Kubiks provides an AI‑native observability platform that ingests OpenTelemetry data to unify traces, logs, metrics, and errors in a single, correlated view. Its on‑call AI Agent continuously monitors telemetry, automatically detects anomalies, pinpoints root causes, and can generate pull requests with suggested code fixes, while real‑time dashboards and instant search give developers fast insight into performance and cost metrics.
Funding
Funding not disclosed
Founders
Product
Problem
Modern cloud applications generate massive amounts of telemetry—traces, logs, metrics, and errors—yet teams must stitch together multiple tools to correlate data, leading to slow incident detection and high mean time to resolution.
Solution
Kubiks offers an AI‑native observability platform that ingests OpenTelemetry data from the entire stack and presents traces, logs, metrics, and errors in a single, correlated view. The platform automatically enriches each trace with database queries, API calls, LLM usage, and performance metrics, giving engineers full context for debugging. An on‑board AI Agent continuously monitors telemetry, detects anomalies, pinpoints root causes, and can generate pull requests with suggested code fixes before users are impacted. Real‑time dashboards provide customizable visualizations of request volumes, latency percentiles, AI token consumption, and cost metrics. Kubiks integrates with popular Node.js SDKs and frameworks via drop‑in instrumentation, enabling rapid adoption without extensive code changes.
Target Audience
Primary customers are development and SRE teams building microservice‑based applications that require fast, end‑to‑end observability and automated incident remediation.
Features
- OpenTelemetry‑native distributed tracing that captures end‑to‑end request flows across microservices, databases, external APIs, and LLM calls
- Unified correlation of traces, logs, metrics, and errors in a single interface, eliminating tool fragmentation
- AI‑powered on‑call agent that auto‑detects anomalies, performs root‑cause analysis, and creates pull requests with fixes
- Real‑time dashboards showing latency, request volume, database performance, AI token usage, and cost metrics
- Drop‑in instrumentation for Node.js libraries (e.g., Better Auth, Drizzle ORM, Stripe, Redis, Vercel AI SDK) with a single line of code
- Instant search across all telemetry types, returning results in milliseconds
- Integration with source code repositories and cloud providers to provide complete incident context