Migration Services
Codimite migrates self-hosted Docker applications and services to Google Kubernetes Engine. Improve scalability, deployment reliability, and workload management through a secure, production-ready Kubernetes environment.
Scale with Kubernetes
Increase or reduce application replicas based on CPU, memory, custom metrics, or external workload signals.
Add or remove compute nodes as workload demand changes, reducing the need for manual capacity management.
Automatically restart failed containers, replace unavailable Pods, and reschedule workloads when nodes become unavailable.
Use rolling updates and rollback capabilities to release application changes while maintaining availability when workloads are configured correctly.
Use Kubernetes Services and DNS-based discovery to connect workloads and distribute traffic across application replicas.
Connect clusters, nodes, Pods, and containers with Google Cloud Monitoring and Cloud Logging.
Migration Process
Review Docker images, Compose files, hosts, services, dependencies, storage, networks, secrets, traffic, and resource usage.
Define the GKE architecture, operation mode, namespaces, networking, identity, storage, security, autoscaling, and observability approach.
Deploy a selected application to GKE and validate container compatibility, networking, storage, performance, and scaling.
Convert existing service definitions into Kubernetes Deployments, Services, configuration, secrets, storage, and autoscaling policies.
Complete functional, load, security, resilience, monitoring, and rollback testing before directing production traffic to GKE.
Why Codimite
Codimite combines Google Cloud, Kubernetes, container engineering, application modernization, security, and DevOps expertise to deliver controlled GKE migrations.
Talk to a Cloud Migration ExpertContainer Environment Assessment. We evaluate Docker hosts, images, Compose configurations, dependencies, traffic, storage, and operational risks.
GKE Architecture Design. We design clusters, namespaces, node strategies, networking, security, storage, scaling, and deployment models around your workloads.
Kubernetes Workload Conversion. We convert Docker services into suitable Kubernetes Deployments, Services, ConfigMaps, Secrets, Jobs, and storage resources.
Security and Access Planning. We configure identity, permissions, workload access, secrets, network controls, image policies, and security monitoring.
CI/CD and Observability. We build automated deployment pipelines and connect workloads with logging, metrics, dashboards, alerts, and rollback processes.
End-to-End Support. Codimite supports assessment, architecture, migration, testing, cutover, optimization, documentation, and knowledge transfer.
Comparison
| Comparison Area | Self-Hosted Docker | GKE Advantage |
|---|---|---|
| Container deployment | Containers are deployed and managed directly on individual hosts | ✓ Kubernetes manages containerized workloads across a cluster |
| Scaling | Capacity and container replicas may require manual changes or custom automation | ✓ Pod and cluster autoscaling can respond to workload demand |
| Host management | Teams provision, patch, monitor, and balance Docker hosts | ✓ GKE manages the Kubernetes control plane and offers managed operation modes |
| Availability | Application availability depends on host architecture and custom failover | ✓ Workloads can run across multiple nodes and zones |
| Failure recovery | Failed services may require host-level scripts or manual intervention | ✓ Kubernetes can restart containers and replace unavailable Pods |
| Deployment | Updates may require direct host or Compose workflow management | ✓ Deployments support rolling updates and rollback strategies |
| Networking | Service discovery and routing require host or external configuration | ✓ Kubernetes Services support discovery and traffic distribution |
| Monitoring | Logging and metrics require separately configured tools | ✓ Integrates with Cloud Logging and Cloud Monitoring |
| Infrastructure capacity | Teams plan and add server capacity | ✓ GKE can scale nodes and workloads based on demand |
FAQs
Not usually. Existing container images can often be retained, but deployment configuration, networking, secrets, storage, health checks, and operational workflows must be adapted for Kubernetes.
Yes. Compose files can help document services, ports, dependencies, volumes, and environment variables. However, production Kubernetes resources normally need to be redesigned around Deployments, Services, configuration, storage, and scaling requirements.
GKE can automatically scale Pods and cluster nodes when autoscaling is properly configured. Resource requests, scaling thresholds, application startup behaviour, and infrastructure limits must also be planned.
Autopilot provides a more managed cluster configuration, while Standard offers greater control over nodes and cluster settings. The right option depends on workload, security, networking, performance, and operational requirements.
Minimal or zero-downtime cutover may be possible through parallel environments, multiple replicas, readiness checks, rolling deployment, traffic switching, and rollback planning. The application must support this deployment model.
The timeline depends on the number of services, container quality, networking, persistent storage, security, dependencies, CI/CD requirements, and application complexity.
Identify which containerized services should move to GKE and build a secure, scalable Kubernetes migration roadmap.
Talk to a Cloud Migration Expert
