Running an application in Kubernetes is one thing, but supporting that application in Kubernetes environments your customers run is something else entirely. You don’t control the cluster configuration, its upgrade schedule, the surrounding tooling, or the process for investigating an incident. But customers will still look to you when your application won’t install, an upgrade breaks, or a workload behaves differently in their environment than they expected.
That doesn’t mean customer-managed Kubernetes deployments can’t work, but it does mean support has to account for the variation you’ll see in real clusters.
You’ll definitely have two customers (or more!) who both say they run Kubernetes and yet have very different environments.
One may run a managed Kubernetes service in a public cloud. Another may operate its own infrastructure. They may use different Kubernetes versions, networking configurations, ingress controllers, storage classes, image registries, security policies, observability tools, or access controls.
Those differences affect how your application deploys and how your team supports it. A chart that installs cleanly in your reference architecture may fail because a customer’s admission policies reject a required permission, their storage configuration doesn’t meet your application’s requirements, or their cluster runs a Kubernetes version you haven’t tested yet or no longer support.
Unfortunately, your customer still experiences that as a problem with your application. That’s why your team needs a documented view of what the application requires from the cluster, and what falls outside the support boundary.
At a minimum, customers need to know:
The goal isn’t to make every customer environment identical (you can’t). Instead, you need to define a supported operating model so every deployment doesn’t turn into a new discovery process for your customer support team.
Your application roadmap may assume customers will move to newer Kubernetes versions quickly. A quick reality check: most won’t.
Customers have their own release schedules, validation processes, maintenance windows, compliance requirements, internal dependencies, and risk thresholds. Even when they want to upgrade, their platform team may have a long list of cluster add-ons, integrations, and workloads to validate first.
Like any other software, Kubernetes and different components in its ecosystem change over time. APIs are deprecated and removed, version compatibility varies across control-plane and node components, and the upstream project supports release branches for only the three most recent minor releases.
Your team needs a compatibility policy that answers a few basic questions:
If the answer to every compatibility problem is to update Kubernetes, customers will quickly find that your support isn’t aligned with how they operate. Your team needs to explain what’s incompatible, why it matters, and the easiest path to return to a supported configuration.
A general application support team can’t diagnose every Kubernetes issue. When a product runs inside a cluster your customer manages, customer-facing teams need enough Kubernetes depth to identify where the problem really lives.
That doesn’t mean every support employee has to operate production clusters. It does mean someone working directly with customers needs to understand the difference between an application issue, a deployment-configuration issue, and a cluster-level issue.
For example, a pod stuck in Pending may point to unavailable capacity, resource requests that don’t fit on available nodes, a scheduling constraint, or a policy that prevents placement. An image pull failure may involve registry access, credentials, network connectivity, or image policy enforcement. Those details determine who needs to take the next action and what evidence they need to act on it.
Your customer-facing team needs dedicated Kubernetes expertise that can:
Getting accurate answers to these questions matters because the person opening a support case may not own the cluster. The application team probably owns the deployment. A platform team probably owns Kubernetes. Security owns policies. Another infrastructure team may own networking, storage, or identity. Someone on your team needs to help move the issue between those groups.
You can’t control every Kubernetes environment where customers run your application. You can control whether your support model treats that variation as expected or as a surprise.
So make sure you have a plan for it by:
The support model changes when a provider manages the Kubernetes layer alongside the customer. Instead of troubleshooting an application across an unknown mix of cluster configurations, versions, networking, and add-ons, the provider and customer can work from a more clearly defined operating foundation.
With Fairwinds Managed Kubernetes-as-a-Service, Fairwinds manages the Kubernetes layer, including core infrastructure, networking, add-on upgrades, DNS, and monitoring in partnership with the customer. That gives application teams a more consistent operating foundation while they remain responsible for their applications.