I reveal how Qovery works under the hood
Check out our updated documentation to learn more about how Qovery works.
You will learn:
- What Qovery installs on your infrastructure
- How Qovery uses Kubernetes, Terraform, Helm.
- How Qovery deploys your applications
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Kubernetes success is determined by Day 2 execution, not Day 1 deployment. While migration is a bounded project, maintenance is an infinite loop that often consumes 40% of senior engineering capacity. To protect margins and velocity, enterprises must transition from manual toil to agentic automation that handles scaling, security, and cost.
Day-0 is planning, Day-1 is deployment, and Day-2 is the infinite lifecycle of maintenance. While Day-0/1 are foundational, Day-2 is where enterprise operational debt accumulates. At fleet scale (1,000+ clusters), managing these differences manually is impossible, requiring agentic automation to maintain stability and eliminate toil.
A multi-cluster Kubernetes architecture distributes application workloads across geographically separated clusters rather than a single environment. This strategy strictly isolates failure domains, ensures regional data compliance, and guarantees global high availability, but demands centralized Day-2 control to prevent exponential cloud costs and operational sprawl.
Stop overpaying for Kubernetes observability. Learn how in-cluster monitoring and AI-driven troubleshooting with Qovery Observe can eliminate APM ingestion fees, reduce SRE bottlenecks, and make your cloud costs predictable.
Kubernetes multi-cluster management is the Day-2 operational practice of orchestrating applications, security, and configurations across geographically distributed clusters. Because native Kubernetes was designed for single-cluster orchestration, enterprise platform teams must implement a centralized control plane to prevent configuration drift and manage a global fleet without scaling manual toil.
Achieving zero-downtime deployments on Kubernetes requires more than running multiple pods. It demands a standardized architecture utilizing Pod Disruption Budgets (PDBs), precise liveness and readiness probes, pod anti-affinity, and graceful termination handling. At an enterprise scale, these configurations must be enforced via a centralized control plane to prevent catastrophic configuration drift.
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