Kubernetes upgrades are often treated as infrastructure changes, but they can directly affect application deployments. An application may continue to run correctly while its deployment manifests, custom resources, CI/CD scripts, operators, or admission webhooks stop working as expected.
This is why API compatibility testing should be part of every Kubernetes upgrade plan.
When testing a Kubernetes 1.38 environment, developers should not only check whether existing pods start successfully. They should also verify the Kubernetes API resources used by the application and the tools responsible for deploying and managing it.
This article explains how to test applications against a Kubernetes 1.38 environment, identify API compatibility problems, and build a practical validation process before moving workloads to the upgraded cluster.
Why Kubernetes API Compatibility Matters
Kubernetes exposes an API that applications and platform tools use to communicate with the cluster.
Developers may interact with this API directly through clients, but most applications use it indirectly through tools such as:
For example, a deployment pipeline might execute:
kubectl apply -f deployment.yaml
The command looks simple, but behind it several API operations take place. If a resource definition, field, API version, or dependent controller behaves differently after an upgrade, the deployment can fail.
API compatibility testing helps detect these problems before production.
Start With an API Inventory
Before testing Kubernetes 1.38, identify the Kubernetes APIs your application environment actually uses.
Start by reviewing YAML files stored in application repositories.
For example:
apiVersion: apps/v1
kind: Deployment
metadata:
name: orders-api
spec:
replicas: 3
selector:
matchLabels:
app: orders-api
template:
metadata:
labels:
app: orders-api
spec:
containers:
- name: orders-api
image: example/orders-api:1.0
ports:
- containerPort: 8080
The important part for compatibility testing is not only the apiVersion. You should also review the resource kind, fields, annotations, labels, and custom resources used by the deployment.
Create an inventory containing:
Resource | API Version | Used By | Test Required |
|---|
Deployment | apps/v1 | Application | Yes |
Service | v1 | Application | Yes |
ConfigMap | v1 | Application | Yes |
Secret | v1 | Application | Yes |
Ingress | networking.k8s.io/v1 | Web application | Yes |
Custom Resource | Depends on operator | Platform | Yes |
CRD | apiextensions.k8s.io/v1 | Operator | Yes |
This inventory gives you a baseline for the upgrade test.
Check API Resources Available in the Cluster
Once the Kubernetes 1.38 test cluster is available, inspect the API resources exposed by the cluster.
kubectl api-resources
You can also inspect API versions:
kubectl api-versions
These commands provide a useful first-level comparison between the existing cluster and the Kubernetes 1.38 test environment.
For a resource you depend on, inspect its definition:
kubectl explain deployment
You can inspect specific fields as well:
kubectl explain deployment.spec
This is useful when reviewing manifests that depend on specific resource fields.
Validate Application Manifests
The next step is to test application manifests against the new cluster.
A basic server-side validation can be performed with:
kubectl apply --dry-run=server -f deployment.yaml
This sends the request to the Kubernetes API server without actually creating the resource.
This is more useful than relying only on local YAML validation because the Kubernetes API server performs the actual schema and admission checks.
For multiple manifests:
kubectl apply --dry-run=server -f ./k8s/
If the command succeeds, you have confirmed that the API server accepts the submitted resources under the current validation rules.
However, this should not be considered a complete compatibility test. The resource must still be deployed and exercised as part of the application workflow.
Test Helm Charts
Helm charts are another important source of Kubernetes API compatibility problems.
A chart may generate Kubernetes manifests dynamically based on values supplied during deployment.
Render the chart before applying it:
helm template orders-api ./chart \
--values ./chart/values.yaml
Then inspect the generated manifests.
You can also send the generated output through Kubernetes validation:
helm template orders-api ./chart \
--values ./chart/values.yaml |
kubectl apply --dry-run=server -f -
This is particularly useful in CI/CD because it tests the actual manifests generated by the Helm chart rather than only the source templates.
Test Custom Resources and Operators
Many production Kubernetes environments depend on custom resources.
For example, an operator might define a resource such as:
apiVersion: example.io/v1
kind: Database
metadata:
name: orders-db
spec:
replicas: 3
storage:
size: 20Gi
The Kubernetes API server may accept this object, but that does not mean the application is working correctly.
The operator must also reconcile the resource.
Test the complete lifecycle:
Create the custom resource.
Confirm that the operator detects it.
Check the resulting Kubernetes resources.
Modify the custom resource.
Confirm that the operator reconciles the change.
Delete the resource.
Verify that cleanup happens correctly.
Inspect the operator logs when troubleshooting:
kubectl logs deployment/example-operator -n operators
Also check the custom resource:
kubectl get database orders-db -o yaml
This helps separate API acceptance problems from controller or reconciliation problems.
Test Admission Webhooks
Admission webhooks can reject requests before Kubernetes creates or updates a resource.
If your environment uses validating or mutating webhooks, test them explicitly.
For example:
kubectl get validatingwebhookconfigurations
kubectl get mutatingwebhookconfigurations
Then deploy a normal application resource and verify that the expected mutation or validation occurs.
Also test an invalid request.
For example, if your policy requires CPU and memory limits, submit a workload without those settings and verify that the policy rejects it.
This is important because an API upgrade can expose compatibility problems in webhook clients, certificates, service endpoints, or request handling.
