Switched from Semgrep OSS to Cloud, but the agent is flaky

backend_perf_guru · 2026-07-29T04:35:55Z

I've been running Semgrep OSS in our CI/CD pipelines for over a year, primarily as a static analysis gate for our Go and Python monorepos. The shift to Semgrep Cloud was motivated by the promise of centralized rule management, the dashboard for tracking findings over time, and the incremental scanning capabilities. However, the operational experience with the Semgrep Cloud Agent has been... inconsistent, to put it mildly. The core issue manifests as sporadic failures during the analysis phase, which our CI system reports as non-zero exits. Crucially, these are not deterministic failures; a re-run of the exact same pipeline, with the same code state, often succeeds. This introduces unacceptable noise into our quality gates. My initial assumption was network latency or timeout to the Cloud backend, but the agent's logging is less than exhaustive. Here is a typical error snippet from a failed run (anonymized paths): ``` [INFO semgrep.agent] Starting Semgrep Cloud scan [INFO semgrep.agent] Found 2 git tracked lockfiles [ERROR semgrep.agent] Scanning failed with code: 2 [INFO semgrep.agent] Agent scan completed with errors ``` Exit code 2 is documented as a "semgrep error," which is unhelpfully broad. Enabling `SEMGREP_VERBOSE=1` sometimes yields more, but not consistently. The failure seems correlated with larger diffs (~50+ files), but I haven't established a strict resource ceiling (CPU/memory). Our agent runs in a Kubernetes pod with resource limits of 1 CPU and 1Gi RAM. My specific questions for the community are: * Has anyone else observed this non-deterministic behavior with the Cloud Agent, and if so, were you able to identify a root cause? I'm particularly interested in whether it's related to: * The agent's internal handling of partial scan state and resumption. * Specific interaction with the Cloud API during findings upload under load. * Underlying `semgrep-core` engine instability when orchestrated by the agent wrapper. * Are there known best practices for agent configuration in resource-constrained CI environments that improve stability? The official documentation is quite sparse on tuning. * As a latency-obsessed engineer, the black-box nature of this failure is frustrating. Has anyone implemented a wrapper script or retry logic that gracefully handles these transient agent failures without masking genuine analysis errors? The value proposition of the Cloud platform is strong, but this operational flakiness threatens to erode team confidence in the tool. We're currently evaluating a fallback to the OSS CLI for blocking scans, using Cloud only for non-blocking monitoring, which defeats much of the purpose. --perf

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grafana_guardian

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29/07/2026 8:12 pm

Exactly the right question to ask. It's often both, which is what makes it so frustrating. You might see a PR fail once, then a rerun on the same commit passes without changes. But the failure can also be *sporadic across repos* if they share a similar resource profile in your CI environment, like memory or I/O constraints during that initial ruleset sync.

The randomness within the same scan comes from external contention on shared runners, while unpredictability across repos usually ties back to unadvertised baseline resource needs.

- GG

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