APIWEBQUEUE
PRODUCTION KUBERNETES · MANAGED BY RUK-COM
Kubernetes built
for every scale
Your team focuses on applications. Ruk-Com helps architect and operate the cluster—from control plane, workers, network and storage to AIOps and incident response.
HASpread workloadsHPA + NodesTwo-level scalingAIOpsExpert governed
DATA PLANELive request path
◎Users / APIHTTPS
WAFFilter threats
Load BalancerHealthy targets
IngressTLS · Routes
Kubernetes ServiceRoutes only to Ready endpoints
APIWEBJOB
+ POD+ PODREADY
CONTROL PLANEManages the cluster, outside user traffic
Managed by Ruk-ComHA Control Plane3×
API ServerSchedulerControlleretcd
CSI StoragePersistent VolumeObservabilityMetrics · Logs · EventsPolicyRBAC · NetworkPolicy
PRODUCTION BLUEPRINT
Every layer a production cluster needs
We begin with availability, failure domains, security boundaries and recovery objectives before sizing machines—so Kubernetes supports the business, not merely runs containers.
WAF · Load Balancer · Ingress
Traffic entry, TLS termination, routing and health-aware delivery.
HA Control Plane
API server, scheduler, controller and etcd designed for continuity.
Multiple Node Pools
Separate pools by workload, CPU/RAM, GPU, taints and failure domains.
CSI · Snapshot · Backup
Persistent volumes, storage classes and recovery plans shaped around state.
SELF-HEALING · NODE FAILURE
A node fails. Desired state continues.
Kubernetes does not live-migrate a running Pod. Controllers maintain replica count, the scheduler places replacement Pods on available capacity, and Services remove unready endpoints from traffic.
- Readiness and startup probes matched to the application
- Replicas, PodDisruptionBudgets and topology spread
- Stateful recovery designed with the storage layer
SERVICEhealthy endpoints
NODE APOD 01POD 02NotReady
NODE BPOD 03POD 04Ready
NODE CPOD 05CAPACITYReady
Controller + SchedulerCreate replacement Pod
- 01DetectNode NotReady
- 02ReconcileDesired replicas
- 03ScheduleHealthy capacity
- 04RouteReady endpoints
TWO-LEVEL AUTOSCALING
Scale Pods and capacity with demand
HPA reacts to CPU, memory or custom metrics. Node autoscaling provisions workers when new Pods remain pending for capacity.
Requests ≠ LimitsSet accurate requests so the scheduler and autoscaler can estimate capacity.Policy + StabilizationControl scaling behavior and keep it inside budget guardrails.
PVC200 → 500 GB
StorageClass · CSI
Ruk-Com Storage PoolCapacity · Replication · Snapshot
PERSISTENT DATA
Expand storage through a Kubernetes workflow
When a workload needs more space, the team can resize its PVC, sending the request through the StorageClass and CSI to the Ruk-Com storage pool without changing the application deployment model.
Place state deliberatelyExpansion depends on CSI driver, StorageClass and filesystem support. Snapshots, backups and DR are separate layers that need their own design.
FULL-FUNCTION PLATFORM
Features for platform teams and enterprises
Modules are shaped around each organization's workload and compliance needs, so every enabled capability remains operable.
Cluster Lifecycle
Provisioning, version planning, upgrades, certificates and control-plane operations.
Workload Autoscaling
HPA, appropriate VPA use, custom metrics and event-driven scaling.
Node Pools
Multiple sizes, labels, taints, affinity, GPU and capacity guardrails.
Zero-trust Controls
RBAC, namespace boundaries, NetworkPolicy, image policy and secret integration.
Observability
Metrics, logs, events, traces, SLO dashboards and alert routing.
Data Protection
CSI volumes, snapshots, backup policy, etcd backups and recovery drills.
Delivery & GitOps
Registry, CI/CD, rolling updates, canary/blue-green and rollback strategy.
Governance
Quotas, LimitRange, policy as code, audit logs, cost allocation and capacity reviews.
RUK-COM AIOPS + KUBERNETES EXPERT
See signals early.
Correlate before acting.
AIOps brings together metrics, logs, events and cluster changes to surface patterns spread across many screens. Experts validate context and act through agreed runbooks and permissions.
Discuss managed operationsMETRICS LOGS EVENTS CHANGES
Ruk-Com AIOpsCorrelate · Prioritize · Recommend
01Validate context02Select runbook03Act within scope
EXPERT SUPPORT
One team across cluster and application
During an incident, we do not stop at “infrastructure is healthy.” We trace evidence across capacity, network, storage, manifests and application behavior.
Platform operations
- Control plane & node lifecycle
- Cluster network & CSI integration
- Monitoring, alerting & capacity
- Upgrade & incident coordination
Production readiness
- Requests, limits & probes
- Scaling policy & SLO
- Release and rollback plan
- Backup & recovery drill
Application ownership
- Source code & business logic
- Image and dependencies
- Data classification
- Acceptance and release decision
FROM WORKLOAD TO PRODUCTION
Start with the workload, not a template
- 01DiscoverWorkloads, dependencies, traffic and RTO/RPO
- 02ArchitectTopology, security, node pools and storage
- 03Build & ValidateDeploy, load test, failure test and recovery
- 04OperateObserve, tune, upgrade and review capacity
TECHNICAL FAQ
Questions before production
Does a Pod migrate automatically when a worker fails?
Kubernetes creates a replacement Pod on an available node; it does not live-migrate the existing runtime. Recovery time depends on node detection, image pulls, probes, startup and workload storage.
Does autoscaling add both Pods and machines?
HPA changes replica count from metrics. Node autoscaling adds workers when new Pods lack capacity. Both require aligned resource requests and policies.
Can every persistent volume expand without downtime?
Not always. Support depends on the CSI driver, StorageClass, access mode, filesystem and application. The team validates the path before execution.
Does AIOps make every cluster change autonomously?
AIOps correlates signals, prioritizes findings and recommends or runs only authorized runbooks. Material changes still follow permissions, approval paths and service scope.
BUILD YOUR PRODUCTION CLUSTER
Share your current architecture.
We will map the path to Kubernetes.
Begin with workloads, traffic, dependencies, compliance and recovery objectives to assess topology, capacity and the right managed-service scope.