Frequent Solutions
☸️ Kubernetes Orchestration

Kubernetes That Your Team Can Actually Operate, Not Just Deploy To

We set up K8s clusters with GitOps, proper RBAC, autoscaling, and full observability — so your team has confidence deploying to production, not anxiety about what kubectl might break.

25+
K8s clusters
99.99%
uptime achieved
10x
traffic spikes handled
GitOps
native
📦 What We Do

End-to-End Kubernetes Setup & Management

From cluster provisioning to day-2 operations — we cover everything your team needs to run Kubernetes with confidence in production.

🏗️

Cluster Setup (EKS/GKE/AKS)

Managed Kubernetes on AWS EKS, Google GKE, or Azure AKS — or self-managed on bare metal. Node group configuration, add-on management, and cluster upgrades handled without downtime.

🔐

Namespace & RBAC Configuration

Namespaces per team or environment, RBAC roles that follow least-privilege. Developers can view and debug their namespace; they cannot accidentally kubectl delete everything in production.

📈

HPA & VPA Autoscaling

Horizontal Pod Autoscaler configured with custom metrics (not just CPU), Vertical Pod Autoscaler for right-sizing requests and limits, and Cluster Autoscaler to add and remove nodes automatically.

🌐

Ingress & Service Mesh

NGINX or Traefik Ingress with TLS termination and path-based routing. Istio or Linkerd service mesh for mTLS between services, traffic management, and circuit breaking when you need them.

Helm Chart Development

Helm charts for your applications with values files per environment. Proper chart structure so your team can deploy to staging and production with a single command and different configuration.

🔄

GitOps with ArgoCD/Flux

ArgoCD or Flux for declarative deployments from git. Every change to your cluster goes through a PR, is audited, and can be rolled back by reverting a commit — not by someone running kubectl in production.

📊

Monitoring with Prometheus/Grafana

kube-prometheus-stack deployed with pre-built dashboards for cluster health, node utilisation, and pod performance. Custom recording rules and alerting rules for your application SLOs.

💾

Persistent Storage & StatefulSets

StatefulSets for databases and stateful workloads, EBS/GCP PD/Azure Disk StorageClasses with proper reclaim policies, and Velero for cluster and PVC backup.

🗺️ How We Work

From Zero to Production-Ready

01
🔍

Workload Assessment

We review your current deployment setup — VMs, ECS tasks, bare Docker — and map each service to its Kubernetes equivalent. We also flag workloads that do not belong in K8s and recommend alternatives.

02
🏛️

Cluster Architecture Design

Node group sizing and types, networking model (CNI choice), add-ons list, multi-tenancy strategy, and cluster upgrade process documented before a single node is provisioned.

03
🚚

Migration & Helm Packaging

Application workloads packaged as Helm charts, migrated to the new cluster with parallel running and traffic shifting, verified against production traffic before old environment is decommissioned.

04
🔄

GitOps & Monitoring Setup

ArgoCD or Flux configured and syncing from your git repository. Prometheus and Grafana live. Alertmanager rules written and routed to your on-call channel. Runbooks documented.

💡 Why Choose Us

Why Businesses Trust Us with Their Kubernetes

⏱️

Five years of real K8s production experience

We have run Kubernetes in production long enough to know which features look good in demos but cause pain at scale — and which sharp edges to avoid when setting up a new cluster for the first time.

🔄

GitOps from day one

ArgoCD or Flux configured before anything else is deployed. Your cluster state lives in git. Deployments are auditable, diffs are reviewable, and rollbacks are a git revert away.

📊

HPA configured correctly

Not just CPU-based autoscaling — custom metrics from Prometheus (request rate, queue depth) where that is what actually drives load. We have seen CPU-based HPA miss real bottlenecks too many times.

🔒

RBAC properly scoped

Developers get exactly the permissions they need to do their job — no more. Production namespaces have approval gates. Cluster-admin is not handed out to developers who just want to check logs.

👁️

Observability that makes sense

Prometheus + Grafana dashboards organised by team and by service, not one wall of graphs. Alerting rules that fire on things that matter to your SLO, not every metric blip.

💰

Cost optimisation via spot and rightsizing

Spot instances for non-critical workloads, on-demand for stateful and latency-sensitive ones. Resource requests tuned with VPA data so you are not reserving 4 CPU for a service that uses 100m.

🚀 Get Started

Get Kubernetes Running Properly in 4 Weeks

We will scope your cluster, design the architecture, and deliver a production-ready setup with GitOps, monitoring, and runbooks — not just a cluster that works on day one.

Didn't Find What You Were Looking For?

We're here to help you get the answers you need, quickly and clearly.

ECS is simpler to operate if you are all-in on AWS and your team does not have Kubernetes experience. Kubernetes makes sense when: you need multi-cloud portability, you want GitOps tooling (ArgoCD, Flux), your team already knows K8s, or you have complex networking and scheduling requirements. We will recommend ECS over K8s if K8s is overkill for your use case — the operational overhead of K8s is real and not worth it for a 3-service application.

Managed K8s means the cloud provider runs the control plane (API server, etcd, scheduler) and you manage the worker nodes. Self-managed means you run everything. Unless you have a specific reason (cost at very large scale, hardware requirements, air-gapped environment), use managed. The control plane is not where problems happen — it is expensive to run well and not where you want to spend engineering time.

K8s is worth the operational overhead when: you have 5+ services that need to scale independently, you need sophisticated deployment strategies (canary, blue-green), you want GitOps-style deployment auditability, or you have teams that need namespace isolation. A 2-service app with predictable traffic can run on ECS, App Service, or even a few EC2 instances managed by Terraform. We will tell you when K8s is not the right answer.

A production EKS cluster setup with GitOps, monitoring, and team onboarding typically runs ₹1,50,000–3,00,000 depending on the number of services and existing infrastructure state. Ongoing managed support (upgrades, scaling events, incident response) is ₹30,000–80,000/month. The cluster infrastructure itself (EC2 nodes) is your cloud bill, which varies with workload.

A greenfield cluster with 3–5 services: 3–4 weeks. Migrating an existing 10-service application from VMs or ECS: 6–10 weeks, depending on how stateful the workloads are. Migrating a monolith that was not designed for containers requires application changes first, which we scope separately.

Our standard hardening includes: RBAC with least-privilege (no cluster-admin for application service accounts), Pod Security Standards enforced (no privileged pods in production), NetworkPolicies to restrict east-west traffic, Secrets management via External Secrets Operator with Vault or AWS Secrets Manager, OPA/Kyverno policies for admission control, and regular CIS Kubernetes Benchmark scanning. We also disable unused API server flags and rotate certificate authorities annually.

Still have questions? Contact us directly →

⭐ Client Stories

Trusted by Teams Across the Globe

Real results from real clients — across AI, SaaS, e-commerce, and enterprise projects.

Frequent Solutions delivered our AI voice calling agent on time and far exceeded expectations. The call quality is so natural our patients genuinely prefer it over speaking to staff. Their understanding of healthcare workflows was impressive — every detail was thought through.

David Martinez
David Martinez🇺🇸
CTO, TeleCare Health
📁 AI Voice Calling Agent