Kubernetes Alternatives for When You Don't Need All That Bullshit

I was an idiot and ran up my AWS bill to something completely fucked - several thousand bucks, I don't even want to think about it - trying to run a simple PHP app on Kubernetes because I thought it would look "professional" on my resume. Turns out enterprise buzzwords don't pay the rent.

Why Your Server Keeps Running Out of RAM

So here's the thing nobody tells you about Kubernetes: it eats RAM like it's going out of style. The official docs say 4GB minimum but that's just for the control plane to not immediately crash. I found this out the hard way when my cheap DigitalOcean box kept dying with OOMKilled errors every few hours.

When you're trying to run anything on a Raspberry Pi or some crappy VPS, Kubernetes eats like half your RAM just sitting there doing nothing.

My stupid edge project was bleeding money on AWS - like close to a grand a month for 20 different locations running full K8s. When I switched to K3s on Raspberry Pis, it dropped to maybe a couple hundred a month after buying all the hardware. That's rent money right there.

The official K3s requirements are way more reasonable:

• K3s server: needs maybe 2GB RAM, works fine with whatever CPU you've got
• K3s agent: can run on 512MB RAM or less if you're not doing anything crazy
• Regular Kubernetes: wants 4GB+ just to boot up, before you run anything useful

My Local Development Pain Points

I used to run Minikube on my MacBook Pro. It had 16GB RAM which sounds like a lot until Docker Desktop and Minikube eat like 6-7GB just sitting there. Throw in VS Code, Chrome with approximately 47 tabs, and Slack, and my laptop starts sounding like it's about to take off.

What actually works without killing your laptop:

• K3d: K3s running in Docker containers. Starts fast, uses maybe 1GB RAM for a whole 3-node cluster
• Kind: Good for CI/CD pipelines, terrible for daily development because it's slow as molasses
• Colima: Kicked Docker Desktop off my Mac, uses way less RAM
• Podman: No stupid daemon running in the background, works great on Linux

With K3d I can run a whole cluster, VS Code, and Chrome without my laptop having a nervous breakdown. Try that with full Kubernetes and you're screwed.

Real gotcha: The K3s installer sometimes fails silently and you waste an hour wondering why kubectl isn't working. Always check the logs first: journalctl -u k3s

IoT Projects That Actually Work

I've deployed containers on everything from Raspberry Pi Zeros (512MB RAM) to industrial PCs in factories. Here's what I learned:

Skip orchestration entirely for simple IoT:

• Single container? Just use systemd and docker run. Don't overcomplicate it.
• Multiple containers? Docker Compose works fine and uses way less resources.
• Need clustering? That's when K3s makes sense.

Real IoT deployments I've done:

• Environmental sensors: K3s on Pi 4 running TensorFlow Lite for edge ML
• Factory monitoring: Podman on Red Hat CoreOS, no daemon needed
• Remote cameras: Just Docker Compose. K8s would be overkill and waste power.

Power consumption is a real pain when you're running stuff remotely. A Pi running K3s draws like 5-10W max. Full Kubernetes on some beefy x86 machine? That's 50-100W easy. If you're running on solar or battery, full K8s will drain your power budget fast.

Why Everyone Thinks They Need Kubernetes

Here's the truth: most teams don't need Kubernetes. They think they do because:

1. Job requirements list it - "Must know K8s" is on every DevOps job posting
2. Conference hype - Every talk is about scaling to Netflix levels
3. Vendor marketing - Cloud providers make more money selling managed K8s
4. Resume-driven development - Engineers want K8s experience

But if you're running 5 services with 10,000 users, Docker Swarm or even systemd will work fine. I've seen teams spend 6 months setting up Kubernetes for a PHP app that could run on a $5 VPS.

When to Use What (Based on Real Experience)

Use simpler alternatives when:

• Your server has less than 4GB RAM - Full K8s will eat everything
• It's just you or a small team - Complex orchestration is overkill
• You're prototyping - Don't waste time on enterprise bullshit you don't need
• You're paying the power bill - Edge deployments, IoT, dev laptops
• You want to understand what's actually happening - Less magic, more learning

Use full Kubernetes when:

• You have >100 services - At this scale, you need the complexity
• Multiple teams - Namespaces, RBAC, and multi-tenancy actually matter
• Compliance requirements - Enterprise security policies, auditing
• You already have K8s experts - Don't fix what isn't broken

Skip orchestration entirely for:

• Single applications - systemd + docker run works fine
• Static sites - Just use a CDN, what are you doing?
• Databases - Run PostgreSQL directly, not in containers
• Legacy apps that don't containerize well - Stop forcing it

Most projects start simple and get complex over time. Begin with Docker Compose, move to K3s when you need clustering, upgrade to full Kubernetes when you actually hit its limits. Don't start with the enterprise solution for a side project.

Kubernetes isn't the only way to run containers. Sometimes the best orchestration is no orchestration at all. Here's what I actually use when K8s is way too much.

