Operations | Monitoring | ITSM | DevOps | Cloud

The more your infrastructure grows, the more likely you are to face a familiar challenge: where to safely store the API keys, passwords, and tokens that power your observability stack. Unfortunately, a common response to this dilemma is to scatter credentials across configurations, making security and management of secrets increasingly complex.

Launch Week Day 3: Introducing Discover Infrastructure Your dashboard looks perfect. APIs responding in 80ms, background jobs processing smoothly, error rates at 0.02%. Everything's green. Then production breaks. "Why is checkout so slow?" "The payment service keeps timing out!" You run kubectl get pods and discover payment-service pods restarting every 3 minutes due to OOM kills. Then you check your database host—CPU at 98% because someone forgot the new ML training job runs there too.

Azure Kubernetes Service (AKS) continuously generates a high volume of telemetry, ranging from node-level CPU and memory usage to request latencies and error rates within individual pods and services. Without a structured monitoring strategy, this flood of metrics can easily become noise, leaving teams blind to early warning signs. Effective monitoring in AKS is about identifying the right signals, correlating them across layers, and acting before they impact application performance or cluster stability.

The promise of large language models (LLMs) brings new performance gains to development teams, sharing information and context to your team. How is this information stored?

This is a guest post by Simon Grimm, founder of Galaxies.dev, a platform dedicated to helping developers master React Native through hands-on courses, expert guidance, and personal support. React Native performance matters more in 2025 than ever before. With the New Architecture now stable and apps competing against lightning-fast native experiences, users expect sub-second load times and buttery-smooth 60fps interactions.