When I read k8s YAML, I am basically doing this:
After doing this too many times, I ended up with something that just visualizes the manifest as a graph and explains it alongside.
It made it way easier to quickly understand what’s going on, especially for larger manifests or stuff I didn’t write.
What do you think of this?
Hello everyone,
We are running a small startup and the problem I am facing right now is single point of failure. Since we don't have much budget, we have hosted in cheap VPS as of now.
We have multiple services(python, node, db, redis, etc) and everything is dockerized inside a compose. So we run staging and production environment behind a nignx revere proxy. Both environment is hosted in single vps. We don't have any monitoring and observisibilty tool right now. The way we deploy is build docker image via github action and push it into vps and run it.
So for our setup, how can we improve our deployment and what are the best strategies we can adapt.
Thank you.
I’ve been speaking with cloud and enterprise architecture teams, and one common theme keeps coming up: architects are no longer just designing systems.
They are expected to handle WAF-aligned designs, architecture documents, PRDs, Infrastructure-as-Code, cost estimates, cloud comparisons, security reviews, and stakeholder explanations — often across multiple clouds.
For Azure teams especially, the workload seems to sit across landing zones, governance, identity, networking, security, cost control, and documentation.
Curious how others are handling this.
Are architects in your organisation still focused mainly on design, or are they now expected to produce the full delivery package as well?
Full disclosure: we are building an AI agents to help cloud architects produce WAF-aligned designs, architecture documents, PRDs, IaC, and costing plans. Not posting this as a sales pitch — genuinely interested in how teams are handling this workload today.
Many people want to switch their career to Cloud Engineering, especially those working as:
Linux Admin
Network Engineer
System Admin
Application Support
SRE / Production Support
Desktop Support
Help Desk
QA Automation
BPO Technical Support
NOC Engineer
Most of us have 2 to 5 years of experience, but with only the current experience and daily tasks, it is difficult to switch directly into a Cloud Engineer role.
First, focus on learning cloud technologies properly. After that, try to work on real-time tasks and projects to understand how the industry actually works.
Once you gain hands-on experience with real-world scenarios, it becomes much easier to clear cloud interviews and move into a cloud career successfully.
Feel free to reach out me if you need any guidance.
Hello, I work in one of the Big 4... And preparing for a switch.
Can you please analyze my resume and let me know what I am missing.
I’ve been doing a help desk internship at my city hall for 2 years and I graduate in December with a computer science degree. I’m looking into getting into cloud engineering because I’ve seen that it’s in more demand and the pay is better. Would any companies even be interested in me for a jr cloud engineering role or anything similar or would I have to try and get the full time help desk role first then leverage that into a cloud career. Was also looking into getting an AWS cert over the summer when my classes end to boost up my resume. Any advice on what I should be doing else would be greatly appreciated!
Hey everyone, I’ve been building a free platform for AWS certification prep and wanted to share it here for anyone currently studying.
What you'll find:
• Domain-focused practice questions aligned to real exam topics
• Full-length practice exams
• Instant feedback with explanations
• No paywall, no credit card (free during beta)
Would really appreciate any honest feedback — still actively improving it.
Do you guys think it's a best option to use Claude Ai to learn cloud by creating a road map and using it daily?
If so what other sites or sources should I use to supplement the learning? I've already started yesterday running for 240 days every.
Looking forward to hearing your tips and advice.
Hi everyone! I'm starting a position at a company as a "cloud architect"... at least that's the title, but I think my employer isn't very sure about what they expect from me.
Anyway, the first thing I noticed is that they've been very messy with their use of AWS resources: lots of people have created resources without following any standards, using arbitrary names, no tags, and everything created from the console (the company has started using IaC, but it's not enforced everywhere). That kind of mess.
To start, I decided to propose some guidelines for the use of REST APIs, and I'm doing some research to get ideas. So far, I've mainly found information about best practices for developing REST APIs, but now I'm looking for something more high-level: how should the scope of an API be defined (when should two APIs be merged, or when should one be split)? Also, any ideas on how to structure repositories for the IaC of REST APIs?
