Amazon CodeGuru Profiler vs Elastic Universal Profiling

Amazon CodeGuru Profiler collects runtime performance data from live applications and recommends ways to improve performance and find CPU bottlenecks. It is designed for continuous profiling of production applications with minimal overhead. Interactive flame graphs show CPU and latency analysis, including which code paths use the most resources. Machine learning recommendations identify expensive methods and explain their cause, impact, and possible resolution.

The service can detect anomalies in application profiles and, when configured, send an Amazon SNS notification for a new anomaly. It supports Java, JVM languages such as Scala and Kotlin, and Python 3.6 or later. Java and other JVM languages can be profiled for CPU and heap summary; Python profiling covers CPU wall-clock time. Applications may run on EC2, ECS, EKS, Fargate, Lambda, or on premises. The agent can be enabled in JVM applications from the command line or application code and is also used for Lambda applications. An AWS account is required, with IAM permissions controlling access. The agent collects stack traces, not parameter names or values, variable values, or application data.

Elastic Universal Profiling has no write-up on Specifiction yet; its figures are above.