Datadog APM allows any portion of your code to be instrumented, helping you uncover performance bottlenecks. Under this solution we will help you integrate Datadog APM into your Python application.
Your Python application will be integrated with Datadog libraries on local and Datadog statsd so that you are able to see a flame graph helping you identify key application bottlenecks. A contributor from the team will work with you to create code patches/PRs/MRs to your codebase to help you effectively utilize Datadog APM within your application.
Note: Depending on how your application is deployed on prod this may require a different setup. For example: If you deploy on AWS EC2 the Datadog setup required for the deployment may be different, if you are deploying on AWS Fargate it may be different. For this reason, this solution is scoped to setting up Datadog for a local Python/Django application. After the local integration if you are satisfied we can work with you to extend the contract to integrate this to prod.
Datadog APM (Application Performance Monitoring) and Continuous Profiler gives deep visibility into your applications with ability to create performance dashboards for web services, queues, and databases to monitor reque
While Datadog is a great tool, integrating it into your application can be time consuming. We have experience integrating Datadog with Python applications so that you can focus on the key functionalities of your software