Tips for Gaining Practical Experience in Cloud Engineering

𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝗽𝗲𝗻𝗱 𝟰𝟬𝟬 𝗵𝗼𝘂𝗿𝘀 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗪𝗦 𝗮𝗻𝗱 𝘀𝘁𝗶𝗹𝗹 𝗴𝗲𝘁 𝗶𝗴𝗻𝗼𝗿𝗲𝗱. Here’s why you’re not getting hired, and how to flip the game. Most people treat the cloud like school: 📚 Study. 📝 Test. 🎓 Cert. Then… silence. No job. No calls. No shot. Why? Because you’ve built 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲, not 𝘃𝗮𝗹𝘂𝗲. Here’s what the people who go from “𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴” to $80, $90 or even $100K+ offers actually do (that no course will teach you): 𝟭. 𝗧𝗵𝗲𝘆 𝗕𝘂𝗶𝗹𝗱 “𝗣𝗿𝗼𝗼𝗳 𝗔𝘀𝘀𝗲𝘁𝘀,” 𝗡𝗼𝘁 𝗝𝘂𝘀𝘁 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 Projects are good. But 𝘗𝘳𝘰𝘰𝘧 𝘈𝘴𝘴𝘦𝘵𝘴 are better. This means: ✅ GitHub repo + architecture diagram ✅ Loom walkthrough: "Here’s how I built it & why" ✅ LinkedIn post: “Business impact of my cloud solution” ✅ Resume bullet: “Reduced X by Y using Z” They don’t just 𝘣𝘶𝘪𝘭𝘥 stuff, they 𝘱𝘢𝘤𝘬𝘢𝘨𝘦 it like a portfolio pitch deck. 𝟮. 𝗧𝗵𝗲𝘆 𝗦𝗼𝗹𝘃𝗲 𝗜𝗻𝘃𝗶𝘀𝗶𝗯𝗹𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 Most beginners build what’s 𝘰𝘣𝘷𝘪𝘰𝘶𝘴 (launch an EC2, host a static site). The ones that want the offer, build what’s 𝘶𝘯𝘥𝘦𝘳𝘷𝘢𝘭𝘶𝘦𝘥: “Automated IAM cleanup across dev/test accounts” “Created centralized logging using ELK & S3 lifecycle policies” “Built a budget alerting system for sandbox projects” These sound advanced, but they’re not. They just 𝘀𝗼𝗹𝘃𝗲 𝗿𝗲𝗮𝗹 𝗽𝗮𝗶𝗻��� companies actually deal with. 𝟯. 𝗧𝗵𝗲𝘆 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 They don’t just say, 👉🏾 “I set up a VPC.” They say, 👉🏾 “I designed a 3-tier VPC for a fintech app that needed PCI-DSS compliance, public ELB, private app + DB tiers, NAT gateway for secure outbound traffic.” Even if it’s all mock, it 𝘵𝘦𝘭𝘭𝘴 𝘱𝘦𝘰𝘱𝘭𝘦: 🎯 “I think like an engineer.” 🎯 “I understand context.” 🎯 “I can walk into your problem and build something that makes sense.” 𝟰. 𝗧𝗵𝗲𝘆 𝗥𝗲𝘃𝗲𝗿𝘀𝗲-𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗝𝗼𝗯 𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻𝘀 Every cloud job is a cheat sheet. Instead of guessing what to build, they: * Pull 10 job posts * Circle every tool/problem mentioned * Build mini-projects around those * Post their journey like a series: “One week, one use case” 👉🏾 By week 5, they’ve built a portfolio targeted to actual market demand. 𝟱. 𝗧𝗵𝗲𝘆 𝗔𝗰𝘁 𝗟𝗶𝗸𝗲 𝗧𝗵𝗲𝘆 𝗔𝗹𝗿𝗲𝗮𝗱𝘆 𝗕𝗲𝗹𝗼𝗻𝗴 This is subtle but massive: They don’t “hope to break in.” They speak, share, and build like they’re already in. Their content doesn’t say: “I’m learning cloud.” It says: “Here’s how I think about cloud architecture.” That energy gets noticed. That mindset 𝗽𝘂𝗹𝗹𝘀 𝗗𝗠𝘀. That shift = leverage to show you can solve THIER problem. Want to Actually Get Hired? Stop going after all certs. Start proving capability. Start showing how you solve problems. 💬 Drop “𝗣𝗥𝗢𝗢𝗙” if you want the full list of value-packed, business-focused projects that actually convert to interviews. I'll send you access to them Let’s make the work, 𝘸𝘰𝘳𝘬 for you.

