What kind of integrations does Scout support?
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.
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.
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.
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.
Join engineering teams who trust Scout Monitoring for hassle-free performance monitoring. With our 3-step setup, powerful tooling, and responsive support, you can quickly identify and fix performance issues before they impact your users.
