Khushbu Tiwari

Jenkins Pipelines: Modern Automation for Modern Engineering In today’s fast-moving IT landscape, engineering teams cannot afford delays, manual errors, or inconsistent deployments. That’s exactly where Jenkins Pipelines continue to prove their value, even in 2025. Over the last few years, the evolution of Jenkins—from freestyle jobs to declarative pipelines—has transformed how organisations approach CI/CD. Pipelines now offer version-controlled automation, tighter governance, and repeatable workflows that scale across global teams. For senior engineers, the biggest shift is how pipelines have become collaborative engineering assets, not just DevOps tools. With code-based configuration, teams can now: 🔹 Standardise build and deployment processes across microservices 🔹 Improve traceability through Git-driven pipeline definitions 🔹 Integrate QA, security scanning, and compliance checks directly into CI/CD 🔹 Automate rollbacks, notifications, and environment-specific deployments The trend is clear: modern IT ecosystems demand automation-first engineering, and Jenkins remains one of the most adaptable tools in the market. Its flexibility with plugins, extensibility through shell scripts/Groovy, and seamless integration with AWS, Kubernetes, Docker, and ServiceNow make it extremely relevant for enterprise support and cloud transformation roles across the EU region. As organisations in Europe push for faster delivery, stronger security, and reliable release cycles, Jenkins Pipelines continue to serve as a critical backbone for modern DevOps and production support practices. ⸻ Your Turn How have Jenkins Pipelines shaped your development or support workflows? Have you adopted declarative, scripted, or hybrid models? Share your thoughts—your experience might help someone across the globe. ⸻ #Jenkins #CICD #DevOps #CloudEngineering #Automation #SoftwareEngineering #TechJobsEurope #EUJobs #NetherlandsJobs #IrelandJobs #PolandJobs #RelocationJobs #OpenToWork #ApplicationSupport #EngineeringLeadership

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#day96 The Hidden Workings of Java’s Object Class The Object class in Java is the root class of the class hierarchy. Every class implicitly inherits from Object unless explicitly stated otherwise. All classes in Java inherit from java.lang.Object. In Java, object memory allocation involves several steps: Class Loading: The JVM loads the class definition into memory. Object Creation: When new is called, the JVM allocates memory for the object on the heap. Field Initialization: All fields are set to default values (e.g., 0 for int, null for objects). Constructor Execution: The constructor initializes fields as specified. Reference Assignment: The reference variable points to the object's memory address. Common Object methods include: toString(): Returns a string representation of the object. equals(Object obj): Checks if two objects are equal. hashCode(): Returns a hash code for the object. getClass(): Returns the runtime class of the object. clone(): Creates and returns a copy of the object (if Cloneable). finalize(): Called by the garbage collector before object destruction. notify(), notifyAll(), wait(): Used for thread synchronization. The JVM manages memory using the heap for objects and the stack for references and method calls. Garbage collection automatically frees memory when objects are no longer referenced #JVM #ANDROID #jvm_internal #java #android_automotive #androidautomotive #androidmiddleware #android_os #android_internals Author: Sairamkrishna Mammahe - Seeking Opportunities in Android OS Development

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🎯 Page Fault and Page Swapping A Page Table Entry (PTE) contains the frame number where the page is stored in RAM along with several control bits such as: • Present Bit • Dirty Bit • Reference Bit • Protection Bits Present Bit (Valid Bit) The present bit indicates whether the page is currently loaded in physical memory. • Present Bit = 1 • Page is already in RAM • MMU translates the logical address into a physical address • Physical address = Frame Number + Offset • CPU accesses memory without delay • Present Bit = 0 • Page is not in RAM • Page resides in secondary storage (disk / swap space) • MMU cannot complete address translation • A Page Fault is triggered Page Fault Handling When a page fault occurs, the operating system pauses the running process and starts the page fault handling procedure. • The OS first checks if the memory access is valid. • If the access is invalid, the program is terminated with a segmentation fault. • If valid, the OS locates the required page in disk swap space. ⸻ Loading the Page • If a free frame is available, the OS loads the page from disk to RAM. • The page table entry is updated and the Present Bit is set to 1. • The interrupted instruction is then restarted. ⸻ When RAM is Full If there is no free frame, the OS performs Page Replacement. • A victim page is selected using algorithms like: • FIFO • LRU • Clock Algorithm ⸻ Role of Dirty Bit Before replacing a page, the OS checks the Dirty Bit: • Dirty Bit = 0 → Page not modified → Discard directly • Dirty Bit = 1 → Page modified → Write back to disk first ⸻ Final Step • The new page is loaded into RAM • Page table is updated • The program resumes execution This movement of pages between RAM and disk is called Page Swapping. ⸻ Performance Issue Too many page faults lead to Thrashing, where the system spends more time swapping pages than executing instructions. To reduce this, systems use: • Efficient replacement algorithms • TLB (Translation Lookaside Buffer) for faster address translation. #OperatingSystems #MemoryManagement #Paging #VirtualMemory #PageFault #PageReplacement #OSConcepts #ComputerArchitecture #EmbeddedSystems #SystemsProgramming #TechLearning #EngineeringConcepts #LearnInPublic #SoftwareEngineering #ComputerScience