Stop Collecting Courses. Start Building Systems. I’ve reviewed hundreds of cloud resumes, and here’s the pattern I see: What doesn’t differentiate you: • Another AWS certification • Completed online courses • Theoretical knowledge of services What actually gets you hired: • A GitHub repo showing you deployed a three-tier application on AWS • Evidence you’ve solved real architectural problems • Infrastructure-as-code that demonstrates you understand security and scalability The Learning Trap: Too many aspiring cloud engineers get stuck in perpetual learning mode—jumping from course to course, certification to certification. Meanwhile, the market is screaming for people who can actually build. What Building Projects Actually Teaches You! When you deploy real infrastructure, you encounter: • IAM policies that are too permissive (and how to fix them) • Cost overruns that teach you resource optimization • Network configurations that don’t work , until you understand VPCs deeply • CI/CD pipelines that fail will for e you to master automation. • Monitoring gaps that teach you observability. These lessons don’t come from videos. They come from breaking things and fixing them. Start Here Build something you’d actually use: → Deploy a containerized app with ECS/EKS → Automate infrastructure with Terraform → Create a CI/CD pipeline that deploys on merge → Implement monitoring with CloudWatch and alerting → Document your architecture decisions Then make it public. Write about what you learned. Share your code. The Reality Hiring managers don’t care if you watched 400 hours of tutorials. They care if you can design a VPC, write secure IAM policies, and automate deployments without breaking production. Your GitHub profile is your portfolio. Make it count. What projects are you currently building? What challenges are you running into? My is on the comment section #AWS #CloudEngineering #DevOps #CareerAdvice #TechCareers #CloudComputing #InfrastructureAsCode #LearningByDoing #BuildInPublic #SoftwareEngineering

After 10 years in Cloud Engineering, I wish someone had told me these truths from day one: "Embrace boring technology." That shiny new AWS service isn't worth the operational overhead. Master the fundamentals first: EC2, RDS, S3, and IAM. "Infrastructure as Code isn't optional."  Every manual click in the AWS console is technical debt. If you can't recreate your environment from code, you don't own it. "Security by design, not by accident."  Adding security after the fact is 10x harder than building it in. Start with least privilege IAM from day one. "Automation saves your sanity, not just time."  The goal isn't speed, it's consistency. Manual processes create knowledge silos and single points of failure. "Document your decisions, not just your code."  Write down WHY you chose this architecture. Future you (and your team) will thank you during the inevitable 3 AM incident. "Plan for failure from the beginning."  Every service will fail. Every network will have issues. Design for it, test for it, expect it. What's the best cloud advice you wish you'd received earlier?

𝐓𝐡𝐞 𝐃𝐞𝐯𝐎𝐩𝐬 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐩𝐚𝐭𝐡 𝐄𝐯𝐞𝐫𝐲𝐨𝐧𝐞 𝐚𝐬𝐤𝐬 𝐚𝐛𝐨𝐮𝐭.  Here's the Roadmap that actually works in Production. After mentoring 100+ engineers,  I've seen too many get lost in tutorial hell.  This landscape shows the progression that builds production-ready skills. 𝐌𝐲 𝐫𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐬𝐞𝐪𝐮𝐞𝐧𝐜𝐞: 𝟏. 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 (𝐌𝐨𝐧𝐭𝐡𝐬 𝟏-𝟑): • One language: Python, Go, or Ruby—pick one, master fundamentals • Linux OS concepts: processes, memory, file systems • Terminal mastery: bash scripting, text tools (awk, sed, grep) • Ubuntu or CentOS—stick with one until you can troubleshoot blindfolded 𝟐. 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐁𝐚𝐬𝐢𝐜𝐬 (𝐌𝐨𝐧𝐭𝐡𝐬 𝟒-𝟔): • Networking: HTTP/HTTPS, SSH, DNS—you'll debug these weekly • Web servers: Nginx or Apache, reverse proxy patterns • Security: SSL/TLS, firewalls, port forwarding 𝟑. 𝐈𝐚𝐂 & 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬 (𝐌𝐨𝐧𝐭𝐡𝐬 𝟕-𝟗): • Docker fundamentals before Kubernetes • Ansible or Puppet for config management • Terraform for infrastructure provisioning • Kubernetes only after mastering Docker 𝟒. 𝐂𝐈/𝐂𝐃 (𝐌𝐨𝐧𝐭𝐡𝐬 𝟏𝟎-𝟏𝟐): • GitLab or GitHub Actions • Jenkins—legacy but everywhere • Build automation and testing pipelines 𝟓. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 (𝐎𝐧𝐠𝐨𝐢𝐧𝐠): • ELK or Splunk for logs • Prometheus + Grafana for metrics • APM tools: Jaeger, New Relic Critical insights: DO: • Build real projects, not just tutorials • Automate everything you do twice • Break things in safe environments • Get on-call experience DON'T: • Skip fundamentals to jump to K8s • Collect certs without hands-on work • Try learning everything at once Truth:  Senior DevOps isn't knowing every tool.  It's debugging production at 3 AM and building systems that scale without you. Tools change every 18 months. Principles don't. Where are you on this journey? ♻️ Repost if you found it valuable ➕ Follow Jaswindder for more insights on Cloud Strategy, DevOps, and AI-led Engineering. #DevOps #CloudEngineering #SRE 

