Demystifying FinOps for Containers

While containers have revolutionised how we build, deploy, and scale applications, they’ve also introduced unique challenges for cost management. Let’s dive into what containers are, why they’re a FinOps headache, and how we can address those challenges to make your cloud environment leaner, greener, and more cost-efficient.

What Are Containers?

Containers are lightweight, portable units that package up an application’s code, dependencies, and runtime environment. They run consistently across different computing environments, whether on your laptop, in a data centre, or in the cloud. Popularised by tools like Docker and orchestrated at scale by Kubernetes, containers allow developers to focus on coding without worrying about the underlying infrastructure.

They sound perfect, right? Some of my friends in the DevOps space say they’re not useful in the slightest, just go serverless, but plenty of people use them anyway and from a cost perspective, they’re not as simple as they seem.

The Challenges Containers Bring to FinOps

1. Cost Visibility: The Fog of Cloud-Native

One of the most common complaints from FinOps practitioners is the lack of cost visibility in containerised environments. Containers themselves don’t have a direct cost; they run on nodes (virtual machines or physical servers), which are billed by cloud providers. Kubernetes further abstracts these costs, distributing workloads across nodes and dynamically scaling resources. This means it’s often unclear which team or service is responsible for what share of the bill.

Without clear visibility, it’s challenging to allocate costs accurately, which makes it hard to encourage accountability or optimise spending.

2. Overheads at Every Level

Another issue is the tendency to build in overheads. Developers often provision containers with more CPU and memory than needed “to be safe.” Teams might allocate excessive node pools or leave pods idling in staging environments, and organisations may allow clusters to grow unchecked. Multiply these inefficiencies across hundreds or thousands of containers, and you’re looking at significant waste.

Reducing Costs with Better Awareness and Visibility

The first step to tackling container costs is creating awareness. Developers, engineers, and decision-makers need to understand that their choices in container resource allocation and cluster scaling impact the bottom line. FinOps teams should work to:

• Enable Cost Transparency: Use tools like Kubernetes cost allocation (e.g., Kubecost, CloudHealth, or native tools from cloud providers) to attribute costs to namespaces, pods, and teams.
• Set Guardrails: Introduce policies for resource requests and limits, preventing teams from overprovisioning.
• Promote Accountability: Share clear cost reports with teams to drive awareness and ownership.

Once you have visibility, you can start optimising. That’s where pod and node-level efficiency come into play.

What Is Pod Usage Optimisation?

Pods are the smallest deployable units in Kubernetes, running one or more containers. Pod usage optimisation involves ensuring that pods are using their allocated resources efficiently.

Here’s how it helps:

• Reduce Resource Waste: By fine-tuning CPU and memory requests/limits, you can prevent overprovisioning. For example, if a pod requests 4 CPUs but uses only 1, the remaining 3 CPUs are wasted, even though you’re paying for them.
• Avoid Performance Bottlenecks: Under-provisioned pods can cause crashes or performance issues. Optimising resource requests ensures a balance between cost and reliability.

Tools like Vertical Pod Autoscaler (VPA) can automatically adjust resource requests based on actual usage, helping you strike the right balance.

What Is Node Optimisation?

Nodes are the infrastructure that runs your pods. Node optimisation ensures you’re using this infrastructure as efficiently as possible. Here’s how:

1. Utilise Spot Instances

Spot instances (or preemptible VMs) offer significant cost savings compared to on-demand instances. By running non-critical workloads on spot instances, you can drastically reduce costs. Kubernetes makes this easier with tools like Cluster Autoscaler and node pools that can intelligently balance spot and on-demand usage.

2. Improve Node Utilisation

Nodes are often underutilised because of poor workload distribution. Kubernetes’ default scheduler isn’t always optimal, so it’s worth experimenting with:

• Binpacking: Packing workloads tightly onto fewer nodes to reduce idle resources.
• Custom Schedulers: Using tools or configurations to improve how workloads are distributed.

3. Right-Size Your Nodes

Choose instance types that match your workloads. Oversized nodes lead to wasted resources, while undersized nodes can cause performance issues. Regularly review your node pool configurations to ensure they’re aligned with actual demand.

Putting It All Together

Containers may have complicated the FinOps landscape, but with the right tools and mindset, you can manage their costs effectively. By focusing on cost visibility, resource optimisation at the pod and node levels, and fostering a culture of financial accountability, you can turn your containerised environment from a cost sink into a cost-efficient powerhouse.

As with any FinOps initiative, the key is collaboration. Developers, DevOps, and finance teams must work together to understand, monitor, and control container costs. With shared responsibility and the right practices in place, you can enjoy the benefits of containers without blowing your budget.