Kubernetes (K8s) and containers have become just about every developer’s bread and butter for building, deploying, and scaling applications. But let’s be real—using K8s in the cloud-native race isn’t always a walk in the park. In fact, even though K8s automates a lot of the heavy lifting, there are still plenty of ways to stumble. 

Sure, you got it working right the first time. But in Cloud native, with great power comes great flexibility. In K8S, things change faster, and that's when they go sideways. Managing resources while maintaining workload stability is easier said than done. 

So, if you’ve ever found yourself wondering why your Kubernetes workloads are causing more headaches than expected, buckle up. We'll take a quick look at the key situations that can trip you up when scaling microservices and offer a few simple fixes that could make your life easier (and if nothing else, offer fewer surprises). And by the way, there’s a lot more to explore in this space—definitely something we’ll cover in our upcoming webinar. 

Key Causes of Kubernetes gotchas (and How to avoid them)

1. Cluster Over-/Under-Provisioning: “Why is everything either slow or burning money?”

When setting up your K8s cluster, it’s easy to go overboard and throw way more resources at it than necessary. Or worse, under-provision it and watch everything crash under load. This is like going to a buffet and either piling your plate so high you can't finish or leaving the table still hungry. 

Gotcha moment: You’ve got more nodes than you need or fewer than your app demands.

A better way: Start by monitoring your actual resource usage with tools like Prometheus, (for extra credit,  Perfectscale or Goldilocks). Then, scale things back to a closer approximation or reality using Cluster Autoscaler to dynamically adjust your nodes to just the right size. You'll reduce waste and avoid performance issues. 

2. Over/Under Allocation of Pod Resources: “Why is my pod hogging all the RAM?”

Allocating too many resources (CPU, memory) to your pods can lead to waste, but if you don’t allocate enough, you’ll have pods gasping for air like they’re stuck in a cramped elevator. And if you’ve got hundreds of microservices, suddenly a handful of greedy pods can turn into gridlock

Gotcha moment: One pod is eating up all your cluster’s memory while others starve.

A better way: Use Kubernetes resource limits to define clear requests and limits for each pod. Just like rationing snacks on a road trip, make sure every service gets what it needs without hogging it all.

3. Missing or Incorrect Scaling Policies: “Wait, Where did all these new pods come from?!”

Let’s say your app’s traffic spikes, and instead of scaling to meet demand, your K8s cluster is like a deer in headlights. Or worse, you’ve set up autoscaling but overcompensated, so you end up with a ridiculous number of pods that are barely running.

Gotcha moment: Your app either buckles under load or spawns unnecessary pods like there’s no tomorrow.

A better way: Set up a Horizontal Pod Autoscaler (HPA) to scale pods based on actual traffic. But, heads-up: you’ll want to ensure the triggers you’re using (like CPU usage) actually reflect your real-world needs.

4. No Resource Limits: “Why did this one service crash everything?”

Imagine a pod decides it’s the center of the universe and starts grabbing as much CPU and memory as possible. Without limits in place, it might just succeed—at the cost of everything else. This is where not having resource limits feels like leaving your credit card with a friend who promises to be careful.

Gotcha moment: One runaway pod crashes your entire cluster or depletes resources.

A better way: Always define both resource requests and limits for CPU and memory in your manifests. It’s like putting a leash on your pods so they don’t run wild.

5. Garbage Collection and Orphaned Resources: “Who left these behind?”

Kubernetes clusters can get cluttered with leftover resources (like old persistent volumes, orphaned pods, or unused config maps) that nobody seems to remember. These orphaned resources sit around, eating up space and making your cluster more bloated than a half-finished Jenga game no one cleaned up.

Gotcha moment: Your cluster is filled with zombie resources that just won’t quit.

A better way: Implement a solid labeling and ownership strategy from day one. It’s kind of like labeling your lunch in the office fridge—make sure there’s accountability and ownership so people know who’s responsible for cleanup.

6. Container Compatibility Chaos: “Why did this container just break everything?”

When working with microservices, one team’s small change to a container might break dependencies with other services. With Kubernetes, it's easy to have each container optimized differently, but that flexibility can quickly turn into a nightmare when builds fail because of mismatched libraries or incompatible updates.

Gotcha moment: One container config update breaks the whole system due to dependency conflicts.

A better way: Use ofing GitOps and Infrastructure as Code (IaC) helps prevent these issues by ensuring all changes are tracked, versioned, and consistent across environments. Tools like CGDevX further streamline this by automating application delivery and enforcing consistency across teams, so everyone stays on the same page, builds succeed, and releases stay on schedule.

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The Big Takeaway: Start Small, Scale Smart

Kubernetes is an incredible tool for scaling cloud-native workloads, but it’s also full of hidden potholes and stumbling blocks. Under- or over-allocating resources, missing autoscaling configurations, and leaving junk behind are all common mistakes that can throw a wrench into your day. But there are definitely best practices—like proper autoscaling, setting resource limits, and maintaining good ownership practices—that can go a long way in keeping your workloads happy and your cluster running smoothly.

And if you’ve ever wondered if there’s more to these best practices (spoiler alert: there is), we’ve got a whole lot more coming your way in our upcoming webinar with our partners at PerfectScale.. We’ll dive deeper into more the nitty-gritty best practices and optimization strategies that’ll help keep you on your toes  and keep your Kubernetes environments going for the long run.

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