Tech-Gen

 🚀 30 Days Windows Server 2016 Interview Series 🔹 Day 23 – Performance Tuning & Optimization A good System Administrator does not just fix problems — they optimize performance before issues happen. Performance tuning questions are common in L2/L3 and System Admin interviews 👇 Q1. What is Performance Tuning? 👉 The process of improving server speed, stability, and resource usage. Q2. Which tools are used for performance monitoring? 👉 Task Manager, Performance Monitor, Resource Monitor, and Event Viewer. Q3. What causes high CPU usage? 👉 Heavy applications, background services, or malware. Q4. What causes high memory usage? 👉 Memory leaks, excessive applications, or insufficient RAM. Q5. How do you identify disk bottlenecks? 👉 Check disk queue length and disk latency in Performance Monitor. Q6. What is Performance Baseline? 👉 A record of normal system performance used for comparison. Q7. How can you optimize server performance? 👉 Remove unnecessary services, update drive...

 Kubernetes Kubelet Architecture — Explained Simply 🧠 This diagram shows what actually happens inside a Kubernetes Node. Flow: 1️⃣ API Server    → Sends PodSpec (desired state) 2️⃣ Kubelet Main Loop    → Continuously reconciles desired vs actual state 3️⃣ Pod Workers (Parallel)    → Handle pod lifecycle independently 4️⃣ CRI Layer    → Kubelet → CRI → Container Runtime (containerd / CRI-O) 5️⃣ Image Manager    → Pulls & garbage-collects images 6️⃣ Volume Manager    → Mounts / Unmounts volumes 7️⃣ PLEG    → Detects container state changes 8️⃣ Status Manager    → Sends Pod status back to API Server      (IP, Phase, Conditions) Core Concept: Kubelet is a reconciliation engine. It constantly ensures: Desired State = Actual State That’s how Kubernetes achieves self-healing.

 31 Open Source Projects Every DevOps Engineer MUST Know 1. Coolify: self-host your apps with a Heroku-like experience on your own VPS. https://github.com/coollabsio/coolify 2. Nextcloud: private file storage, collaboration, and team productivity stack. https://github.com/nextcloud/server 3. n8n: automate APIs, alerts, and workflows without writing glue code. https://github.com/n8n-io/n8n 4. Taubyte: deploy event-driven functions globally at the edge. https://github.com/taubyte/tau 5. PocketBase: lightweight backend with auth, database, and realtime in one binary. https://github.com/pocketbase/pocketbase 6. Dokku: deploy apps with git push on a single server. https://github.com/dokku/dokku 7. Appwrite: full backend server with auth, database, storage, and functions. https://github.com/appwrite/appwrite 8. Supabase: Postgres-based backend with auth and realtime APIs. https://github.com/supabase/supabase 9. Postiz: AI-powered social media scheduling platform. https://github.com/gitro...

 Terraform Made Simple: Day 4: Data Sources & Locals In Day 3 of this Terraform series, we learned how variables make configurations flexible. But Terraform configs often need two more things: - Fetching existing infrastructure data - Computing reusable internal values That’s exactly where Data Sources and Locals are used. 1. Data Sources:  A Data Source lets Terraform read information from your cloud provider without creating anything. Instead of manually looking up values (like an AMI ID or VPC ID), Terraform can query the provider and fetch it automatically. Common use cases: - Get the latest AMI ID - Fetch an existing VPC or subnet - Read information about already created resources Example: data "aws_ami" "example" - This tells Terraform to query AWS and return the latest AMI that matches the filter. - That value can then be used directly in your resources. - So instead of hardcoding an AMI ID, Terraform dynamically retrieves it for you. 2. Locals: Locals ar...

 Terraform Made Simple: Day 3 - Terraform Variables After learning the basics, it's time to understand Terraform variables. Variables are important because we don’t want to hardcode values directly in our configuration. Instead, we define variables and pass values when needed. This makes our Terraform code flexible, reusable, and easier to manage across different environments. Let's see how it works- 1. What are Terraform Variables? Variables act as customizable inputs that remove the need for static, "hard-coded" values in your files: > Parameterize Configurations: Use placeholders for values like regions or instance types. > Accept Values at Runtime: Pass data into your code from various sources when you run Terraform. > Enable Reusability: Allow the same configuration to be passed into different modules or environments. 2. Types of Variables & Values: There are three main ways to handle data within your project: > Input Variables: Accept values from...