If I did not have an internship, here's what I would do to increase my chances for next time. Multiple students have asked me in mentorship calls, "What to do if they don't have an internship?" Sharing a few options: (I followed #4 and #2) 𝟭. 𝗗𝗲𝗲𝗽𝗲𝗻 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀: - Pick one technology (e.g., React, Python, AWS) and build a comprehensive project around it. - Example: If you're interested in AI, build a sentiment analyzer and deploy it on Hugging Face or Streamlit. 𝟮. 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗬𝗼𝘂𝗿 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 (focus on AI usage in every domain): - Clearly document your projects on GitHub using professional READMEs. - Add detailed explanations, architecture diagrams, and deployment links. 𝟯. 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲 𝘁𝗼 𝗢𝗽𝗲𝗻 𝗦𝗼𝘂𝗿𝗰𝗲: - Even small contributions count. Use sites like goodfirstissue.dev or explore GitHub repositories in your domain. - Document your contributions clearly on LinkedIn or your resume. 𝟰. 𝗝𝗼𝗶𝗻 𝗦𝘂𝗺𝗺𝗲𝗿 𝗦𝗰𝗵𝗼𝗼𝗹 𝗼𝗿 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀: - Engage in academic research projects or summer schools offered by universities or organizations. - This provides experience, mentorship, and networking opportunities. - Explore options like Stanford University Summer Session, Massachusetts Institute of Technology Summer Research Program, or the Amgen Scholars Program. Many universities globally offer virtual or on-campus summer research and learning programs -> check their official sites for deadlines and details. Ex: https://oge.mit.edu/msrp/ | https://lnkd.in/gPXEqgxn - 𝘞𝘩𝘢𝘵 𝘸𝘰𝘳𝘬𝘦𝘥 𝘧𝘰𝘳 𝘮𝘦? In my freshman year, I joined the Stanford Summer School and Research Program. At the same time, I built my web portfolios to increase my chances of securing interviews with big tech companies. 𝟱. 𝗪𝗿𝗶𝘁𝗲 𝗮𝗻𝗱 𝗦𝗵𝗮𝗿𝗲 𝗬𝗼𝘂𝗿 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴𝘀: - Post weekly or bi-weekly updates on LinkedIn explaining what you're learning or building. - This boosts visibility and demonstrates initiative to recruiters. 𝟲. 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 & 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: - Leverage high-quality online resources like Coursera, Udemy, or FreeCodeCamp. - Example: Deep Learning Specialization or AWS Cloud Practitioner. https://lnkd.in/ggPDt7qV Internships are beneficial, but your career growth isn’t limited by not having one. Strategic skill-building and visibility can position you strongly for future opportunities.

