How to Compare Metrics in Amazon CloudWatch and Datadog | Datadog Tips & Tricks
In this video, you'll learn how to directly compare values from your Amazon CloudWatch console with metrics presented in Datadog.
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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.
Modifying a Span Using Hooks - an Example in Node.js
Using hooks to add application specific tags to spans in dd-trace-js.
Monitor Cisco Meraki with Datadog
Cisco Meraki provides a range of IT infrastructure devices—like network security appliances, switches, and wireless access points. As your on-prem infrastructure grows and you add potentially thousands of Meraki devices to your network, it becomes a challenge to get visibility across your entire fleet of devices.
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.
Modifying a Span Using Hooks -- an Example in Node.js
Using hooks to add application specific tags to spans in dd-trace-js.
Track and Monitor Datadog Account Usage using Dashboards
How to leverage the datadog.estimated_usage namespace to track usage stats and estimate overages.
Monitoring Kafka performance metrics
Kafka is a distributed, partitioned, replicated, log service developed by LinkedIn and open sourced in 2011. Basically it is a massively scalable pub/sub message queue architected as a distributed transaction log. It was created to provide “a unified platform for handling all the real-time data feeds a large company might have”.Kafka is used by many organizations, including LinkedIn, Pinterest, Twitter, and Datadog. The latest release is version 2.4.1.
Collecting Kafka performance metrics
If you’ve already read our guide to key Kafka performance metrics, you’ve seen that Kafka provides a vast array of metrics on performance and resource utilization, which are available in a number of different ways. You’ve also seen that no Kafka performance monitoring solution is complete without also monitoring ZooKeeper. This post covers some different options for collecting Kafka and ZooKeeper metrics, depending on your needs.
Monitoring Kafka with Datadog
Kafka deployments often rely on additional software packages not included in the Kafka codebase itself—in particular, Apache ZooKeeper. A comprehensive monitoring implementation includes all the layers of your deployment so you have visibility into your Kafka cluster and your ZooKeeper ensemble, as well as your producer and consumer applications and the hosts that run them all.