
Linux Concepts Explained Using Windows Analogies
Every cloud engineer must know the linux fundamentals.

Every cloud engineer must know the linux fundamentals.
Feels like every company eventually reaches:
“Why are we running this tiny internal service on a 40-layer orchestration platform?”
I’m seeing more teams move smaller workloads back to:
- ECS/Fargate
- plain Docker on VMs
- managed PaaS
- even systemd services
Not because Kubernetes is bad.
Because not everything needs:
- operators
- ingress drama
- Helm templating nightmares
- CRD ecosystems nobody understands
- 14 dashboards to debug one timeout
K8s is incredible at scale.
But I think a lot of orgs adopted it WAY before they actually needed it.
Curious if others are seeing the same thing internally.
I am interested in this profession and i have couple questions, are there fully remote opportunities to work in this profession, is this better path then software/devOps engineering, and what would be my beginner to job timeline to start, since i have 8-12 hours available daily for next 2-4 months? Thank you in advance.
i would like to apply for us company maybe work remotly or even there what are the real paths that i should take
Hey everyone,
I’ve been working in an MSP for about 4 years now, currently doing mostly Level 3 work.
Pretty much deal with everything SMB clients throw at us — networking, firewalls, servers, Microsoft 365, security, VoIP, CCTV, Windows/Mac, MDR/XDR, troubleshooting, projects, etc. Basically a bit of everything.
Currently on around 100k AUD, but I’m trying to figure out where to go next career-wise.
I’m interested in moving more towards:
Network Engineering
Cybersecurity
DevOps / Cloud
But honestly not sure what the best move is from an MSP background since you end up becoming a generalist.
For people who made the jump from MSP:
How did you do it?
What should I focus on learning?
Any certs/projects that actually helped?
Which path would you recommend long term?
Would appreciate any advice from people who’ve been through it.
Thanks!
\#MSP #SysAdmin #ITCareer #NetworkEngineer #CyberSecurity #DevOps #CloudEngineering #Microsoft365 #Networking #Firewall #Servers #CareerAdvice #ITSupport #Level3Support #Infrastructure #VoIP #MDR #XDR #WindowsServer #Homelab
I know sysadmin is one, but I want to take a different route that's more automation and coding to start with. I say this because I heard someone say that cloud engineering is more a product engineering role rather than a traditional infrastructure role.
Wondering if switching to cloud engineering would be a good choice, coming from SAP HANA background with 2 years of experience.
Kindly share some tips to begin as a fresher in the domain
Found this as a lightweight alternative to OpenCost. I didn't want to deploy anything into the cluster, just get quick insights into where the money is going. It runs locally via kubectl, pulls real pricing from AWS/Azure/GCP, and breaks down costs by namespace and pod.
Hey everyone,
I’m currently working in helpdesk and have just over 2 years of experience. My goal is to transition into a junior cloud engineer role by 2027, but I honestly feel a bit stuck on where to begin properly.
I’ve done some certs already, but if I’m being real, I mainly passed them through memorising past papers/exam questions. That method has always worked for me academically, but the knowledge doesn’t really stay in my head long-term. I’ve realised the only way I properly learn is through real-life experience and hands-on work.
At work, I mainly use PowerShell for scripting and we use Azure quite a lot. I’ve also spoken to one of my senior colleagues and he’s open to helping mentor me a bit, which I’m really grateful for, but I still don’t know what projects or areas I should focus on first.
So I wanted to ask people already in cloud:
What projects would actually help someone at my level break into cloud?
What should I be building in Azure to gain practical experience?
Are there any “must know” junior cloud skills that companies actually care about?
How can I make the most of my current helpdesk role to transition internally or externally?
I’d especially appreciate advice from people who moved from helpdesk/support into cloud engineering because sometimes it feels difficult to bridge that gap without getting lucky with an opportunity.
Any advice/resources/project ideas would be massively appreciated!
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 am a 23-year-old woman from the Middle East. I graduated from the BIS Institute and obtained an OSCP certification in cybersecurity, as well as an AWS Associate certification. I have approximately six months of experience in freelance bug bounty projects. I am looking to work with a European company in the field of cloud security. Will it be difficult to get a job, even though it's my first opportunity, and what is the potential salary in dollars?
Hey Chat,
I recently finished building an end-to-end MLOps setup on Kubernetes using EKS because I wanted to understand what it actually takes to run ML workloads in production, not just the usual “deploy a model” tutorials.
A few things I implemented:
The security side of this project honestly changed the way I think about deployments. After reading about a few real-world supply chain incidents, I decided to go much stricter with image signing and admission policies.
I also wrote a short Medium post about that mindset shift:
https://medium.com/@samarth38work/how-a-supply-chain-attack-made-me-sign-every-container-image-i-ship-c2e7391721db
One thing this project taught me is how many trade-offs exist in real ML systems:
Some parts were honestly frustrating to wire together, especially the policy enforcement side, but I learned a lot from it.
Repo if anyone wants to take a look:
https://github.com/blue-samarth/mlops-tryops
Would really appreciate thoughts from people working in MLOps or platform engineering:
Thanks in advance!
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.
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.
Hello people,
Wanting to connect with people who want to create something exceptional in cloud domain or who want to start their career I am trying to connect with people and building a community.dm me if you are one.
I am 18 and iam in first year of compsci engineering but I am side by side also preparing for my masters (ie trynna learn German) and learning linux commands, docker basics , basic networking and stuff.. what else should I learn I know basic python fundamentals
I tried to get into competitive programming but miserably failed, tried machine learning but 💀💔🙏🏿 math got me
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.
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.