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🔥 Toughest DevOps Interview Questions Series for Serious Engineers 🚀 ❓ Interview Question How do you handle secrets management in a CI/CD pipeline? 💡 The Real Answer Secrets are sensitive, dynamic, and critical. Hardcoding or exposing them breaks security instantly. Proper management ensures secure, auditable, and automated access. Secrets should never be stored in plain text or in code repositories. ⚠️ Common Secrets Management Mistakes Failures happen when: Secrets are committed to source control Access is shared manually across teams Rotation is infrequent or nonexistent Secrets are stored in environment variables without protection ⚠️ A leaked secret is a catastrophic vulnerability. ⚙️ Best Practices for Secrets Management High-performing teams implement: Use secret management tools (Vault, AWS Secrets Manager, Azure Key Vault) Integrate secrets retrieval in CI/CD pipelines Automate secret rotation and expiration Audit and log all access Limit secrets to least privilege 🔐 Treat secrets like first-class infrastructure components. 🧩 Real-World Use Case A compromised API key caused production downtime. Fix applied: All secrets stored in Vault Pipelines fetch secrets dynamically Automated rotation and audit logging enabled Result: No secrets exposed in code Safer deployments Reduced security risk 🎯 Interviewer Insight This question tests whether you: Understand secure DevOps practices Can automate sensitive operations Protect business-critical data > ❗ Weak answer: “We put secrets in environment variables or config files.” 🧠 One-Line Power Statement Secrets are only secure when managed, automated, and audited. #DevOps #SecretsManagement #DevSecOps #CICD #SRE #DevOpsInterview

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Speed wins in AI, and infrastructure should never be the bottleneck 🚨 When Techdome set out to accelerate AI-led product delivery across India, the UAE, and the US, they needed a Kubernetes platform that matched their automation-first engineering culture. Traditional cloud providers were slowing them down with high costs, complex provisioning, and over-engineered setups. By adopting Civo Kubernetes, Techdome reduced infrastructure costs, simplified operations, and provisioned production-ready clusters in minutes. The result is faster go-to-market timelines and improved ROI for both Techdome and its customers. Read the full case study to see how Techdome accelerated AI delivery with Civo: https://civo.io/4sUid34

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🚀 Day 10 of My Terraform Learning Journey – Writing Smarter Infra, Not More Infra Today’s learning was a big upgrade in how I approach Infrastructure as Code. I dug into three concepts that make Terraform feel intelligent: Conditional Expressions, Dynamic Blocks & Splat Expressions. And honestly, these features are true productivity boosters. 👇 🔹 Conditional Expressions – Let Terraform Think No more multiple configs for dev/stage/prod. Based on a simple condition, Terraform auto-selects the right values (instance types, tags, AMIs, etc.). Cleaner code + fewer mistakes. 🔹 Dynamic Blocks – My Biggest Win Today Instead of writing the same nested blocks again and again, one dynamic block generates them automatically. Perfect for: ✔ Security group rules ✔ EBS volumes ✔ IAM statements ✔ Route table routes It keeps modules DRY and super scalable. 🔹 Splat Expressions – Extract Anything in One Line Need all instance IDs? All subnet IDs? All SG ARNs? Just use [*] and Terraform gives you a clean list. Makes outputs easier and modules more reusable. 🌟 The Real Power Together, these three make Terraform: 🔥 More flexible 🔥 More environment-aware 🔥 Much easier to maintain Today’s session didn’t just teach me syntax — it changed how I design Infra as Code. 📝 Full blog for those who want the deeper breakdown: 👉 https://lnkd.in/g5AqqVUn #Terraform #DevOps #AWS #IaC #LearningInPublic #CloudComputing #TerraformTips #InfraAsCode #TerraformLearningJourney #100DaysOfCloud #awscommunity #devopscommunity #30daysofawsterraform

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Deploy Apache Web Server on Kubernetes Cluster: There is an application that needs to be deployed on Kubernetes cluster under Apache web server. The Nautilus application development team has asked the DevOps team to deploy it. We need to develop a template as per requirements mentioned below: Create a namespace named as httpd-namespace-devops. Create a deployment named as httpd-deployment-devops under newly created namespace. For the deployment use httpd image with latest tag only and remember to mention the tag i.e httpd:latest, and make sure replica counts are 2. Create a service named as httpd-service-devops under same namespace to expose the deployment, nodePort should be 30004. Solution: #Create namespace $ kubectl create namespace httpd-namespace-devops #Create deployment $ sudo vi httpd-deployment-devops.yaml apiVersion: apps/v1 kind: Deployment metadata:  name: httpd-deployment-devops  namespace: httpd-namespace-devops spec:  replicas: 2  selector:    matchLabels:      app: httpd-app  template:    metadata:      labels:        app: httpd-app    spec:      containers:      - name: httpd-container        image: httpd:latest        ports:        - containerPort: 80 :wq #Create Service $ sudo vi httpd-service-devops.yaml apiVersion: v1 kind: Service metadata:  name: httpd-service-devops  namespace: httpd-namespace-devops spec:  type: NodePort  selector:    app: httpd-app  ports:    - port: 80      targetPort: 80      nodePort: 30004 :wq #Apply Configuration $ kubectl apply -f  httpd-deployment-devops.yaml $ kubectl apply -f httpd-service-devops.yaml ✅ Verify Everything (VERY IMPORTANT) #Check Namespace $ kubectl get ns #Must show httpd-namespace-devops #Check Deployment $ kubectl get deployment -n httpd-namespace-devops #Should show 2/2 Ready #Check Pods $ kubectl get pods -n httpd-namespace-devops #Two pods must be running #Check Service $ kubectl get svc -n httpd-namespace-devops #Must show NodePort 30004 🎯 Lab Validation Checklist ✔ Namespace name correct ✔ Deployment name correct ✔ Image exactly httpd:latest ✔ Replicas = 2 ✔ Service type = NodePort ✔ NodePort = 30004 ✔ Same namespace used everywhere #DevOps #Linux #Docker #Jenkins #CICD-Pipeline #Ansible #Kubernetes #Terraform #IaC #AWS #Azure #PowerShell #ShellScript #Bash

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