DevOps
Kubernetes
Kubernetes Engineering Teams, On Demand.
Production-grade Kubernetes engineering without the hiring bottleneck. Our engineers design, deploy, and operate clusters running mission-critical workloads — from multi-tenant SaaS platforms to real-time data pipelines. We serve infrastructure teams across the United States, Germany, Netherlands, and the wider EU, with 4–6 hours of daily timezone overlap and fully GDPR-compliant processes for regulated industries.
Use Cases
What we build with Kubernetes.
Multi-Tenant SaaS Infrastructure
Namespace-isolated Kubernetes clusters that serve hundreds of tenants with resource quotas, network policies, and per-tenant ingress routing. We design control planes that let your platform team onboard new customers without manual intervention. Deployed for fintech platforms in New York and healthtech companies in Frankfurt meeting strict data residency rules.
Microservices Migration
Decompose monolithic applications into Kubernetes-native microservices with proper service discovery, circuit breaking, and distributed tracing. We handle the incremental migration — running legacy and new services side by side — so your users never notice the transition. Successfully executed for logistics companies in Rotterdam and e-commerce platforms in the US Midwest.
CI/CD Pipeline Infrastructure
Self-hosted runner pools on Kubernetes for GitHub Actions, GitLab CI, and Jenkins that autoscale based on queue depth. Ephemeral build environments with cached layers and artifact storage reduce build times by 60–80%. Used by engineering teams in Berlin and Stockholm who needed EU-hosted CI infrastructure for compliance.
Real-Time Data Processing
Kubernetes-orchestrated streaming pipelines with Kafka, Flink, or Spark running on dedicated node pools with GPU support where needed. Horizontal Pod Autoscaler tuned for throughput metrics ensures you're never over-provisioned. Built for adtech platforms processing 500K+ events per second across US-East and EU-West regions.
Edge & Multi-Cluster Deployments
Federation across cloud providers and on-premise data centers using Cluster API or Rancher. Workloads route to the nearest cluster for low-latency responses while a central control plane maintains consistency. Deployed for IoT platforms in the Netherlands and retail chains with edge nodes across 12 European countries.
Disaster Recovery & High Availability
Active-passive and active-active cluster topologies with Velero-based backup, cross-region failover, and automated recovery runbooks. RPO under 5 minutes and RTO under 15 minutes for critical workloads. Designed for banking infrastructure in the EU and healthcare platforms in the US requiring strict uptime SLAs.
Expertise
How we work with Kubernetes.
Cluster Architecture & Management
We design clusters sized for your workload profile — node pools, taints, tolerations, affinity rules, and topology spread constraints that balance cost and reliability. Managed Kubernetes on EKS, GKE, and AKS, or bare-metal with kubeadm for on-prem requirements. Every cluster ships with monitoring via Prometheus, alerting via Alertmanager, and dashboards in Grafana.
Helm Charts & GitOps
Parameterized Helm charts with environment-specific values, dependency management, and automated rollback on failed health checks. ArgoCD or Flux for GitOps — every cluster state change is a pull request, auditable and reversible. We maintain chart repositories and upgrade strategies that keep your releases predictable across staging and production.
Service Mesh & Networking
Istio, Linkerd, or Cilium service mesh implementations with mTLS, traffic splitting, canary deployments, and observability baked in. Network policies that enforce zero-trust between namespaces. Ingress controllers (NGINX, Traefik, or Gateway API) configured for TLS termination, rate limiting, and geographic routing.
Security & RBAC
Cluster hardening with Pod Security Standards, OPA Gatekeeper policies, and image scanning in the CI pipeline. RBAC configurations scoped to teams with audit logging for every API server call. Secrets management via External Secrets Operator syncing from AWS Secrets Manager, HashiCorp Vault, or Azure Key Vault.
Autoscaling & Cost Optimization
Horizontal Pod Autoscaler with custom metrics, Vertical Pod Autoscaler for right-sizing, and Cluster Autoscaler or Karpenter for node-level scaling. Spot/preemptible instance strategies that cut compute costs 40–70% without compromising availability. We implement resource requests and limits that prevent noisy-neighbor problems across shared clusters.
Why us
Why TBI for Kubernetes.
Productive from Day One
Our Kubernetes engineers have operated clusters in production across EKS, GKE, and AKS for years. They arrive familiar with common failure modes, scaling bottlenecks, and security pitfalls — no ramp-up period where they're learning CRDs on your dime.
AI-Augmented Infrastructure
Every engineer uses AI-native workflows — Cursor, Copilot, and custom LLM tools — to generate Helm templates, debug pod scheduling issues, and write OPA policies. This measurably accelerates infrastructure-as-code delivery and catches misconfigurations before they reach production.
US & EU Timezone Overlap
Our engineers maintain 4–6 hours of daily overlap with both US Eastern and Central European timezones. Morning incident triage with your New York SRE team or afternoon architecture reviews with your Munich platform team — we flex to your on-call schedule.
GDPR & Infrastructure Compliance
For European clients, we ensure clusters run in EU regions with data residency controls, encrypted etcd, and audit-ready logging. Data Processing Agreements, namespace-level isolation, and network policies that meet regulatory requirements are part of our standard delivery — not an afterthought.
Related
Our Kubernetes teams often ship with.
FAQ
Common questions.
How much does it cost to hire a dedicated Kubernetes engineer offshore?
Our Kubernetes engineers start at $5,500/month for a full-time dedicated engineer. Senior platform engineers with deep experience in cluster operations, Helm, and service mesh range from $7,000–$10,000/month depending on specialization. This includes full integration with your tools (GitHub, Slack, PagerDuty), daily standups, and monthly flexibility to scale. Compared to a US-based Kubernetes engineer at $170,000–$220,000/year, you're looking at 60–70% cost savings with equivalent operational quality.
How fast can a Kubernetes engineer be onboarded to my infrastructure?
Most engineers are productive within 3–5 days. Before onboarding, we match engineers to your specific setup — cloud provider, cluster version, GitOps tooling, monitoring stack, and deployment strategy. They arrive having reviewed your cluster architecture and runbooks, so the first meaningful infrastructure change typically ships within the first week.
How do your engineers handle Kubernetes upgrades and zero-downtime deployments?
We follow a rolling upgrade strategy — control plane first, then node pools with PodDisruptionBudgets ensuring minimum available replicas throughout. For Kubernetes version upgrades, we test against your workloads in a staging cluster, validate API deprecations, and upgrade Helm chart dependencies before touching production. Blue-green and canary deployment patterns are standard for application workloads.
Are your Kubernetes operations GDPR-compliant for European clients?
Yes. We sign Data Processing Agreements with all European clients and ensure clusters run exclusively in EU regions (eu-central-1, eu-west-1, or equivalent GKE/AKS regions). Etcd encryption at rest, network policies isolating tenant data, audit logging for API server calls, and encrypted inter-node communication via service mesh mTLS are standard. Our engineers understand data residency requirements for regulated industries.
What timezone overlap do your engineers have with US and European teams?
Our engineering team is based in India (IST, UTC+5:30), providing 4–6 hours of overlap with Central European Time and 3–4 hours with US Eastern Time during standard working hours. For infrastructure teams, we structure on-call handoffs so critical cluster operations happen during overlapping hours. During incidents or maintenance windows, our engineers flex their schedules to provide extended coverage.
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