Introduction

The future of production reliability depends on developer contribution. By making it easier for developers to understand how their code impacts production, we can shift observability from being a reactive, bolt-on program to an integral part of the Software Development Life Cycle (SDLC), moving production intelligence left.

Kerno is a lightweight observability platform engineered for cloud-native engineering teams. It provides the easiest way for developers and on-call engineers to navigate complex systems, identify critical issues, and resolve them independently—without manual instrumentation, steep learning curves, complex configurations, or exorbitant pricing.

Kerno leverages kernel-level integration to collect and correlate issues with key change events and telemetry data across your cloud, infrastructure, applications, Git, and CI/CD pipelines. This enables your team to quickly determine whether an issue is code or infrastructure-related, identify where it started, and assess its impact across your services so you can efficiently notify and align the relevant people.

Kerno then gives developers and on-call engineers the context they need—down to the specific request and the broken line of code—to spot the root cause quickly without manually sifting through uncorrelated logs and dashboards.

What Makes Kerno Different

Developer-Focused with Opinionated Workflows: Kerno does the heavy lifting to provide only the essential data needed to troubleshoot application issues, using opinionated workflows that guide you to the right places to look without unnecessary noise or complexity. It's designed for developers of any experience level, so you don't need to be a power user or systems expert to contribute effectively.

Event-Based Data Collection: Kerno focuses on critical events by collecting data only when something breaks. It correlates and deduplicates information before presenting it, so you don't have to sift through logs, traces, or dashboards.

Easy Installation and Low Maintenance: The Kerno agent gives you complete visibility without requiring SDK integrations, code changes, or application restarts. You won't need to instrument your code now or in the future, eliminating potential blind spots and ensuring consistent monitoring. The agent runs separately from your applications and uses minimal resources.

Data Remains Secure: Kerno keeps all sensitive data within your cluster; no data leaves your infrastructure.

Predictable Pricing: Kerno is priced per unique component monitored, not based on data volume, so you won't encounter surprise bills as you scale.

Zero-Code Instrumentation with eBPF

eBPF (extended Berkeley Packet Filter) enhances the capabilities of the Linux kernel by providing a safe and efficient way to extend kernel functions without modifying kernel code. This technology has fundamentally transformed observability and performance monitoring in modern Linux environments.

Key Benefits of Kerno’s eBPF Agent

• Out-of-the-Box, Language-Agnostic Visibility: By leveraging specific kernel hook points, Kerno offers complete visibility into your applications without needing SDK integration, code modification, or application redeployment.

• Minimal System Footprint: Deployed as a DaemonSet, Kerno’s eBPF agent runs separately from your application, resulting in minimal CPU and memory impact and avoiding unexpected resource overhead on your infrastructure.

• Granular Data Down to the Payload Level: Kerno provides metrics, logs, and traces—including header and payload data for every request.

Stay in Control of Your Sensitive Data

Kerno stores all your sensitive data inside your cluster, ensuring that your sensitive data, contained in logs and traces, never leaves your cluster. This data is pulled to the Kerno portal on-demand using double-blind encryption, so it's never exposed to Kerno or any third parties.

By leveraging AWS S3, Kerno stores this data cost-effectively while maintaining high availability and durability.

Fair and Predictable Pricing

Kerno’s architecture enables Kerno to offer a fair, transparent, and predictable pricing model based on the number of monitored components. Data volumes don't affect your subscription price so that you can scale your monitoring without unexpected costs.