In line with Granulate, present profiling options require code modifications, and are usually arduous to make use of, resource-intensive, or costly. These issues are intensified in trendy environments, akin to Kubernetes-based environments or huge knowledge workloads, that require steady profiling of knowledge throughout whole clusters and for jobs throughout a number of batches. This typically forces groups to make use of these options just for restricted quantities of time.
Granulate hopes that with its new open-source resolution, these challenges may be eradicated. G-Profiler aggregates profiling knowledge throughout a number of nodes and utility languages, with out requiring modifications to code. This enables groups to establish and optimize efficiency bottlenecks extra effectively, the corporate defined.
G-Profiler is modeled after inner instruments Granulate created for its personal real-time steady optimization resolution. It determined to open supply this venture with a purpose to help the group in addition to improve trade consciousness of computing inefficiencies.
“On this cloud-native age, code profiling is extra essential than ever for bettering utility efficiency, taming cloud prices, and rising margins. The G-Profiler is a really highly effective software that enables growth groups to realize visibility and enhance efficiency,” stated Asaf Ezra, CEO of Granulate. “As a consequence of complexity of implementation and efficiency overhead, many groups couldn’t afford to make the most of such instruments, so we’re releasing the G-Profiler to permit them to reap the advantages of a code profiler with out having to make modifications of their code. This can be a main milestone in our effort to commoditize real-time steady optimization with a purpose to allow hyperscale efficiency and cost-efficiency for all.”
G-Profiler is offered on GitHub, or as a free picture in AWS, Azure, GCP, or the Docker registry.