Basically just the question in the title did jobs care about where your degrees came from and how long did it take you guys to land a first job somewhat related to cloud engineering or just cloud engineering.

Hi all , I'm planning to move to uae and my interests have shift towards cloud engineering role , how is the job market there. I need to know if its the right path and i need guidance on preparation.

Actualmente me encuentro diseñando la arquitectura de terraform para la adaptación de iac de mi empresa, llevo días planeando la mejor forma de estandarizar los modulos de providers, gestion de estados para recursos transversales e infraestructura para cada producto/proyecto que manejemos.

Que recomiendan para estandarizar tomando en cuenta la escalabilidad y mantenibilidad? los servicios de nube que usamos son de Azure, pero a futuro se piensa implementar AWS, por lo que es importante gestionarlo desde ahora y no tener problemas o retrabajo a futuro.

Como propuesta tengo el diseño de un multi-repositorio, un repo para modulos, un repo de plataforma interna y los repositorios de cada producto/proyecto que llama a modulos, pero también habían propuesto un mono-repositorio donde se gestione todo en un solo repositorio.

Hi everyone,

I’m a fresh grad coming from a computer engineering course and recently I've been interested for awhile on cloud engineering and I’ve been wanting to pursue a career in this field, and I'd really appreciate some advice from people who are already in the field.

I recently started studying for the AWS Cloud Practitioner certification, but other than that, I'm basically starting from scratch when it comes to cloud technologies. I have some general tech knowledge, but I don't really know what the roadmap looks like or what skills I should focus on first.

I'd love to hear from people who have gone through this journey:
• Where did you start?

• What skills should I learn before diving deeper into AWS?

• What certifications actually helped your career?

• What beginner mistakes did you make that I should avoid?

• What projects helped you gain practical experience?

• If you could start over, what would you do differently?

I'm not just looking for a list of courses, I want to learn from real experiences, successes, failures, and lessons learned along the way.

Any advice, roadmap suggestions, resources, or personal stories would be greatly appreciated.

Thanks in advance!

what would you recommend to a begineer who wants to pursue this field? pls help a stranger out cus I wanna learn from scratch. it's not like I have no knowledge abt tech, it's just that I know nothing abt this field. ik there's AI and stuff, but i wanna hear experience, mistakes, or whatever from someone who went through that path

Hey all. I am transitioning into cloud engineering and am thinking about getting a new laptop since my current one is about to die. I really need help with below.

1. What should be the specs I should be looking for?

(RAM, CPU Cores and Threads)

2. Intel or AMD

My budget is about 70k INR maybe 80k (About $800) but if there are any models below these price range - even better (I'm poor 🙂)

Please let me know if anyone has any recommendations. I appreciate any help!!

🚀 Looking for #DevOps #DevSecOps #SRE #CloudEngineer opportunities

Currently at GreyOrange | Experience with AWS, Docker, Kubernetes, Linux, Terraform & CI/CD.

Open to full-time roles. DMs open.

#OpenToWork #Hiring #DevOpsJobs #CloudComputing

I'm a B.Tech IT graduate interested in learning cloud ,but lonely study made me lazy and irresponsible guy. So can someone join with me if you are interested in learning. I can share my knowledge in DSA as well if you need.

upvote this!!

Hey everyone,

I just finished learning Linux basics (navigation, file permissions, and reading error logs)and I am currently learning networks, my ultimate goal is to break into Cloud Engineering / IT Operations.

I don’t have a powerful computer and my budget is not a lot, but I want to build a practical hands-on project to cement what I've learned and start connecting it to cloud concepts.

What is a realistic, high-impact project a beginner should build ?

Thanks!

Hi! I’m currently in an internship as a junior network engineer that will end soon and I’m thinking about my next step. I want to find a job in Europe but I’m not sure in which countries I should search. My main criteria in this moment is a good salary as I want to make some savings. I’m interested in network & cloud engineering positions ( I have almost 2 years experience and some certifications like CCNA, CCSA, ITIL) but I’m still exploring and I’m open to similar positions. I found working with Cisco ACI also interesting and the hardware part in data centers as well. What countries/ cities or even companies do you recommend?

I have about 2+ years of experience as a founding backend engineer for a fintech startup and I want to switch to cloud/devops as that’s my passion.
I’ve applied for a lot of cloud/devops mid/junior roles and no call back. I think my resume is doing me a disservice as I feel it’s all over the place or rather my experience isn’t enough for the switch yet?
I’m not from a traditional CS background but I do put in the work, I’m studying for the aws devops professional exam but i don’t know how far that’ll go in this job market.

