Our journey behind the observability scenes ends with continuous profiling, the intermittent data collection of which offers a unique tradeoff between the quality of the information available and minimal overhead.
Let’s continue our journey behind the observability scenes, explore the extends and limits of a deterministic stack, and understand how continuous profiling can fit into this landscape.
Embark on a journey behind the scenes to discover the different ways of collecting observability data and converting it into actionable information.
Blackfire’s continuous profiler dashboard opens new performance improvement possibilities. Let’s learn how to navigate through flame graphs, and table views to pinpoint performance bottlenecks and optimize your code.
Our Top Transactions Breakdown feature charts the progression of the most influential transactions of your application, enriching Blackfire users’ comprehension of the context at play.
Blackfire for PHP and Python relies on a deterministic approach to observability. Let’s explore what this means and discover how it compares to a probabilistic one and how both could shape the future of observability.
In the second part of this mini-series, we’ll delve into the intricacies of defining a test boilerplate that could help us get started on setting up long-lasting control over the performance of an existing application.
Stepping into an unknown application landscape with the mission to improve its performance can be daunting. Discover how Blackfire is all about turning measurement into performance optimization, ensuring your next steps are driven by data.
Managing your application’s growth requires adaptability. Stay in the driver’s seat and discover how to align your Blackfire subscription and usage with your expanding needs.
Kickstart your continuous observability strategy with a 360 overview of your applications’ health. Blackfire Monitoring allows you to prioritize performance optimization by providing actionable insights based on aggregating key metrics.