 Terraform Made Simple: Day 2 - Terraform Providers Welcome to Day 2! Today it’s time to talk about Terraform Providers. If the terraform {} block is the foundation, Providers are the functional plugins that allow Terraform to communicate with external platforms. 1⃣ What is a Provider? A Provider is an interface plugin that translates Terraform configuration (HCL) into specific API calls for a target platform:  ➜ It contains the code required to manage resources for a specific cloud or service. ➜ It allows Terraform to interact with hundreds of platforms, including AWS, GCP, Azure, GitHub, and Kubernetes. ➜ It carries out the actions needed to create, update, or delete your infrastructure. 2⃣ Types of Providers: Providers are categorized based on who maintains and supports them: ➜ Official: Managed and supported directly by HashiCorp. ➜ Verified: Maintained by the platform itself (e.g., AWS or Azure) and verified by HashiCorp. ➜ Community: Open-source options developed and mai...

 Terraform Made Simple: Day 0 - FOUNDATION Let's lay the foundation: What is Terraform, why use it, and how does it work?  1. What is Terraform?  ➔ It is an Infrastructure as Code (IaC) tool created by HashiCorp. ➔ It uses a declarative configuration language (HCL). This means you simply define the goal (what you want to build), and Terraform figures out the steps to get there. ➔ It actively manages the full lifecycle of your resources from creation to destruction. 2. Why do we use it?  ➔ Speed & Repeatability: Instead of manually clicking through cloud consoles, you can spin up identical, error-free environments (Dev, Staging, Prod) in minutes using the same code. ➔ Version Control & Collaboration: Because your infrastructure is just text files, you can store it in Git. Teams can track history, review changes via Pull Requests, and instantly roll back mistakes. ➔ State Management & Locking: Terraform keeps a State file, which is a memory of exactly what ...

 Terraform Made Simple: Day 1 - The terraform { } Block Welcome to Day 1! Now that we know what Terraform is, let’s look at the very first thing Terraform reads: the Configuration Block. This block is used to set the technical requirements and global settings for your project. 1. Purpose of the Block:  The terraform {} block is a special top-level block used for global settings. It is used to configure the Terraform engine: - It defines the required version of the Terraform CLI. - It specifies which providers (AWS, Azure, etc.) and versions are needed. - It tells Terraform where to store its "memory" (the State file). 2. Core Components:  > (required_version): This ensures everyone on your team is using the same version of Terraform (e.g., ~> 1.6.0). This prevents "it works on my machine" errors caused by syntax differences between versions. > (required_providers): Here, you list the plugins Terraform needs to download. You define the source (where to get i...

 Most asked Kubernetes interview question: Explain services in Kubernetes and which you use ? Read it for simple explanation: 👇 - Pods in Kubernetes are temporary. - They get created, destroyed, and replaced anytime. - So how do apps connect reliably? 👉 Services. A Service provides a stable endpoint to access a group of Pods even when Pod IPs change. ⚙️ 4 Main Kubernetes Service Types: 1️⃣ ClusterIP (Default) • Internal IP • Accessible only inside the cluster • Used for service-to-service communication Example: Backend API → Database 2️⃣ NodePort • Exposes the Service on each Node’s port • Access via: NodeIP:NodePort • Common for testing & demos Example: Access app in browser using node IP 3️⃣ LoadBalancer (imp) • Creates a cloud load balancer (AWS / Azure / GCP) • Provides public IP • Used for production workloads Example: Public web application 4️⃣ ExternalName • Maps Service to external DNS • Connects Kubernetes apps to external services Example: External database Why Serv...

   Docker 101: Building Container Images🐳 I prepared a skill path that helps you learn Dockerfile authoring from the ground up, starting with the simplest possible image and building up to production-grade multi-stage builds. You'll learn how to: - Build and publish a container image to a registry - Write Dockerfiles using core instructions: FROM, COPY, RUN, and CMD - Handle application and system-level dependencies in a Dockerfile - Compile and build applications inside a Dockerfile - Inspect container image internals (layers, sizes, digests) - Optimize images with multi-stage builds to produce smaller, cleaner production artifacts By the end of this skill path, you'll be comfortable writing Dockerfiles for real-world applications and understand how to keep your images lean and efficient. Happy building! 🛠️

