Kerno provides a codeless instrumentation solution that integrates kernel telemetry with application logic and business context, enabling developers to quickly identify and resolve critical issues in complex distributed systems. By minimizing manual overhead and data costs, Kerno empowers all developers to take ownership of their code's performance without the need for extensive dashboards or custom setups.
Funding
$1.9M 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
Developers often lack real-time visibility into how their code behaves in production environments, leading to delayed issue identification and resolution in complex distributed systems. Traditional observability solutions require manual instrumentation, extensive dashboards, and custom setups, creating overhead and hindering developer ownership.
Solution
Kerno provides a codeless instrumentation solution that integrates kernel telemetry with application logic and business context, enabling developers to quickly identify and resolve critical issues in production. By leveraging kernel-level integration, Kerno eliminates the need for manual instrumentation, SDKs, and sidecars, reducing engineering overhead. The platform correlates issues with change events and telemetry data across cloud, infrastructure, applications, Git, and CI/CD, helping teams determine the source, impact, and ownership of issues. Kerno operates in-cluster, keeping logs and traces with PII securely within the user's infrastructure, and uses smart sampling algorithms to minimize storage and transfer costs.
Target Audience
Kerno targets engineering teams, particularly those building AI-native applications, who need to ship code quickly and confidently without breaking production.
Features
- Codeless instrumentation leveraging kernel-level integration for automatic data collection
- Event-driven data processing to focus on critical issues and reduce noise
- Automatic correlation of issues with change events and telemetry data across various systems
- In-cluster operation to keep sensitive data secure within the user's infrastructure
- Smart sampling algorithms to minimize storage and transfer costs
- IDE integration for real-time production feedback
- Zero-config dashboards for application context and service maps
- Integration with Jira, Linear, and Slack for streamlined workflows