Python Performance Monitoring
Scout Monitoring will point you at Python performance problems, pronto. With support for Django, Flask, FastAPI and many other web frameworks and libraries, we have you covered.
Solve memory bloat and n+1 queries in Python
Scout’s Performance Monitoring tool pinpoints and prioritizes Python performance and stability issues, such as N+1 database queries and memory bloat. With Scout’s tracing logic developers can detect the exact line of code causing the performance abnormality, and with detailed backtraces you can fix the issue before customers ever notice. Scout provides actionable insights for your Python application by automatically monitoring memory usage, prioritizing query data by potential time saved, and tracking object allocations to minimize overhead.
Instantly report key Python performance metrics with details on every web endpoint and background job
- Response Time
- Throughput
- Web transactions
- Error Rate
- Deploy tracking
- Python Memory Usage
- Detailed Tracing
- Slow Query Insights
Leverage Database Query Monitoring for Python apps
Scout’s database query monitoring feature helps you identify slow and repeatedly expensive database queries within your Python application. The database feature specifically collects metrics around the database and concisely visualizes only the relevant insights you need to understand how your database performs in relation to your Python app. Connect transaction traces to their corresponding calls to provide better insights into what the query is and where it occurred with the Python database monitoring feature.
Track user-specific issues with custom context for your Python Application
Custom context delivers greater understanding into how and which customer(s) were impacted by a specific Python database query and which developer wrote the code. Establishing custom context enables you to define different values to better understand why a particular database query was slow. Scout also offers a customizable dashboard of custom context parameters and connect them to your slowest web endpoint traces to optimize Python performance based on user experience.
Python Monitoring FAQ
- What kind of performance alerting options do I get with Scout Monitoring?
Scout’s Python Monitoring provides alerting options such as Github, Slack, weekly digest emails and more. For a full list visit our performance alerting options, visit this section of our docs page.
- What kind of integrations does Scout support?
Scout Monitoring supports integrations with PagerDuty, Rollbar, Sentry, Zapier, Github, plus others. Click here for a comprehensive list of our integrations.
- What’s Scout Monitoring overhead like?
Scout’s performance monitoring agent uses just a portion of the resources of existing app monitoring agents while providing higher-fidelity trace details.
- What is the Scout installation process like?
You can start collecting Python Performance insights in just 3 easy steps. Simply install your Python framework’s package/bundle, set a configuration key, and deploy.
- Is it safe to run Scout alongside my current APM library?
Yes, Scout Monitoring can safely run alongside your current APM library.
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