Continuous code profiling is critical for capturing an application’s CPU over time, allowing teams to spot patterns and issues proactively vs. reacting to isolated snapshots from failures. By collecting and storing profiling data continuously, developer teams can visualize trends, correlate spikes or anomalies with code changes, and detect bottlenecks before they escalate. However, traditional profiling solutions can significantly impact production performance by creating additional workload for the application, consuming extra CPU and memory, and persistently collecting large volumes of data.
Coralogix’s Continuous Profiling eliminates this problem by leveraging vendor-neutral eBPF (extended Berkeley Packet Filter) probes together with the OpenTelemetry standard to deliver kernel-level, always-on performance telemetry with less than 1% overhead. These lightweight in-kernel probes capture high-frequency stack traces, CPU cycles, memory allocations, I/O wait times and thread states, all ingested by Coralogix’s OpenTelemetry-compatible collector. The platform then renders this data as interactive flame graphs and time-series charts on the Coralogix platform. Later this year, the company will broaden support to include off-CPU profiling (blocked and scheduling delays), GPU utilization metrics, detailed memory-allocation insights and fine-grained I/O profiling—offering end-to-end visibility across every performance dimension.
“Traditional profiling solutions may provide useful insights, but their invasive and resource-intensive nature often degrades performance,” said Ariel Assaraf, CEO of Coralogix. “With Coralogix Continuous Profiling, we’re giving teams an unprecedented lens into production code paths — automatically and without compromise. By pairing eBPF’s efficiency with Coralogix’s full-stack observability, we are enabling organizations to accelerate root-cause analysis, optimize resources, and cut costs, all in one unified platform.”
Benefits of the new feature include:
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Rapid Deployment – Get up and running in minutes without having to modify application code.
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Performance Optimization: Identify slow function calls within production applications, enabling immediate code optimizations.
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Cost Efficiency: Quickly detect and mitigate resource-intensive processes, directly lowering infrastructure costs.
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Enhanced Troubleshooting: Correlate stack traces with logs and metrics, dramatically reducing incident resolution times.