Test CI/CD API Operations
Application compatibility testing should include the deployment pipeline.
A pipeline might perform operations such as:
kubectl apply -f ./k8s/
kubectl rollout status deployment/orders-api
kubectl scale deployment/orders-api --replicas=5
kubectl rollout undo deployment/orders-api
Test each operation against the Kubernetes 1.38 cluster.
Do not test only kubectl apply.
A production deployment pipeline usually performs several API operations before and after deployment.
Pay particular attention to scripts that parse command output or API responses.
For example, this type of automation can become fragile:
kubectl get pods -o json | jq '.items[].metadata.name'
Prefer structured API responses and explicit fields rather than relying on human-readable command output.
Test API Clients
If your application or internal tooling communicates directly with Kubernetes, test the client library against the new cluster.
For example, a service might use a Kubernetes client to list pods:
var config = KubernetesClientConfiguration.BuildConfigFromConfigFile();
var client = new Kubernetes(config);
var pods = await client.CoreV1
.ListNamespacedPodAsync("default");
foreach (var pod in pods.Items)
{
Console.WriteLine(pod.Metadata?.Name);
}
The important test is whether the client library version supports the Kubernetes API behavior used by your application.
Do not assume that because kubectl works, every application using a Kubernetes client library will also work.
Review client-library compatibility separately.
Compare Behavior, Not Just API Versions
API version comparison is useful, but behavior testing is more important.
For example, an application should be tested for:
Area | Test |
|---|
Deployment | Create and update workload |
Service | Verify service discovery |
Ingress | Verify HTTP and HTTPS routing |
ConfigMap | Confirm configuration injection |
Secret | Confirm secret consumption |
Scaling | Increase and decrease replicas |
Rollout | Verify rollout completion |
Rollback | Restore previous version |
CRD | Create and update custom resource |
Webhook | Validate accepted and rejected requests |
CI/CD | Execute complete deployment pipeline |
This approach tests what the application actually depends on rather than simply checking whether the API server starts.
Common API Compatibility Problems
Unsupported API Version
A manifest may reference an API version that is no longer supported.
The result can look like:
no matches for kind "Example" in version "example.io/v1beta1"
The solution is to identify the supported API version and update the manifest or dependency responsible for generating it.
Removed or Changed Fields
A resource can continue to use a supported API version while individual fields cause validation failures.
Use:
kubectl explain <resource>
to inspect the current schema.
Custom Resource Compatibility
The Kubernetes API server may accept a custom resource while the operator fails to process it.
In this situation, check the operator version and reconciliation logs rather than changing application code immediately.
Webhook Failures
Webhook failures can prevent otherwise valid resources from being created.
Check:
kubectl get events -A --sort-by='.lastTimestamp'
Then inspect the webhook service, pods, logs, and certificates.
Best Practices for Kubernetes API Testing
Maintain Kubernetes manifests in version control so compatibility testing can be repeated consistently.
Use an isolated test cluster that closely resembles the production environment.
Run server-side dry-run validation in CI/CD before allowing workloads to move toward production.
Test both standard Kubernetes resources and custom resources.
Include negative tests for admission policies and validation rules.
Test the complete deployment lifecycle rather than only resource creation.
Keep Kubernetes client libraries and operators under explicit dependency management.
Record compatibility failures and the exact Kubernetes resource involved. This makes troubleshooting much faster during the production upgrade.
Most importantly, test the APIs your organization actually uses. There is little value in spending significant time validating unused Kubernetes features while overlooking the CRDs, webhooks, operators, and deployment automation your applications depend on.
Troubleshooting Checklist
When an application fails against the Kubernetes 1.38 test environment, check the problem in this order:
Verify the resource API version.
Check whether the resource kind exists.
Validate the manifest with server-side dry run.
Inspect Kubernetes events.
Check admission webhook errors.
Inspect operator or controller logs.
Verify client-library compatibility.
Test the same operation manually with kubectl.
Compare the working cluster with the Kubernetes 1.38 test cluster.
Re-run the deployment after correcting the identified dependency.
This approach helps determine whether the problem is caused by the Kubernetes API, an external controller, deployment tooling, or the application itself.
Advantages and Disadvantages
Advantages | Disadvantages |
|---|
Finds API compatibility issues early | Requires a separate test environment |
Reduces upgrade surprises | Testing takes additional engineering time |
Validates CI/CD workflows | Third-party components may require separate testing |
Identifies CRD and operator problems | Some failures require vendor updates |
Improves migration planning | Test environments can differ from production |
Summary
Testing applications against Kubernetes 1.38 should go beyond checking whether pods start successfully. The Kubernetes API is used by application manifests, Helm charts, operators, admission webhooks, CI/CD systems, client libraries, and platform automation.
Start by creating an inventory of the APIs and resources your applications depend on. Validate manifests with server-side dry runs, test Helm-generated resources, verify custom resource reconciliation, and exercise admission webhooks and deployment automation.
Most importantly, test complete application workflows. A Kubernetes upgrade is successful only when the applications and the surrounding platform tooling continue to perform the operations they depend on.
A structured API compatibility test gives development and platform teams a clearer picture of upgrade risk and provides concrete evidence for deciding whether an environment is ready for the next stage of the Kubernetes upgrade process.
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