Podman: Docker Without the Daemon Bullshit

Podman doesn't run a daemon. That means when you're not running containers, it uses zero resources. Docker Desktop sitting in your system tray? That's 2GB RAM gone even when idle.

I switched to Podman after Docker daemon shit the bed again and took out all my containers. Maybe the third time that month? With Podman, each container is its own process. One crashes, the others don't give a fuck and keep running.

Why I like Podman:

• No daemon means no crashes - Docker daemon dies, all containers die with it
• Rootless containers work - No more sudo everywhere, better security
• Same commands as Docker - alias docker=podman and you're done
• systemd integration - Containers can start at boot without Docker daemon

Podman has some rough edges though. The networking can be weird as hell on some distros, Docker Compose files sometimes break for no reason, and the docs are written for people who already know Docker really well. But when it works, it's solid and won't randomly die on you.

Setting Up Podman the Right Way

Skip podman-compose. It's janky and breaks randomly. Instead, use systemd to manage your containers:

Gotcha: Podman networking is still weird as hell on some distros. If containers can't talk to each other, try podman network create and explicitly assign networks.

## Generate systemd service files from running containers
podman run -d --name myapp nginx:alpine
podman generate systemd --files --name myapp

## Enable the service
sudo cp container-myapp.service /etc/systemd/system/
sudo systemctl enable container-myapp.service
sudo systemctl start container-myapp.service

This creates proper systemd services that start at boot, restart on failure, and integrate with Linux logging. Way more reliable than compose files.

Docker Swarm: Actually Pretty Good

Swarm isn't dead, whatever the Kubernetes fanboys tell you. I use it for small production deployments because it's simple and actually works.

Swarm mode is just Docker with clustering. No separate control plane, no etcd, no bullshit. You run docker swarm init and suddenly you have orchestration.

Why Swarm doesn't suck:

• Zero overhead - It's built into Docker Engine already
• Secrets management works - No HashiCorp Vault needed
• Overlay networking just works - No CNI plugins to debug
• Load balancing included - Built-in ingress controller

I deployed a WordPress site with Redis and MySQL using Swarm. Total setup time: 20 minutes. Trying the same with Kubernetes would take hours.

## Create a 3-node Swarm cluster
docker swarm init --advertise-addr 192.168.1.100

## On worker nodes:
docker swarm join --token <token> 192.168.1.100:2377

## Deploy your app:
docker stack deploy -c docker-compose.yml wordpress

The main downside? Nobody gives a shit about Swarm on resumes. But if you need something that works without giving you headaches, Swarm is solid.

Just Use systemd (Seriously)

For single-node deployments, systemd beats every container orchestrator on resource usage. It's already running on your Linux box, knows how to restart services, handles dependencies, and integrates with logging.

I run several production services this way. A Go web app, a PostgreSQL container, and a Redis container. All managed by systemd, zero orchestration overhead.

## /etc/systemd/system/webapp.service
[Unit]
Description=Web Application Container
After=docker.service
Requires=docker.service

[Service]
Type=notify
ExecStart=/usr/bin/docker run --rm --name webapp -p 80:8080 myapp:latest
ExecStop=/usr/bin/docker stop webapp
Restart=always
RestartSec=30

[Install]
WantedBy=multi-user.target

Why systemd works:

• Reliability - systemd has restarted services for decades, it knows what it's doing
• Dependencies - Start database before web app, systemd handles ordering
• Logging - journalctl -u webapp shows all your app logs
• Resource limits - Built-in cgroup controls for CPU/memory limits
• Zero overhead - systemd is already running anyway.

When You Don't Need Containers At All

Sometimes the best container solution is no containers. If you're running a simple web app, a binary + systemd might be better than containerizing everything.

Consider skipping containers for:

• Single binary applications - Go/Rust apps that compile to static binaries
• Simple Python/Node apps - pip install or npm install works fine
• Legacy applications - Don't force containerization, just run them normally
• Databases - PostgreSQL installed directly is faster and easier to backup

I've seen teams containerize a PHP app that could run fine with Apache + mod_php. They spent weeks debugging volume mounts and networking when apt install apache2 php would work better.

I watched this team spend like 3 months trying to containerize some ancient .NET app - hardcoded file paths everywhere, registry bullshit, probably written in 2003. They could've just slapped it on Windows Server and called it a day.

My Actual Recommendations

For development: Use K3d if you need K8s compatibility, Colima if you just want Docker without Docker Desktop.

For single-node production: systemd + Docker containers. It's boring, reliable, and uses minimal resources.

For multi-node but simple: Docker Swarm. Dead simple clustering without K8s complexity.

For edge/IoT: K3s on devices with >2GB RAM, systemd + containers on smaller devices.

For "enterprise": Just use regular Kubernetes. Don't fight it, you'll need the features eventually.

The key insight: start simple, add complexity when you actually need it. Don't begin with enterprise solutions for side projects. Don't containerize everything because it's trendy. Use the right tool for the job, even if that tool is boring.