Overview
Kubernetes has become the de facto industry standard for container orchestration. Originally developed by Google and grown as open source under the CNCF (Cloud Native Computing Foundation), Kubernetes automates the deployment, scaling and management of containerized applications. However, the powerful capabilities Kubernetes offers also bring significant complexity. Getting cluster design, security configuration, network policies, storage integration and monitoring infrastructure right requires deep technical expertise.
Indexline's Kubernetes services cover the entire lifecycle, from production-ready cluster deployment to day-to-day operations management. Our engineers, experienced in on-premise Kubernetes (bare-metal or virtualized), managed Kubernetes services (EKS, AKS, GKE) and hybrid Kubernetes environments, design the solution that best fits your organization's infrastructure strategy. Our CKA (Certified Kubernetes Administrator) and CKAD (Certified Kubernetes Application Developer) certified engineers play an active role in every project.
Security is especially important in Kubernetes environments. Misconfigured RBAC policies, insecure container images or non-isolated namespaces pave the way for critical vulnerabilities. Indexline's Kubernetes security assessment covers network policy management, pod security standards, secrets management, image scanning and runtime security. Hardening work based on the CIS Kubernetes Benchmark puts your cluster on a secure foundation.
Observability is critical for Kubernetes clusters in production. We build a comprehensive monitoring and alerting infrastructure with leading tools from the CNCF ecosystem such as Prometheus, Grafana, Loki and Jaeger. Application metrics, infrastructure metrics, log streams and distributed tracing data are combined in a single observability platform. As a result, issues are detected and resolved before end users are affected.
How It Works
Infrastructure Assessment and Design: Your existing infrastructure, application architecture and team capabilities are assessed to determine the most suitable Kubernetes deployment model (on-premise, managed, hybrid).
Cluster Architecture: The number of control plane and worker nodes, hardware requirements, high availability configuration and network CNI choice (Calico, Flannel, Cilium) are designed.
Security Baseline: RBAC policies, network policies, pod security standards and secrets management (Vault integration) are configured. Container image security scanning is built into the pipeline.
Storage Integration: A persistent storage solution (Ceph, Longhorn, NFS, cloud native storage) is configured for StatefulSet applications. A storage class hierarchy is created.
CI/CD Integration: Existing CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions) are integrated into Kubernetes deployment processes. A GitOps approach (ArgoCD, Flux) is evaluated.
Observability Stack: Prometheus Operator, Grafana dashboards, Alertmanager rules and log aggregation (Loki or ELK) are set up.
Load Testing and Capacity Validation: Autoscaling is configured with HPA (Horizontal Pod Autoscaler) and VPA (Vertical Pod Autoscaler) and validated through load testing.
Key Features
HA Control Plane
An etcd cluster is configured with three or more control plane nodes, eliminating single points of failure in the control plane.
Autoscaling
Pod- and node-level autoscaling is configured with HPA, VPA and Cluster Autoscaler. Resource utilization is optimized.
Network Policy Management
East-west traffic is secured with granular network policies at namespace and pod level. A zero trust network model is applied.
Helm Chart Management
Application deployments are packaged as Helm charts, with environment differences managed through values files. Chart repository management is included.
Ingress & Service Mesh
External traffic management with NGINX or Traefik Ingress controllers; service mesh and mTLS configuration with Istio or Linkerd.
Security Scanning
Container image security scanning with Trivy or Snyk is integrated into the CI/CD pipeline. Critical CVEs are blocked at build time.
Multi-Tenant Management
A secure multi-tenant environment is configured for multiple teams or projects with namespace isolation, resource quotas and network policies.
Disaster Recovery
Backup of Kubernetes objects and persistent volumes is configured with Velero. Cluster state is backed up at regular intervals and recovery procedures are tested.
Benefits & Advantages
Application deployment time drops from hours to minutes; deployment pipeline automation significantly boosts developer productivity.
Autoscaling dynamically adjusts infrastructure capacity to actual demand, eliminating the cost of over-provisioning.
Self-healing mechanisms automatically restart failed pods, maintaining service continuity without operator intervention.
Infrastructure as Code eliminates environment inconsistencies, and "it worked on my machine" problems become a thing of the past.
