Operations | Monitoring | ITSM | DevOps | Cloud

Not every workload should scale on CPU. Qovery brings event-driven autoscaling into the application lifecycle, letting applications scale on real signals like queue depth or request latency.

A slow CI/CD pipeline costs more than just time. Developers context-switch while waiting for builds, feedback loops stretch longer, and compute costs add up with every inefficient run. Most teams know their pipelines could be faster, but optimizing configurations requires deep knowledge of caching strategies, parallelism, and resource allocation. The challenge compounds with AI-assisted development. As AI coding assistants help teams ship code faster, pipelines run more frequently.

d function there, and before long you’re navigating a codebase full of inconsistent patterns, repeated logic, and code that’s harder to maintain than it should be. Refactoring is essential, but finding the time to clean up code while shipping features is a constant challenge. The rise of AI-assisted development has accelerated this tension. AI coding assistants help teams ship features faster, but they don’t always produce consistent code.

Fed up with Openshift's weight? Compare alternatives that offer Kubernetes power without the enterprise overhead and complexity.

We are continually enhancing our offering to support enterprises looking to modernize without the pain of modernization. We partnered with IBM to bring our highly flexible cloud application platform to the IBM Cloud Marketplace to give financial service organizations a cloud option that meets both workload and organizational requirements.

Have you ever watched a “temporary” Infrastructure as Code script quietly become mission-critical, undocumented, and owned by someone who left the company two years ago? We can all related to a similar scenario, if not infrastructure-specific, and this is usually the moment teams realise the build vs buy IaC decision was made by accident, not design.

The Argo ceiling is a predictable scaling challenge, not a failure of Argo CD or GitOps. As clusters and teams grow, visibility, governance, and orchestration fragment without a control plane. Script-heavy workflows and manual processes slow delivery and increase risk at scale. A GitOps control plane enables unified visibility, structured workflows, automated guardrails, and secure secret management. GitOps has become the default model for deploying applications on Kubernetes.

Kubernetes cost overruns usually come from small, invisible scheduling decisions—not the platform itself. Over-provisioned requests, poor bin packing, and fragmented node pools quietly waste cloud spend. Cost-aware scheduling, right-sizing, and smarter node selection can deliver major savings without hurting performance. Treat cost as a first-class metric with visibility into why scaling decisions happen—not just when.