Kubernetes & Amazon EKS consultant — clusters built to survive production and audit.

What you get

Proof

How an EKS engagement runs

Most teams call me at one of two moments: the first production cluster is due and nobody wants to guess at the network model, or an existing cluster has grown organically and now blocks an audit, a cost target, or a release cadence. Both start the same way — I map what you actually run before touching Terraform.

What a hardened EKS baseline actually includes

"Hardened" gets used loosely. Here is what it means concretely on the clusters I build, and why each piece is there.

Private networking by default

Worker nodes sit in private subnets with no public IPs. The Kubernetes API endpoint is private, or public with a CIDR allowlist when a managed CI runner genuinely needs it. This single decision removes an entire category of finding from every audit I have taken a client through, and it costs nothing at build time — retrofitting it later means rebuilding the cluster.

IRSA instead of node roles

IAM Roles for Service Accounts binds a role to a specific service account rather than to the node. Without it, every pod on a node inherits that node's permissions, which means your logging sidecar can read the same S3 buckets as your payments service. IRSA is the difference between least privilege as a diagram and least privilege as a fact.

VPC endpoints, which pay for themselves

Routing ECR pulls, S3 access, CloudWatch logs and STS calls through VPC endpoints keeps that traffic off the NAT gateway. On one AI lending platform this removed roughly $1,800 a month in NAT data processing charges while also shrinking the egress surface. Security and cost usually pull against each other; this is one of the rare places they agree.

Admission control and image provenance

Pod Security Standards enforced at the namespace level, network policy for east-west traffic, and Trivy scanning in the pipeline so a critical CVE fails the build rather than surfacing in a quarterly report. Admission policy is where you encode the rules you would otherwise write in a wiki nobody reads.

EKS or ECS — a straight answer

I get asked this in almost every discovery call, and the honest answer is that most teams running a handful of stateless services on AWS do not need Kubernetes. ECS with Fargate has a fraction of the operational surface: no control plane version to chase, no addon compatibility matrix, no node lifecycle to manage.

EKS earns its overhead when you need the ecosystem — operators, CRDs, service mesh, GitOps tooling that assumes Kubernetes primitives — or when portability across clouds is a real constraint rather than a hypothetical one. It also earns it when you already have Kubernetes expertise in the building, because the operational cost drops sharply when the team has seen these failure modes before.

I have written this comparison out properly, with the cost and operational-overhead numbers, in EKS vs ECS: which AWS container platform fits your team. If you are still deciding, start there — and if the answer turns out to be ECS, I will tell you that on the call rather than sell you a cluster.

Keeping EKS costs honest

Kubernetes makes it easy to spend money quietly. Requests get copied from a tutorial, nodes get provisioned for a peak that happens twice a year, and nobody notices until finance does. The levers that actually move the bill, roughly in order of impact:

If cost is the primary driver rather than a secondary one, my AWS cost optimization work goes wider than the cluster — reserved capacity, storage lifecycle, data transfer and the account-level waste that Kubernetes tuning cannot reach.

Upgrades: the part teams postpone

Amazon supports each EKS minor version for a limited window, after which you are moved to extended support and billed for the privilege. Clusters that skip upgrades do not stay still; they accumulate addon drift, deprecated APIs and a growing gap that makes each subsequent jump harder.

The approach that works is boring and repeatable: read the deprecated-API report before touching anything, upgrade the control plane first, then roll node groups with surge capacity so workloads drain rather than restart in place. Addons — VPC CNI, CoreDNS, kube-proxy, EBS CSI driver — get version-pinned and upgraded deliberately, because a compatible-in-theory addon is how a routine upgrade turns into an incident. On clusters I run, upgrades are scheduled quarterly and rehearsed in a non-production account first.

Turning a cluster into audit evidence

If you are heading for SOC 2 or ISO 27001, your cluster is not just infrastructure — it is a source of evidence, and auditors ask for it in a predictable shape. Access control maps to IRSA bindings and RBAC role definitions. Change management maps to git history plus ArgoCD's reconciliation record, which is stronger evidence than a ticketing system because it cannot be edited after the fact. Vulnerability management maps to scan results in the pipeline with a demonstrable remediation SLA. Logging and monitoring map to retention configuration and alert routing.

Building those exports while the cluster is being built costs very little. Reconstructing them the month before an audit costs a great deal, and usually surfaces gaps that need engineering work at exactly the wrong moment. This is the overlap between my DevOps and compliance work and the ISO 27001 and PCI DSS engagements — the platform and the evidence are the same project, run once.

Ship on Kubernetes without the 3AM surprises.

Free 30-minute call — tell me your workloads and I'll map a hardened EKS path.