For now, those are the main questions I'm stuck with. If you have any comments or recommendations, I would really appreciate it.
Regards!
Pretty much the title. We have 47 aws accounts across prod, staging, dev, sandbox. The idea of deploying agents to every workload in every single one makes me want to walk into the sea.
Cross-account permissions took us weeks alone. Then agent health monitoring. Then auto-scaling groups launching without the damn agent installed. Every sprint something new broke. Agentless is the only thing that scales.
Change my mind, or better yet, tell me what I'm missing cause every vendor demo makes agents sound like a five minute install and that has not been my reality.
For people who already have a job in cloud :
In this case:
I'm concentrating on the basics of AWS, Linux, and networking.
Next, I want to learn about CI/CD, Docker, and infrastructure as code.
Still working on my programming basics (C/C++/Python)
btw i found this roadmap on youtube do you guys think it is good : roadmap
moreover, i saw many people saying that cloud is not for beginners and one should gain some experience before entering this field but is there any way to bypass it like by getting certifications and deploying projects.
We’re hiring experienced Cloud Engineers to help design, deploy, and maintain robust cloud infrastructure—without the overhead of unnecessary meetings.
What you get:
What you’ll be working on:
What we’re looking for:
If this sounds like a good fit, send a message with your experience and location—we’d love to connect.
kubelizeme — free, native Kubernetes manager
A free alternative to Lens, built with Tauri (Rust) + React. Universal macOS binary + Linux. Lightweight (~10 MB bundle, ~50 MB RAM).
What it does:
- Multi-cluster — merges KUBECONFIG, ~/.kube/config, extra files, and service-account token connections; switch contexts via tabs with custom aliases
- Full resource coverage — Pods, Deployments, StatefulSets, DaemonSets, ReplicaSets, Jobs/CronJobs, Services, Ingresses, ConfigMaps/Secrets, PVs/PVCs/StorageClasses, Nodes, Namespaces, Events, HPAs, PDBs, ResourceQuotas, LimitRanges, NetworkPolicies, PriorityClasses, Endpoints/EndpointSlices
- CRDs — browse by API group, list instances, view YAML
- Helm — install, upgrade with dry-run preview, rollback with revision picker, uninstall, history, repo search
- Logs — multi-pod streaming (stern-like), per-pod color/exclude, 10k-line ring buffer
- Exec / Terminal — per-cluster terminal panel with PTY sessions (in-pod and local shells), `Ctrl+`` toggle
- Debug containers — ephemeral debug container creation with auto-exec
- Workload actions — scale, rollout restart, view YAML/describe
- RBAC Visualizer v2 — subject browser, permission tree, risk scoring, scoped graph
- Dashboard — cluster metrics from metrics-server, pod phase chart, node health, warnings
- Cmd+K global search across all resources, Cmd+Shift+P kubectl-like command palette with aliases
- AI assistant — right-docked chat panel (detachable), supports Ollama, LM Studio, OpenAI, Claude; agentic tool-calling with permission gating; contextual [?] button on problematic resources
- Cloud detection — auto-detects EKS/AKS/GKE/DO/OVH/Linode
- Themes — dark/light, fully consistent
- Distribution — Homebrew cask (brew install --cask amioranza/tools/kubelizeme)
Stack: Tauri v2, kube-rs 0.99, tokio, React 19, TanStack Query, Zustand, Tailwind v4.
I am offering 1:1 personalized training with hands-on experience and real-time project work. This is ideal for anyone looking to gain practical skills rather than just theoretical knowledge.
If you're interested in learning with direct guidance and working on real-world projects, feel free to reach out to me for more details.
Experience : intern-Senior
Location: Must be US, Canada, Mexico
Salary: Negotiable; specific details can be discussed privately.
Apply: Country + Gender
Hey guys, just curious has anyone done this academy/bootcamp or what your thoughts on it might be?
https://learn.cloudengineeracademy.io/training
It is by Tech with Soleyman from YouTube who mainly focuses on Cloud Engineering educational videos. Apparently this Academy/Bootcamp costs in the mid-thousands $$.