Kode Builder provides Kubernetes consulting services and DevOps engineering for teams running production platforms on AWS and other clouds. We design EKS clusters, build CI/CD and GitOps pipelines, implement Terraform infrastructure, and set up observability — while being candid about when simpler options like ECS or managed PaaS are the better choice for your stage and team.
Kubernetes and DevOps Services for Production Platforms
DevOps is not a tool — it is how your team ships software reliably. We help engineering organizations reduce deployment friction, improve incident response and build platform capabilities that let developers focus on features instead of infrastructure firefighting.
Our engagements range from greenfield platform design to rescuing clusters that grew organically without standards. Deliverables include working infrastructure, documented runbooks and knowledge transfer so your team can operate independently or with our managed support.
When Kubernetes Is the Right Choice—and When It Is Not
Kubernetes excels when you have multiple microservices, need portable deployments across environments, require sophisticated scaling and rollout strategies, or have a team ready to invest in platform engineering. It is often overkill when you run a monolith on a few containers, have predictable traffic, or lack operational bandwidth for cluster maintenance.
We assess your team size, service count, deployment frequency, compliance needs and growth trajectory before recommending EKS, ECS Fargate, App Runner or a hybrid approach. Honest advice builds trust — and saves you from a six-figure platform nobody can maintain.
Read Kubernetes for product teams: when you need it for a deeper decision framework.
EKS, GKE, AKS and Self-Managed Cluster Options
On AWS, Amazon EKS is our primary recommendation for Kubernetes workloads. We also support:
- EKS — managed control plane with AWS-native integrations (IAM, ALB, EBS CSI).
- GKE / AKS — for multi-cloud or client-mandated environments.
- k3s / self-managed — edge deployments or cost-sensitive smaller clusters.
Cluster design includes node group strategy (spot vs on-demand), networking (CNI choice, service mesh if needed), ingress controllers, cert-manager, external-dns and cluster autoscaling policies.
CI/CD, GitOps and Automated Deployment Pipelines
Manual deployments do not scale. We implement pipelines using GitHub Actions, GitLab CI, Jenkins or AWS CodePipeline — with:
- Automated testing gates (unit, integration, security scans)
- Container image building and registry management (ECR)
- Helm chart versioning and environment promotion
- GitOps with Argo CD or Flux for declarative cluster state
- Blue-green and canary deployment strategies
- Rollback procedures tested before you need them
Developers merge to main; pipelines handle the rest. Releases become boring — in a good way.
Terraform and Infrastructure as Code
ClickOps does not survive team growth. We write Terraform modules for VPCs, EKS clusters, RDS databases, S3 buckets, IAM roles and monitoring stacks. Infrastructure changes go through pull request review, plan/apply in CI, and state locking to prevent conflicts.
IaC enables reproducible environments — dev, staging and production share the same modules with different variable files. Disaster recovery becomes "terraform apply in a new region" rather than a multi-week rebuild from memory.
Observability, Logging, Metrics and Alerting
You cannot fix what you cannot see. We deploy observability stacks with:
- Metrics — Prometheus and Grafana, or Amazon Managed Prometheus.
- Logging — Fluent Bit to CloudWatch Logs or OpenSearch.
- Tracing — OpenTelemetry with Jaeger or AWS X-Ray.
- Alerting — PagerDuty, Opsgenie or SNS with tuned thresholds.
Dashboards cover golden signals (latency, traffic, errors, saturation) per service. Runbooks link from alert notifications so on-call engineers know what to check first.
Kubernetes Security, Reliability and Cost Control
Production clusters need guardrails:
- RBAC policies, network policies and pod security standards
- Secrets management with External Secrets Operator or Sealed Secrets
- Image scanning in CI and admission controllers
- Resource requests/limits and Horizontal Pod Autoscaler configuration
- Cluster upgrades planned and tested in staging first
- Cost monitoring with Kubecost or AWS Cost Explorer tags
Compare approaches in our Kubernetes vs AWS ECS guide.
Migration, Audit and Ongoing Platform Support
We help teams migrate from Docker Compose, ECS, bare VMs or legacy PaaS to Kubernetes — with phased cutover and parallel running. For existing clusters, we perform audits covering security posture, resource utilization, upgrade path and operational maturity, then deliver a prioritized remediation plan.
Ongoing support options include platform engineering retainers, on-call incident response and quarterly architecture reviews as your product scales.
Frequently Asked Questions About Kubernetes Consulting
Probably not yet. A single app on ECS Fargate, App Runner or even a well-managed EC2 instance is often simpler and cheaper. We recommend Kubernetes when service count, deployment complexity or portability requirements justify the operational investment.
A production-ready EKS foundation — cluster, networking, ingress, CI/CD, monitoring and first service deployment — typically takes 3–6 weeks depending on complexity and compliance requirements.
Yes. Helm is our default packaging tool, often combined with Argo CD or Flux for GitOps. We structure charts for environment-specific values and version-controlled releases.
Knowledge transfer is part of every engagement. We provide documentation, runbooks and hands-on sessions covering deployments, debugging, upgrades and incident response.
We evaluate whether migration benefits justify the effort. Many teams stay on ECS longer than expected. When EKS makes sense, we plan a phased migration with minimal downtime.