Python Application
Performance Monitoring

Monitor Python end-to-end application performance - map and track metrics for business transactions - in the most complex, distributed environments.

Monitor your Python applications in real time, drill down into call stacks, correlate transactions traversing your distributed environment, and diagnose performance bottlenecks while running in a live production or development environment. Auto-discovered business transactions, dynamic baselining, code-level diagnostics, and Virtual War Room collaboration ensure rapid issue identification and resolution to maintain an ideal user experience for any Python application, running on-premises or in the cloud. Full support for popular frameworks including Flask, Django, and Pyramid, with APIs to manually instrument code for custom environments.


Get end-to-end visibility into your Python application environment and all the dependencies

  • Automatically discover application topology and interdependencies, correlate and trace key business transactions based on production application behavior

  • Visualize and prioritize the end-to-end business transactions performance, not just the health of the application and infrastructure nodes

Monitor applications at code-level depth with minimal overhead within minutes

  • Get in-depth application monitoring with detailed call graphs, leveraging Automated Code Instrumentation within minutes

  • Easily locate hot spots and slow methods within your application code, and drill down from transaction snapshots

Minimize application downtime with real-time detection of errors and exceptions

  • Detect the errors and exceptions thrown by application components in real time

  • Fix the errors and proactively address the exceptions with policy-based actions with Runbook Automation

Manage performance of heterogeneous databases in context with your Python monitoring

  • Visually understand how database performance is impacting your overall application

  • Diagnose issues and pinpoint the queries causing performance bottlenecks

Understand end-user experiences across the globe with Python performance monitoring

  • Visually monitor your mobile and web user experience across the globe in context with your application performance through a single pane of glass

  • Rapidly identify the offending line of code in Python applications impacting the end user

Correlate your Python monitoring with underlying server infrastructure visibility

  • Understand infrastructure resource consumption in the context of application performance and end-user experience

  • Automatically capture infrastructure snapshots in context with business transactions when performance degrades

In addition to the key features described above, you can enjoy all the other benefits provided by the AppDynamics platform, including AppDynamics University, automated baseline of performance, intelligent alerting and health rules, ease of use, and more.

"It was simple to deploy. It took minutes, literally. On our first proof-of-concept, we saw results within an hour. "

Eric Poon
Director of Operations Analytics, Nasdaq


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What Is Application Performance Monitoring?

Responsible for the performance of your enterprise’s IT operations? Read this guide to find out if you could benefit from application performance monitoring (APM).

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We believe our innovation in business analytics, regional Software-as-a-Service expansion and strong portfolio to drive full-stack innovation contributed to our mention in the report.

The Need for Next-Generation Application Performance Monitoring

Why legacy APM solutions can’t address the needs of complex distributed environments.

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