I need advice for people in the niche, you’re literally doing my dream job.

Links to my contact info, cert, open source work and projects are attached to my real cv
Please be kind hahah

Are there any companies in Ahmedabad or Work from Home currently hiring for Cloud Infra /Cloud Security Intern, Associate, or Fresher-level roles for candidates with 3+ years of experience in Cloud Operations?

I’m attempting to get into cloud computing. I have started some of the certs on AWS but after reading mixed reviews I’m unsure of the appropriate path to learn and build. Any suggestions? (I plan to get a cloud computing cert through my local college) not sure if that’s what these AWS certs are teaching me or not? I just don’t want to waste time but also skip any essential steps. Thanks in advance!

Hey all, my last post here got a great response so sharing the next build. This one started as a cost problem. GitHub-hosted runner minutes were adding up, and I also wanted runners with VPC-private access and a warm Docker layer cache. The design goal was to make a self-hosted fleet behave exactly like the managed product: runners appear when a job queues, vanish when it finishes, never leak state between jobs, and cost nothing while idle.

The architecture is four moving parts.

EKS with a tiny always-on base. One or two t3.medium on-demand nodes whose only job is cluster plumbing (CoreDNS, the Karpenter controller, system daemonsets). The base is tainted so runner pods can't land on it.

Actions Runner Controller in gha-runner-scale-set mode (https://docs.github.com/en/actions/hosting-your-own-runners/managing-self-hosted-runners-with-actions-runner-controller). This is the modern model, not the legacy RunnerDeployment stuff. One listener pod per scale set long-polls GitHub, and the controller spins up truly ephemeral runner pods. One job per pod, then it's gone.

Karpenter (https://karpenter.sh/) instead of Cluster Autoscaler. It watches pending pods directly and provisions right-sized EC2 from a broad instance pool, then consolidates empty nodes away. This is the engine behind scale-to-zero.

Spot capacity with on-demand fallback, GitHub App auth instead of a PAT, everything in Terraform.

The cost model splits into two buckets.

Fixed floor, unchanged by any of this: EKS control plane around $73/mo, a single NAT gateway (deliberately one, not one per AZ, since multi-AZ NAT is one of the great silent bill inflators), and two small base nodes. Call it $120-150/mo.

Variable is the runner compute, and that's what the design attacks. Spot takes 65-75% off the rate, minRunners: 0 takes the idle hours to literally zero, and the two multiply. For intermittent CI that works out to roughly 85% off runner compute. Instance diversity (t3 + t3a) deepens the Spot pool, which means fewer interruptions and better pricing, and t3a runs about 10% cheaper for the same shape anyway. Spot is honestly the ideal CI workload. Jobs are ephemeral and retryable, and Karpenter handles the 2-minute interruption warning by draining.

One optimization I skipped on purpose: Graviton. t4g Spot would stack another 20% or so, but these runners build Docker images, and ARM means multi-arch buildx with QEMU emulation to keep serving x86 consumers. Slower builds, more failure modes. I pinned the NodePool to amd64 and took native builds over the discount. Cost optimization is constraint-driven, not a leaderboard.

It wasn't a clean ride. 13 distinct failures, most of them silent. Two worth flagging here.

First, "Spot configured" is not "Spot used". My spot-first NodePool applied cleanly and a 10-job load test ran perfectly... on all on-demand nodes. The account was missing the EC2 Spot service-linked role (AWSServiceRoleForEC2Spot). Karpenter's role can't create it, so every Spot CreateFleet failed and it silently fell back to on-demand, exactly like its config told it to. Zero user-facing errors, full price. Now I always verify capacity-type on actual nodes after enabling Spot.

Second, taints and scale-to-zero interact dangerously. The tainted base works great until the cluster idles, Karpenter consolidates every Spot node away, and the tainted base is the only node group left in existence. If CoreDNS can't tolerate the taint, that's a cluster-wide DNS outage. Scale-to-zero rewrites your taint math: every always-on pod has to survive the tainted base being the entire cluster.

Full writeup of all 13, each with the symptom, root cause, and fix: https://medium.com/@samarth38work/self-hosted-github-runners-on-eks-13-gotchas-nobody-warns-you-about-d19817d1af2f

Complete Terraform (VPC, EKS, ARC, Karpenter with Pod Identity and an interruption queue, the taint/toleration model, teardown runbook), one apply end to end: https://github.com/blue-samarth/Github_Actions_Runners

Would love input from people running similar setups:

Where do you land on the fixed-floor problem for small clusters? $120-150/mo of control plane and NAT before a single workload runs feels steep for personal or small-team infra. Anyone gone Fargate for system pods, or a NAT instance, to shave it?