A consistent platform is provided across multi-cloud and hybrid environments, avoiding cloud lock-in.
With monitoring and alerting infrastructure, issues are detected and resolved before they reach end users; MTTR (Mean Time to Repair) drops dramatically.
Industry Use Cases
Fintech & Banking
A fintech company moving to a microservices architecture now performs 50+ deployments a day with Kubernetes; service errors fell by 80%.
E-Commerce
During the high season, autoscaling increased capacity 20-fold while keeping infrastructure costs flat; Black Friday passed without any outage.
Health Technology
Applications processing health data were moved to the cloud on a HIPAA-compliant Kubernetes cluster, meeting compliance requirements.
Media & Broadcasting
Video processing workloads were run on Kubernetes using a GPU node pool; render time was cut by 60%.
SaaS Software
A multi-tenant SaaS platform was moved to Kubernetes with namespace isolation; infrastructure cost per customer fell by 45%.
Public Sector & Local Government
A digital government services platform was deployed on-premise on an air-gapped Kubernetes cluster, preserving data sovereignty.
The Indexline Approach
At Indexline, we avoid a "lift and shift" approach in Kubernetes projects. Rather than containerizing applications as they are, we work with the development team to restructure the application in line with cloud native principles. Although this approach requires more effort in the short term, it delivers a far more valuable result in the long term.
The most critical component of Kubernetes operations is in-house team capability. In every Kubernetes project, we run a comprehensive knowledge transfer and training program. In addition to theoretical training, we offer the opportunity to work through real scenarios in hands-on lab environments. Your team becoming able to manage the cluster independently is the key measure of success.
The Kubernetes ecosystem evolves rapidly. At Indexline, we closely follow CNCF projects and the Kubernetes release cycle, ensuring our customers stay on current, secure and supported versions. Cluster health is continuously monitored through our quarterly version assessment reports.
Frequently Asked Questions
Should we choose on-premise Kubernetes or a managed service?
This choice depends on your data sovereignty requirements, team capabilities and cost. On-premise provides full control and data sovereignty, but the operational burden falls on your team. Managed services such as EKS, AKS or GKE significantly reduce the operational burden but create cloud dependency. We help you decide by carrying out a cost-benefit analysis of both options.
Can we move our existing VM-based applications to Kubernetes?
Yes, but this process requires careful planning. Migration of stateless applications is usually quick and smooth. Stateful applications may require persistent storage configuration and possible architectural refactoring. We recommend a separate migration analysis for each application.
What are the most critical steps for Kubernetes security?
The most critical security steps include least privilege with RBAC, pod isolation with network policies, image security scanning, secrets management (Vault or external secrets), pod security standards and enabling audit logs. The CIS Kubernetes Benchmark is our reference point.
How should Kubernetes upgrades be managed?
Kubernetes' supported version policy covers the last three minor versions. Upgrades are performed as rolling updates, first the control plane and then the worker nodes. Testing each upgrade in a staging environment beforehand and preparing a rollback plan is standard practice.
How much hardware does Kubernetes require?
For a minimum production-ready cluster, three control plane nodes (each with 4 vCPU and 8GB RAM) and at least three worker nodes are recommended. Actual resource requirements depend on your workload profile. During the discovery phase, we size the cluster based on current load and growth projections.
Can we manage a microservices architecture together with Kubernetes?
Kubernetes and microservices architecture are a natural fit. Kubernetes features such as service discovery, load balancing, health checks and rolling updates greatly simplify the operation of microservices. With service mesh (Istio/Linkerd) integration, inter-service communication, security and observability are enhanced even further.
How can we manage Kubernetes with GitOps?
In the GitOps approach, Kubernetes cluster state is held as manifests defined in a Git repository. Tools such as ArgoCD or Flux treat Git as the single source of truth and keep the cluster synchronized with that state. This approach ensures that all changes are version-controlled, auditable and easily reversible.
How long does it take to build Kubernetes monitoring infrastructure from scratch?
A basic Prometheus + Grafana + Alertmanager stack can be deployed within a week. A full observability stack, including comprehensive dashboards, alert rules, log aggregation and distributed tracing, typically takes 3-4 weeks. Team training is included in this timeframe.