Kubernetes observability at scale: cutting the noise in multi-cloud environments
Blog post from Qovery
Traditional Application Performance Management (APM) tools often impose high costs on organizations by charging per-GB ingestion and egress fees, which can become financially burdensome as companies scale. This pricing structure forces businesses to limit data collection, potentially leading to blind spots during outages. Qovery Observe addresses these issues by retaining telemetry data within an organization's cloud infrastructure, eliminating external vendor fees and transforming monitoring expenses into predictable, low-cost storage costs. It democratizes troubleshooting through an integrated platform and AI DevOps Copilot, which allows developers to debug their own services, thereby reducing the Mean Time to Resolution (MTTR) and minimizing reliance on Site Reliability Engineers (SREs). This shift not only reduces costs but also empowers developers by providing them with the tools to resolve incidents independently, ultimately improving overall productivity and efficiency in managing Kubernetes environments.