 Kubernetes in Plain English (Made Simple) Kubernetes can feel overwhelming at first: Pods, Deployments, Services, Ingress, RBAC, etc.. Here are the core concepts explained simply: 🔹 Pod → Smallest unit. Runs your app.   🔹 Deployment → Keeps the right number of Pods running.   🔹 StatefulSet → For stateful apps like databases (stable identity + storage).   🔹 Service → Stable IP/DNS to access Pods.   🔹 Ingress → Internet entry point (HTTP/HTTPS routing).   🔹 DaemonSet → Runs one Pod on every node (e.g. monitoring/logging).   🔹 ConfigMap → Non-sensitive configuration data.   🔹 Secret → Sensitive data (passwords, tokens).   🔹 Namespace → Logical separation (dev/test/prod).   🔹 Node → Worker machine (e.g. EC2 instance in EKS).   🔹 Control Plane → Brain of the cluster.   🔹 RBAC → Permission system. 💡 Think of Kubernetes like a building:   Pods = App rooms...

VMware Virtual Machine Files Explained When you create or run a virtual machine in vSphere, it isn’t just a single file—it’s a collection of files that together define the VM’s configuration, state, and data. Each file has a specific purpose, and understanding them helps with troubleshooting, backup, and advanced administration. 1. .vmx – Configuration File This is the heart of the VM. The .vmx file contains all the configuration details: CPU count, memory size, device mappings, network adapters, and storage references. It’s essentially the blueprint of the VM. While you can technically edit it with a text editor, it’s safer to modify settings through the vSphere Client to avoid corruption. 2. .vmxf – Supplemental Configuration This file stores additional configuration data, often related to VM teams or extended features. It’s not as critical as the .vmx, but it complements it by holding metadata that vSphere uses for advanced setups. 3. .vmdk – Virtual Disk Descriptor The .vmdk file d...

  📦 OVA vs OVF  📦 OVA vs OVF 🔹 OVF (Open Virtualization Format) Definition : OVF is an open standard for packaging and distributing virtual appliances. Structure : It consists of multiple files: .ovf  → Descriptor file (XML-based, defines VM hardware, metadata, and requirements) .vmdk  or other disk files → Virtual machine disk images .mf  → Manifest file with checksums for integrity .cert  (optional) → Digital certificate for authenticity Purpose : Designed for interoperability across different virtualization platforms (VMware, VirtualBox, etc.). Benefit : Flexible, transparent, and easy to inspect or customize since files are separate. 🔹 OVA (Open Virtual Appliance) Definition : OVA is a single-file distribution format that  packages OVF  into one archive. Structure : A  .ova  file is essentially a  TAR archive  containing: The  .ovf  descriptor Disk image files ( .vmdk ) Manifest and optional certificate Purpos...

  🔷 vSphere Fault Tolerance (FT) – Detailed Explanation In VMware vSphere , Fault Tolerance (FT) provides continuous availability for virtual machines by eliminating downtime during host failures. Unlike HA (which restarts VMs after failure), FT ensures zero downtime and zero data loss . 🔹 1️⃣ What is vSphere FT? vSphere FT creates: Primary VM (Active) Secondary VM (Shadow copy) Both run simultaneously on different ESXi hosts . If the primary host fails: ✔ Secondary VM immediately becomes active ✔ No reboot ✔ No service interruption ✔ No transaction loss This is called Continuous Availability . 🔹 2️⃣ How FT Works (Architecture) Components Involved: ESXi Hosts (minimum 2) Shared Storage (SAN / vSAN / NFS) vMotion network FT Logging network (very important) vCenter Server Process Flow: VM powered ON FT enabled vSphere creates a secondary VM CPU & memory execution state is mirrored in real time All instructions are log...

  🔷 VMware vSphere – Affinity, Anti-Affinity Rules & Admission Control (Detailed Explanation) These features are critical in enterprise cluster design to ensure availability, compliance, performance, and predictable failover capacity . 🔹 1️⃣ Affinity & Anti-Affinity Rules (DRS Rules) These are DRS cluster rules that control how VMs are placed across ESXi hosts. They ensure workload placement aligns with business, licensing, and availability requirements. ✅ A. VM–VM Affinity Rules 🔹 What It Does: Forces selected VMs to run together on the same host . 📌 Use Cases: Multi-tier applications needing low latency (App + Middleware) Application server tightly coupled with backend Licensing tied to single host execution 🧠 Example: Web Server + App Server must stay on same host for performance. DRS ensures: ✔ Both VMs move together during migration ✔ They restart together after HA failover ❌ B. VM–VM Anti-Affinity Rules 🔹 What It Does: Forces sele...