Want to switch from Software engineer to Cloud engineer role in 6 months? Study this roadmap: You already know the SDLC processes – now dive into how to build, run and deploy cloud-native apps 3-Month Foundation : • Learn core Linux (permissions, systemd, logging) • Understand networking (VPC, DNS, NAT, firewalls) • Pick a cloud provider (AWS / GCP / Azure / OCI) ↳ Focus on IAM, Compute, Storage, networking basics, billing fundamentals etc • Learn Python for automation (already familiar? think how you can use with Boto3, SDKs, scripting) • Learn Infrastructure as Code (Terraform / Pulumi/ AWS Cloudformation) • Explore cloud-native patterns (microservices, managed services) ↳ Target: Junior Cloud Engineer roles (ave comp ~$100k) You already know Git — now use it to: • Version control your Terraform infrastructure • Track changes to IaC and cloud automation scripts • Set up GitOps-style deployment patterns 3-Month Advanced Track : • Pick a specialty (Networking, Data, Databases, DevOps, Security, AI/ML etc) If you picked DevOps: • Work with containers (build/run with Docker) • Deploy apps using Kubernetes (pods, services, configs) • Set up CI/CD pipelines (using cloud-specific services) • Implement cloud security concepts (IAM, roles, secrets management) • Configure monitoring & logging (Cloud-Specific or Prometheus/Grafana) • Automate end-to-end workflows(from build to deploy) using Python or Shell (SDKs, scripts, cron) - [this is very advanced] ↳ Target: Mid-level Cloud Engineer roles (ave comp ~$125k) Leverage your SWE skills: • Containerize existing apps • Build pipelines for test → deploy • Refactor into cloud-native services Quick Wins: - Complete Qwiklabs or provider-specific cloud labs - Sign up for free tiers and experiment (watch your credit limits) - Build and deploy 3 cloud-native projects - Earn a practitioner or specialty certification (based on your tech exposure) Free Resources to start, here's your one stop shop: https://lnkd.in/dF9xVE9X Do this next: You've already built apps - now think which cloud-based services you'd need to run it on cloud (deploy it with Terraform + CI/CD) Hands-on experience >> watching videos or reading blogs. Remember, you're not starting from scratch. As a Software Engineer, you already think in systems. Now think in cloud systems What worked for you in your cloud journey? • • • If you found this useful.. 🔔 Follow me (Vishakha) for more Cloud & DevOps insights ♻️ Share so others can learn as well

I have 12 years of AWS experience If I was in college and here's how I would start. Here’s the path I wish I had when I was starting out 👇 Step 1: Understand the Cloud (but skip the fluff) → What is compute, storage, IAM, VPC? → How do EC2, Lambda, and S3 actually work? 🎓 Start here: → AWS Cloud Quest → Cloud Practitioner Essentials Step 2: Use the Free Tier to build projects → Host a portfolio with S3 + CloudFront → Create a serverless app with Lambda + API Gateway → Set up a DynamoDB database 📚 Tutorials: → AWS Hands-on Labs → Build on AWS (YouTube) Step 3: Learn to code just enough → Python for scripting & Lambda → Shell for automation → Terraform for infra-as-code Resources: → realpython.com → gobyexample.com → HashiCorp Learn (Terraform) Step 4: Get AWS Student Credits → Apply at awseducate.com → Use credits to try SageMaker, RDS, Bedrock, etc. Step 5: Focus on the Core 5 Don’t learn 200+ services. Just start with: → S3 → EC2 → Lambda → RDS or DynamoDB → IAM Build mini-projects with just these. Step 6: Build Projects That Show What You Know Real > Tutorial 💡 Ideas: → Telegram bot using Lambda → AI chatbot using Bedrock + Streamlit → CI/CD portfolio with S3 + GitHub Actions → Scheduled job with CloudWatch + Python → Share them on GitHub → Write about them on LinkedIn Step 7: Join the Community → Follow Corey Quinn, Forrest Brazeal, Ant Stanley → Join r/aws, AWS Discords, local events → Attend AWS Community Days, re:Invent online Final Advice: Don’t chase 100 certs. Build. Break things. Document everything. That’s how you grow. If you want 3 custom AWS project ideas to practice, Comment “AWS Projects” and I’ll send them your way. Let’s get you cloud-ready