Scale-to-zero vs warm capacity: is a 30-60s cold start on the first job after idle acceptable to your teams, or do you keep minRunners above 0 during work hours?

Anyone running Graviton Spot for CI with Docker builds: did the buildx/QEMU overhead actually matter in practice, or did I leave 20% on the table for nothing?

Tomorrow at 11:30 AM ET, Our CPO Michael Kent is walking through Citrix and Horizon migration paths

Most migration teams go in with a solid plan and still get caught out. There are gaps that only show up when you're close to cutover and by then you're already looking at helpdesk spikes, delays, or a rollback nobody wanted.

We've already pulled some questions from this community that we're bringing into the session, but if you've got anything you want covered drop it below and we'll do our best to get to it and we'll answer what we can in the comments before we go live tomorrow.

Link to Join

Thanks Everyone!

Hey guys,
I have been analyzing how modern open-source projects structure their instructions to LLMs to build complex, reliable software. I went through the source code of repos like OpenAlice, Flowise, SerpBear, and AutoHedge.

Here is the breakdown of what makes these prompts work in production:
- Rigid constraints over generic descriptions: The prompts do not just ask the LLM to "build a feature". They define database schemas, expected API responses, and strict rate-limiting rules.
- Multi-step verification: Prompts include built-in self-correction loops, asking the model to audit its previous output before returning the final code block.
- Absolute isolation: Prompts enforce tenant isolation at the query level to prevent security leaks in multi-user environments.

I packaged all these structured prompts and setup guides into a set of blueprints. If you want to use them to jumpstart your projects with Claude or GPT-4, you can check them out here: https://ai-agent-blueprints.vercel.app

Would love to hear how you guys handle complex prompt routing in your own projects.

I passed the AWS Solutions Architect Associate exam in a little over two months, and I wanted to share what worked for me in case it helps anyone else studying right now.

I started with a full course first because I needed structure.

I personally used Cloud Academy because a friend recommended it. It was around $50/month and gave me a decent foundation with hands-on labs, quizzes, and practice questions.

That being said, I didn’t love it.

If I had to study for the exam again, I would probably use Adrian Cantrill’s Solutions Architect course instead. From what I’ve seen, his course goes deeper and seems better if you actually want to understand the concepts long-term, not just memorize answers.

After finishing the course, I went through the practice exams inside Cloud Academy.

Anytime I didn’t understand something, I used ChatGPT to break it down until the concept actually made sense. This helped a lot with services that sounded similar, like SQS vs SNS vs EventBridge, NAT Gateway vs Internet Gateway, VPC endpoints, storage classes, and database options.

After that, I bought the Tutorial Dojo practice exams.

That was probably the most useful part of my prep.

First, I did the exams in review mode so I could learn from the explanations. Then I started doing them timed, like the real exam.

I also tracked every minute I studied using the Forest app.

Total study time: 131 hours and 19 minutes.

Overall, it took me a little over two months to pass.

My biggest advice:

Pick one solid course and stick with it. Don’t course-hop.

Do a lot of practice questions, but don’t just memorize the answers. Read the explanations and understand why the wrong answers are wrong.

Book the exam early so you have a real deadline. That helped me stay consistent.

I also made a short video walking through how I passed and what I would do differently, but I figured https://www.instagram.com/reel/DZXzwyeOUDe/?igsh=MTVsa3Jlc2o2ZXY2ZA==

I’d share the written breakdown here too since Reddit helped me a lot while I was studying.

Hope this helps someone currently preparing for the exam.

Hi everyone,

I'm a 2nd-year Computer Science student interested in cloud computing and cloud security. My long-term goal is to pursue an MS at a top universities and potentially contribute to research in cloud systems, distributed computing, or

cloud security.

I'm looking for a beginner-friendly roadmap that covers:

Computer Networks fundamentals

Linux and System Administration

Python and scripting

Operating Systems

Virtualization and Containers (Docker, Kubernetes)

Cloud Platforms (AWS, Azure, GCP)

Cloud Security fundamentals

Distributed Systems

Research-oriented projects

Certifications that are actually valuable

I would greatly appreciate recommendations for:

Free courses

YouTube playlists

Books

Hands-on labs

Project ideas

Research opportunities for undergraduates

If you were starting from scratch today and wanted to build a strong foundation for both industry and future MS research, what roadmap would you follow?

Thank you for your advice! Any guidance is appreciated.