Intel Granulate blogs: Continuous Profiling
Best Practices for Identifying Bottlenecks in Modern Applications
Maximize your application's performance with these 5 steps to identify bottlenecks to ensure your applications remain at peak performance.
Shared Resources that Contribute to Java Bottlenecks and Profiling Solutions
Discover why the shared resources that cause Java bottlenecks have to be constantly monitored and optimized to ensure that the application...
Golang Profiling: The Basics and a Quick Tutorial
Golang profiling is the process of collecting and analyzing data about the performance of a Go program, and is typically done with the open...
Java Profiling: Key Areas to Profile and 6 Java Profiling Tools
Java profiling is the process of analyzing the performance of a Java application in order to identify bottlenecks and optimize its performance
Java Profiling: Key Areas to Profile and 6 Java Profiling Tools
Java profiling is the process of analyzing the performance of a Java application in order to identify bottlenecks and optimize its performance
Optimizing Python: Why Python Is Slow and 4 Optimization Methods
Python optimization is the process of improving performance of Python programs, despite the inherent disadvantages of the technology.
Continuous Profiling for Python Applications
Read this step-by-step guide to learn how to benefit from continuous profiling and see a Python application example.
Continuous Profiling for Scala Applications
Learn how to use Granulate's continuous profiler to profile your entire server including both the user and kernel stack.
The Scale Trap: How We Reduced CPU Utilization by 80%
This transcript from DeveloperWeek Cloud features R&D Team Lead at Granulate and how his team reduced CPU utilization from 80% to 15%.