DEVOPSdigest

Granulate announced the release of a new Kubernetes filters feature to the company's gProfiler.

gProfiler is an open-source production profiling solution that measures the performance of code in production applications to facilitate computing optimization, improve code quality, and save on computing costs. Granulate's gProfiler empowers R&D and DevOps teams to maximize their applications' performance, improve the quality of their code and reduce cloud costs – all with simple installation and no code changes.

With the launch of the newest feature, users of gProfiler are now able to filter services based on Container name, Hostname, or Kubernetes deployment object by simply selecting the resolution level within the platform. With these native Kubernetes filters, users can deploy gProfiler once on the entire cluster, and profile down from the deployment to pod level without having to deploy a profiler for each one of these objects. This allows teams to investigate the behavior of different deployments, pods, nodes, and hosts across different regions and code versions with a single profiler deployed.

"We've had a tremendous response from the DevOps community to the added value gProfiler provides them around application performance, investigating bottlenecks, and inefficient code, including numerous requests for additional features, particularly for Kubernetes, which led us to develop this latest version," said Asaf Ezra, Co-Founder and CEO of Granulate. "The new feature is part of our ongoing mission to commoditize continuous profiling and increase awareness of the potential for performance optimization and lower costs across all industries."

Granulate's gProfiler provides several benefits for development and software engineers managing production applications including a simple setup with no code changes, low overhead with less than 1% utilization penalty, and wide coverage for Java, Go, Python, Scala, Clojure, Kotlin, Node.js, Ruby, and PHP.

gProfiler is available as a free open-source package from GitHub, or via the free public image in AWS, Azure, and GCP, or the free container image in the Docker registry.