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Monitoring for Python applications

Performance metrics, distributed tracing, and code-level insight typically in minutes

Simple setup, powerful insights for Python performance

Simple setup, powerful insights for Python performance

See application performance in real-time both within individual service tiers and across entire distributed applications.

Python application performance monitoring tool: Trace and visualize application bottlenecks

https://play.vidyard.com/8uREsLGsJiwoYyZwQWWiB2.jpg

Python application performance monitoring tool: Trace and visualize application bottlenecks

AppOptics provides real-time visibility into any application by collecting both high-fidelity metrics and detailed transaction traces.

  • Out-of-the-box support for dozens of frameworks and libraries in Java, .NET, PHP, and Python
  • Distributed tracing follows requests across processes, hosts, and data centers—no manual instrumentation required
  • Easily leap from visualizing trends to deep, code-level root cause analysis

Python server and infrastructure monitoring: Your key metrics in real-time dashboards

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Python server and infrastructure monitoring: Your key metrics in real-time dashboards

AppOptics removes the divide between application and infrastructure health metrics. Enjoy unified dashboards, alerting, and management.

  • Open integrations based on the Snap and Telegraf ecosystems mean you’re always covered
  • Leverage out-of-the box dashboards or create your own
  • Customize our plug-ins or create your own

Custom metrics and analytics: Amazing application, infrastructure, and business insights

https://play.vidyard.com/HivvaLY17YN4bSaHfAcxuD.jpg

Custom metrics and analytics: Amazing application, infrastructure, and business insights

AppOptics is an extensible custom metrics and analytics platform that ties together your applications, infrastructure, and business metrics.

  • Use multi-dimensional tags to easily filter and group data—dissect your cloud environments in real time to see only data that belongs to certain cloud regions, instance types, availability zones, etc.
  • Define mathematical transformations to perform on a selection of native metrics or time series
  • Compare the past to the present by easily tracking disparities between the same metrics over days or weeks
  • Combine fine-grained measurements sent to the API into a single summary metric

Easily monitor your Python apps

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