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- 15%-20% of cluster workloads contain resilience and performance risk, due to lack of resources - On average K8s clusters are 3X over provisioned - 50% of DevOps/SRE time is spent on defining/fixing K8s configs Is your DevOps engineer to blame for your #Kubernetes cluster woes? That sounds expensive, right? 💸 Before you jump to conclusions and consider firing your DevOps engineer, consider these tips to set them up for success: 1️⃣ Gain clarity into your K8s clusters: Understand your current K8s setup to identify optimization opportunities. 2️⃣ Identify resiliency risks: Prioritize and focus on the most important risks. 3️⃣ Set alerts: Receive real-time notifications on performance issues. 4️⃣ Automate tasks: Use automation for scaling, deployment, and resource allocation. 5️⃣ Implement owner-led actions: Encourage team members to take ownership of their services. 6️⃣ Continuous improvement: Regularly review configurations, adapt to changing needs, and iterate. Optimization is an ongoing journey, and with the right strategies in place, your DevOps engineer can help your Kubernetes cluster reach its peak performance. If you are interested in learning how PerfectScale helps you: 🚀 Drop at least 30% in K8s compute costs 🚀 Reduce 90% in MTTR and SLA/SLO breaches (for capacity-related K8s issues) 🚀 Cut time spent on defining/fixing K8s configs by 70% Book a dedicated demo: https://lnkd.in/ggAXj84g or start your free trial here: https://lnkd.in/d_RD3x5Q 🚀 #DevOps #Kubernetes #Optimization #PeakPerformance #ContinuousImprovement

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