The Impact of API Response Time on Performance: What You Need to Know

This page summarizes the projects mentioned and recommended in the original post on dev.to
Monitoring HacktoberFest Logging Database crash-reporting

Scout Monitoring - Free Django app performance insights with Scout Monitoring
Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.
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InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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  • prometheus

    The Prometheus monitoring system and time series database.

    • Monitoring tools and performance profiling methods are invaluable in identifying performance bottlenecks. These tools provide real-time insights into API behavior, enabling developers to spot inefficiencies and potential issues. There's a range of monitoring tools, including platforms like New Relic, Datadog, and Prometheus that offer extensive performance metrics like response times, error rates, and resource usage. Using these tools, developers can get a comprehensive view of API performance and uncover hidden problems affecting responsiveness.

  • Sentry

    Developer-first error tracking and performance monitoring

    • Monitor and Tune Caching Performance: Continuously monitor caching metrics like hit ratio, eviction rate, and utilization to assess effectiveness. Fine-tune configurations based on observed performance and user behavior to optimize cache use and derive maximum benefit. Tools like Sentry are developing features to help track cache performance.

  • Scout Monitoring

    Free Django app performance insights with Scout Monitoring. Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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