.com to provide ourselves and our fellow New Yorkers with detailed insight into New York’s subway system, the MTA. For a recent Datadog hackathon, Chuck Hagenbuch and I, part of our growing engineering team here in Boston, created a version of the service checker for our local system, the MBTA.

Alibaba Cloud provides a comprehensive suite of cloud computing services to power businesses across the globe. We are excited to announce that our new integration with Alibaba Cloud is now in public beta. While the Datadog Agent has always been able to provide visibility into Alibaba Cloud instances, this new integration now enables you to also monitor the health and performance of Alibaba Cloud services (load balancers, managed databases, and more) in Datadog.

Organizations that depend on distributed systems often write their applications in Go to take advantage of concurrency features like channels and goroutines (e.g., Heroku, Basecamp, Cockroach Labs, and Datadog). If you are responsible for building or supporting Go applications, a well-considered logging strategy can help you understand user behavior, localize errors, and monitor the performance of your applications.

IBM MQ is enterprise-grade message-oriented middleware (MOM). Previously known as MQSeries and renamed to WebSphere MQ, IBM MQ is known for its stability and reliability. Companies in industries ranging from financial services to retail to aviation use it as an integral part of their backend infrastructure. Datadog’s new IBM MQ integration enables users to collect key metrics and logs from their IBM MQ instances and visualize them with a customizable out-of-the-box dashboard.

Amazon DocumentDB is an AWS-managed document database service that supports MongoDB, the well known open source database. As a managed service, AWS automatically handles database management tasks, autoscales database clusters, and backs up your data to S3. DocumentDB implements the Apache 2.0 open source MongoDB 3.6 API, making it easy to migrate your existing MongoDB workloads to DocumentDB.