Kubernetes Done Right: Part 2 The Costs of Doing it Wrong

Kubernetes done right and what happens when it’s not.

Part 2. The Costs of Doing it Wrong

Welcome back to our “Doing Kubernetes Right” series. In our previous post, we explored the technical and operational challenges that can undermine Kubernetes deployments—from inadequate resource management and security misconfigurations to insufficient monitoring and backup strategies. Getting these fundamentals right is crucial for building a stable, secure platform that your development teams can rely on.

However, technical excellence is only part of the equation. Even the most robust Kubernetes deployment can become a business liability if it’s not financially sustainable. This brings us to a critical question that many organisations grapple with: how do you balance the undeniable benefits of Kubernetes with its potentially significant costs?

The financial landscape of Kubernetes is more complex than many initially realise. Beyond the obvious expenses of infrastructure and tooling, there are hidden costs that can quickly spiral: over-provisioned resources running idle, inefficient workload placement, expensive data egress charges, and the often-underestimated expense of the specialist expertise required to manage it all effectively.

In this second post, we’ll dissect the true cost of different Kubernetes deployment models—from managed services to self-hosted solutions. We’ll shine a light on those hidden expenses that can catch organisations off-guard and, most importantly, demonstrate how strategic optimisation can transform Kubernetes from a cost centre into a genuine competitive advantage.

Whether you’re evaluating your first Kubernetes deployment or looking to optimise an existing environment, understanding these financial considerations is essential for making informed decisions that deliver both technical and business value.

Consideration 1: On-Premise or On-Cloud

While self-managed Kubernetes on bare metal might appear to be a cheaper option, because of the one-off hardware cost (or the ability to repurpose existing on-premise hardware), there is the potential for these configurations to incur significant long-term expenses. Organisations pay fixed monthly costs whether the computing resources are 100% or 0% utilised, so there is wasted investment in unused capacity, especially during off-peak hours.

One major consideration when self-hosting Kubernetes is the technical expertise required and resources required to manage the environment. Scaling up requires significantly more effort, as does patching e.g. security updates which can be fully automated in cloud. Configuring ingresses controllers (allowing traffic into the cluster) can also be challenging when self-hosting.

In cases where organisations operate in both on-premise and cloud-based services (for example, Content Delivery Networks like Cloudflare or Google CDN), integration of containers across the two can be technically challenging with many more services to integrate. As well as the initial cost of the complex integration, ongoing maintenance will account for an additional expense.

On the other hand, managed Kubernetes in the cloud typically operates on a pay per node per hour model. While a cloud deployment may be more expensive to run per node per hour, the ability to dynamically scale down to a lot fewer nodes (say, from 30 to five nodes during non-peak hours or during times of the year when demand is less) results in significant overall cost savings, as resources are consumed only when needed.

Help is at hand: At DeeperThanBlue, we help organisations conduct thorough cost-benefit analyses when considering a move to containers or migration from on-premise to managed cloud Kubernetes. We’ll highlight how the flexibility and dynamic scaling of cloud environments can lead to reduced total cost of ownership, even if the hourly rate per node appears higher.

Consideration 2: Optimisation and Automation

It is possible to unlock significant cost efficiencies by correctly optimising container configurations and automating scaling processes.

A major hidden cost in the deployment of a containerised environment is the misconfiguration of container resource limits. In such cases, active pods will place excessive demands for computing power from a node—more than they actually need to operate. As a result, node resources are wasted and other pods are prevented from utilising the capacity that would otherwise be available, forcing additional new and unnecessary nodes to be spun up.

Cloud providers offer businesses a range of node sizes. It might be tempting to opt for the largest node size you can afford, this could lead to a significant amount of redundancy, particularly during quiet periods. It is therefore important for businesses to consider selecting node sizes that give them the ability to deploy pods across the environment and give them the flexibility to scale up when demand increases.

We’ve spoken about the importance of scaling resources up and down depending on demand. However, relying on manual scaling means reacting to traffic spikes, which can be slow and lead to either over-provisioning (to cope with potential peaks) or performance degradation (if scaled too late).

Kubernetes environments can deploy a feature called Kubernetes Event-Driven Autoscaling (KEDA), which allows for the automatic addition or removal of nodes and pods based on real-time metrics like CPU usage or site performance. This ensures that resources are always aligned with demand, leading to optimal cost efficiency.

Help is at hand: DeeperThanBlue’s expertise lies in auditing and tuning new and existing Kubernetes configurations to ensure optimal resource allocation and utilisation. We help configure pods with precise memory and CPU requests to maximise efficiency, ensuring we get as many pods running on a node as possible.

Furthermore, we’ll implement auto-scaling rules for cloud-based Kubernetes clusters, enabling dynamic cost management by scaling resources up during peak times and automatically scaling them back down during quiet periods, thereby reducing overall spend.

Summary

Our second blog post in the “Doing Kubernetes Right” series focused on the financial implications of Kubernetes deployments, exploring how even robust systems can become a business liability if not managed sustainably. We illuminated various hidden costs and how strategic optimisation can transform Kubernetes from a cost centre into a genuine competitive advantage.

We explored two key financial considerations and how DeeperThanBlue helps organisations navigate them:

• On-Premise or On-Cloud Deployment: While self-managed Kubernetes on bare metal might appear cheaper initially, fixed monthly costs mean wasted investment in unused capacity. In contrast, managed cloud Kubernetes (pay-per-node) allows for dynamic scaling down, leading to significant overall cost savings by consuming resources only when needed. DeeperThanBlue conducts cost-benefit analyses to highlight how cloud flexibility reduces Total Cost of Ownership.
• Optimisation and Automation: Misconfiguration of container resource limits is a major hidden cost, forcing the spin-up of unnecessary new nodes. Relying on manual scaling is also inefficient. DeeperThanBlue specialises in auditing and tuning Kubernetes configurations for optimal resource allocation and utilisation. We also implement auto-scaling rules (like KEDA) for cloud-based clusters, enabling dynamic cost management by scaling resources up and down with demand, reducing overall spend.

The core message of this post is that understanding these financial considerations and implementing strategic optimisation is essential to transform Kubernetes into a genuine competitive advantage.

Conclusion: Getting Kubernetes Right – A Holistic Approach

This two-part series on “Kubernetes Done Right” has highlighted that achieving success with Kubernetes requires a holistic approach, addressing both its technical and operational complexities alongside its financial implications. While the first part focused on critical technical and operational pitfalls—from outdated deployments and fixed resource allocation to inadequate high availability, unoptimised nodes, and bypassing native services—the second part shed light on the equally crucial financial landscape. We’ve seen how common mistakes, whether technical missteps or poor financial planning, can lead to fragile, insecure, and unexpectedly costly deployments, consuming valuable time and resources.

The good news is that these challenges are largely preventable. By leveraging the right expertise and adopting a strategic approach, organisations can avoid common pitfalls and ensure their Kubernetes environments deliver robust performance, ironclad security, and true business value. DeeperThanBlue, as a Kubernetes Certified Service Provider, offers comprehensive support across all these areas. From unpicking labyrinthine configurations and optimising resource utilisation to implementing robust HA/DR plans and strategically managing cloud costs through dynamic scaling and automation, we help ensure your containerised environment is not just technically sound but also financially sustainable.

Ultimately, getting Kubernetes right isn’t just about deploying technology; it’s about delivering genuine business value through cost-effective, scalable solutions that truly meet your demands and transform your operations into a competitive advantage.

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