Intel’s cloud performance tool is Continuous Profiler, open-source software announced on March 11, 2024. It continuously samples CPU activity and combines profiler data in a unified flame graph, helping teams locate hot code paths and performance regressions in cloud-native services. Intel says it can be deployed across a Kubernetes cluster without code changes.
What is Intel Continuous Profiler?
Continuous Profiler is an open-source CPU profiling tool developed by Intel Granulate and contributed to the open-source community. It evolved from gProfiler and brings multiple sampling profilers into a single flame-graph view. It is software for investigating application performance, not a hardware-monitoring product.
Intel announced the tool on March 11, 2024. The announcement describes profiling as a way to help developers identify code bottlenecks and improve application efficiency. Intel Granulate general manager Asaf Ezra said the profiler helps businesses identify bottlenecks in their code and optimize applications.
How does it work?
Rather than requiring teams to manually instrument every suspected function, Continuous Profiler uses sampling profilers to observe where CPU time is spent. It presents the combined results as a flame graph, a visual representation intended to make CPU-heavy code paths easier to spot. Teams can use that view to investigate issues such as excessive garbage collection, deadlocks, and regressions.
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The value of the graph is diagnostic: it points engineers toward code consuming CPU, which can help them investigate throughput limits, latency, and resource use. A profile is evidence about sampled CPU activity; by itself, it does not establish the root cause of every latency or service-health problem.
How does it work with Kubernetes?
Intel describes Kubernetes-aware filters that let an operator narrow an investigation across deployment, pod, node, and host levels, including across regions. This makes it possible to start with a service or deployment and focus on the relevant underlying workload or infrastructure without running a different profiler for each object.
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Intel says Continuous Profiler can be deployed cluster-wide within minutes and supports multiple programming languages. Those are Intel’s product claims; the announcement does not provide a detailed language matrix, deployment steps, or a measured setup benchmark.
Can you profile production containers without changing code?
According to Intel, Continuous Profiler does not require code changes and is designed for continuous use in cloud-native environments. That makes it relevant for production diagnosis: teams can look for CPU hot spots or changes in runtime behavior without adding instrumentation to each application first. Operators still need to deploy and configure the profiling software in their environment; “no code changes” does not mean “no setup.”
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Is Continuous Profiler free or paid?
Intel describes Continuous Profiler as open-source software. The announcement does not state a price or specify licensing terms, nor does it establish whether a hosted or commercially supported edition is available. The tool is also compatible with Intel Granulate’s continuous-optimization services, which are a separate broader offering; that compatibility does not by itself show that using the open-source profiler requires a paid service.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How does it fit with Intel’s other performance tools?
Intel’s software catalog also lists gProfiler, Intel PerfSpect, and Intel VTune Profiler as performance-related tools. Continuous Profiler is specifically presented as a cloud-native continuous profiling workflow built around sampling and a unified flame graph. The available announcement does not provide a feature-by-feature comparison with those other tools, so teams should compare their deployment model, supported workloads, analysis workflow, and licensing independently before choosing.
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