As a B.Tech student graduating in 2024, 2025, 2026, or 2027 and dreaming of a career in cloud computing, you're entering one of the most exciting and in-demand fields of technology. Whether you're passionate about designing scalable systems, managing infrastructure, or building cloud-native applications, the opportunities are immense.  But how do you start your journey into the cloud? Here's a step-by-step roadmap to help you get on track:  1. Understand the Basics of Cloud Computing   - Learn the fundamental concepts: What is cloud computing? What are SaaS, PaaS, and IaaS?   - Explore real-world examples of how companies use cloud services.  2. Pick a Cloud Platform - Start with popular platforms like AWS, Google Cloud, or Microsoft Azure.   - Each offers free tiers and beginner-friendly learning paths.  3. Build Your Skills with Hands-On Practice   - Enroll in free labs or platforms like Qwiklabs or Cloud Academy.   - Complete projects like deploying a website or setting up a virtual machine.  4. Earn Certifications - Begin with entry-level certifications like AWS Certified Cloud Practitioner, Microsoft Azure Fundamentals, or Google Cloud Associate Cloud Engineer.   - Certifications not only validate your skills but also make your resume stand out.  5. Learn Supporting Skills  - Familiarize yourself with Linux, networking, and scripting languages like Python or Bash.   - Understand DevOps practices and tools like Docker, Kubernetes, and CI/CD pipelines.  6. Participate in Cloud Competitions and Hackathons   - Look for cloud-specific hackathons, such as Google Cloud Arcade, to sharpen your skills and network with professionals.   - These events provide a platform to showcase your talents and build real-world experience.  7. Create and Share Your Projects   - Build small cloud projects and showcase them on platforms like GitHub.   - Write about your journey and projects on LinkedIn to connect with like-minded individuals.  8. Seek Internships or Entry-Level Roles - Look for internships or roles like Cloud Intern or Junior Cloud Engineer to get real-world experience.   - Reach out to professionals on LinkedIn or join communities to stay updated on job openings.  Remember  Cloud computing is more than just a career—it's an evolving ecosystem that demands continuous learning. Start small, stay consistent, and build your skills step by step.  This field has room for dreamers and doers, and with determination and the right approach, you can build a thriving career in cloud computing.  Stay tuned—I’ll be sharing more detailed insights, free resources, and exclusive opportunities to help you in this journey! For more valuable content like this, follow Vikram Gaur . #CloudComputing #EntryLevelJobs #CareerDevelopment #CloudEngineer #CloudDeveloper #AWS #Azure #GoogleCloud #google #GoogleCloudPlatform #gcp #GoogleCloudArcade #Amazonintern #DevOps #2024batch #DevOpsEngineer

Cloud is the easiest vertical in tech that you can start with. No prior coding experience or technical background is required. Start with Cloud Networking fundamentals, IAM, and the difference between services(compute, serverless, databases, security). Once you are comfortable enough, start mixing all of them, pick a problem statement, for example, a PII-safe version of Google Forms: 1. Create an architecture diagram using Excalidraw & brainstorm on it. 2. Define & set budget alerts, and start building the foundation with the CLI(later replace it with Terraform). 3. Glue everything together, read engineering blogs to refine your approach. Have at least 10-15 such drills. Once you are confident enough, start applying DevOps principles to all your drill applications: 1. Codify your infrastructure. 2. Automate the mundane tasks. 3. Focus on the application delivery. 4. Observe everything.

Stop Learning AWS Randomly — You’re Wasting Time Many people try to learn AWS without a clear structure and quickly become overwhelmed. The reality is simple: structure beats chaos. This roadmap outlines a practical progression that every Cloud/DevOps Engineer should follow: • Start with foundations cloud concepts, shared responsibility, and architecture • Build compute knowledge with EC2 and Auto Scaling • Develop a strong understanding of networking with VPC (a common challenge area) • Secure your environment with IAM (essential and non-negotiable) • Master storage with S3, and databases such as RDS and DynamoDB • Gain visibility through CloudWatch • Learn scalability and content delivery with Route 53, CloudFront, and ElastiCache • Advance into modern architectures with containers and serverless (ECS, EKS, Lambda) The difference between an average engineer and a strong one is not just knowing services it’s understanding how they work together to solve real-world problems. In practice, you are not deploying isolated services. You are designing resilient, scalable, and cost-efficient systems. My advice: Don’t rush. Build → break → fix → repeat. That is how real cloud engineers are developed. #AWS #CloudComputing #DevOps #CloudEngineer #Architecture #Learning #TechCareers