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Datadog

Monitor ProxySQL with Datadog

ProxySQL is a MySQL/MariaDB protocol–compliant load balancer and reverse proxy with native support for a range of popular backends including ClickHouse, Amazon Aurora, and Amazon RDS. ProxySQL efficiently distributes queries to your database servers and caches results, improving resource management and boosting database performance. You can also configure ProxySQL for high availability to reduce downtime.

Monitor Sidekiq with Datadog

Sidekiq is a Ruby framework for background job processing. Developers can use Sidekiq to asynchronously run computationally intensive tasks—such as bulk email sending, payment processing, and data importing—to help speed up the response times of their applications. If you’re using Sidekiq Pro or Enterprise, Datadog’s integration helps you monitor the progress of your jobs and the applications that depend on them, all in a single platform.

Monitor Windows containers on Google Cloud with Datadog

Many organizations already use Docker to containerize their Windows applications and often run mixed Windows and Linux container environments to support complex architectures. With Kubernetes’s support for deploying clusters with Windows nodes, organizations can leverage the orchestration platform to easily automate container provisioning, networking, scaling, and more for their Windows applications.

Identifying EC2 Right Sizing Opportunities for Cost Optimization | Datadog Tips & Tricks

In this video, you’ll learn how to identify right sizing opportunities for your EC2 instances utilizing Datadog metric dashboards. Optimizing your cloud footprint for cost efficiency can be a huge task, especially for large and scaling environments. Utilizing time series data and toplists, Datadog dashboards allow you to see chronically underutilized EC2s in your AWS environment. Template variables allow you to sort EC2s by teams and instance types, so you quickly identify the scope of cost saving opportunities across your organization.

Monitor Confluent Platform with Datadog

Confluent Platform is an event streaming platform built on Apache Kafka. If you’re using Kafka as a data pipeline between microservices, Confluent Platform makes it easy to copy data into and out of Kafka, validate the data, and replicate entire Kafka topics. We’ve partnered with Confluent to create a new Confluent Platform integration.

NodeJS Instrumentation - Adding Custom Tags to Spans | Datadog Tips & Tricks

In part 1 of this 4 part series, you’ll learn how to use manual instrumentation to add additional detail to traces. We’ll add new tags, or attributes, to the spans generated by our NodeJS application, allowing for more insightful data visualizations in App Analytics.

NodeJS Instrumentation - Creating Custom Spans for Method-Level Visibility | Datadog Tips & Tricks

In part 2 of this 4 part series, you’ll learn how to instrument your NodeJS application to capture custom method-level spans, allowing visibility into how specific methods behave in your application. Flame graphs allow for deep insight into the performance of your code. During instrumentation, we can capture custom spans for deeper layers of visibility in the resulting flame graphs. In this video, we use instrumentation to capture a method-level span, allowing us to see the performance of that specific method in our flame graphs in the Datadog UI.

NodeJS Instrumentation - Adding Analyzed Spans for Improved Data Analytics | Datadog Tips & Tricks

In part 4 of this 4 part series, you’ll learn how to add Analyzed Spans to your traces to open up even more data search and aggregation capabilities via App Analytics. In this video, we will walk you through how you can turn any span into an Analyzed Span. Analyzed Spans function like the root spans of a trace, allowing us to turn the tags embedded in them into facets for advanced data aggregation and searching in App Analytics. You can check out how to add tags to spans—and how to utilize them in App Analytics—in our first video of the series here (link to the first video).