Preparing for DevOps interviews? 🎯 Found an absolute goldmine: a GitHub repo with 2,500+ interview questions covering you name it: ✅ Docker & Kubernetes ✅ AWS, Azure, GCP ✅ Terraform & Ansible ✅ Jenkins & CI/CD ✅ Python, Linux, Networking ✅ And so much more... Each

Moye Moye for BJP on live debate 🤣🤣 BJP spokie : India's first education minister was uneducated INC spokie : Just once India had an uneducated education min. (Smriti Irani) 🗿🔥 BJP spokie went clueless. Look at him 😭

Hello @nitin_gadkari, can you explain this Beef exporting connection? #IStandWithMukeshMohan

मैं यहाँ से आता हूँ। यह मेरे घर का सबसे बेस्ट कोना है। मेरे पास न कुछ खोने को है और न ही मेरी कुछ पाने की ईच्छा। मतलब एकदम फकड़ फ़क़ीर। आप मुझे गोली मार सकते हैं लेकिन आप मुझे चुप नहीं करवा सकते हैं।

Most DevOps teams don't fail because of bad tools. They fail because of bad culture. You can have the best CI/CD pipeline in the world. But if devs and ops teams don't talk — it's useless. DevOps is 20% tools. 80% people + process. Change the culture first. Tools follow.

💾 Kubernetes Storage Explained (PV, PVC & Volumes) Containers are ephemeral… but your data shouldn’t be 👇 🔹 Volumes emptyDir → temporary storage hostPath → node-level storage configMap / secret → inject config & sensitive data 🔹 Persistent Storage PV (Persistent

Me enjoying a peaceful day → Claude Code AI: 'You've used 90% of your daily limit' → Me: 😭💀"

🌐 DNS & Service Discovery in Kubernetes How do Pods find each other inside a cluster? 👉 DNS does the magic. 🔹 CoreDNS Default DNS server in Kubernetes Resolves service names to cluster IPs 🔹 Service DNS Every service gets a DNS name: my-service.default.svc.cluster.local

Interviewer: If ConfigMaps externalize configuration, why does a small typo there cause CrashLoopBackOff for your whole release?

That’s why I don’t celebrate UPSC results anymore. These are the rogue products of the same UPSC system. This is the same hatemonger who was celebrating Holi by causing nuisance to public. Today, see this radical Hindu’s hate speech by abusing his powers.

Interviewer: If Kubernetes handles scheduling, why do critical workloads sit Pending while low-priority jobs hog the nodes?

Interviewer: If HPA auto-scales on CPU, why does your cluster still melt under real user load but look fine in staging?

Interviewer: If Pods are cattle, not pets, why does a single crashed Pod still take down your entire API in production?

🕸️ Service Mesh in Kubernetes (Istio / Linkerd) As microservices grow, managing communication between services becomes complex. That’s where a Service Mesh comes in. A Service Mesh provides dedicated infrastructure for service-to-service communication. 🔹 Traffic Management

Raid concept in Linux

Kubernetes Concepts Every Engineer Should Know 🚀 • Pod → smallest deployable unit • Deployment → manages Pods • Service → networking for Pods • ConfigMap → configuration data • Secret → sensitive data • Ingress → external traffic routing Master these and Kubernetes

Linux Commands Every DevOps Engineer Uses Daily 🐧 • ls → list files • cd → change directory • grep → search text • top / htop → monitor processes • df -h → disk usage • free -m → memory usage • systemctl → manage services These commands power daily server

Monitoring Tools for Modern Infrastructure 📊 1️⃣ Prometheus → Metrics monitoring 2️⃣ Grafana → Visualization dashboards 3️⃣ ELK Stack → Logs analysis 4️⃣ Datadog → Cloud monitoring 5️⃣ New Relic → Application performance monitoring 6️⃣ Jaeger → Distributed tracing 7️⃣ Loki →

AI Agents are the new development wave. Here are some popular Python libraries powering AI agents 👇 1️⃣ LangChain 2️⃣ LangGraph 3️⃣ LlamaIndex 4️⃣ AutoGen 5️⃣ CrewAI 6️⃣ OpenAI Agents SDK 7️⃣ Google ADK 8️⃣ DSPy 9️⃣ SmolAgents 🔟 Langroid Expect this ecosystem to grow rapidly in 2026.

🐍 Python Libraries Every Developer Should Know 📊 NumPy • Numerical computing • Multi-dimensional arrays • Scientific calculations 📈 Pandas • Data analysis • Data cleaning • CSV / Excel processing 📉 Matplotlib • Data visualization • Charts & graphs These libraries

🐍 Python Libraries Every Developer Should Know 📊 NumPy • Numerical computing • Multi-dimensional arrays • Scientific calculations 📈 Pandas • Data analysis • Data cleaning • CSV / Excel processing 📉 Matplotlib • Data visualization • Charts & graphs These libraries