Integrates into development and CI workflows to automate performance measurement, detect regressions, and provide actionable optimization insights. By using high-precision tracing and commit-level differential flamegraphs, it ensures consistent metrics and prevents performance degradation before code is deployed. This reduces manual debugging, keeps release schedules on track, and helps teams meet SLAs with confidence.
Funding
$120K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Software performance regressions often go undetected until code is deployed, leading to unexpected downtime, poor user experiences, and missed SLAs. Manual performance checks are time-consuming and prone to inconsistencies, diverting developers from building new features. Existing performance monitoring tools often lack the precision needed to pinpoint the exact source of performance changes at the commit level.
Solution
CodSpeed is a continuous benchmarking platform that automates performance measurement within development and CI/CD workflows. By integrating directly into existing development processes, CodSpeed detects performance regressions early, enabling developers to optimize code before deployment. The platform uses high-precision tracing and commit-level differential flamegraphs to isolate performance changes with less than 1% variance. This allows development teams to maintain consistent metrics, prevent performance degradation, and ensure every merge meets performance standards. CodSpeed supports multiple languages, including Rust, Python, Node.js, and C++, and integrates with popular CI platforms like GitHub, GitLab, and Buildkite.
Target Audience
CodSpeed is designed for engineering teams, DevOps engineers, and software developers who want to proactively manage software performance and prevent regressions in their applications.
Features
- Automated performance regression detection integrated into CI/CD pipelines
- High-precision tracing data collection with noise filtering
- Commit-level differential flamegraphs for pinpointing performance changes
- Support for Rust, Python, Node.js, and C++
- Integrations with GitHub, GitLab, and Buildkite
- Less than 1% result variance for consistent and reproducible metrics
- Performance monitoring across the entire codebase
- Merge blocking to prevent performance degradation