Release Channel
Channel enrollment, installed version, and support coverage are different facts. Plan tests and upgrades using the exact target version and service policy.
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Version Skew
A kubelet three minors behind can block the next control-plane minor upgrade. That limit does not itself block a patch within the current minor.
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Network Policy
Ingress-only policy does not change egress isolation. Test allowed and blocked paths, and distinguish Pod deletion from confirmed process termination.
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Kubernetes Isolation, Policy, and Upgrades
Additive permissions still deny unallowed access. Verify quota enforcement, policy scope and the distinction between minor upgrades and security patches.
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Readiness Probe
Readiness affects endpoint eligibility without restarting a container. Existing connections, publishing settings and routing delays still matter.
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Kubernetes Networking, Storage, and State
Follow PVCs to their PV policies, distinguish endpoint readiness from traffic cutoff, and budget hooks and cleanup together during shutdown.
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Label Selector
Selectors identify matching objects; owner references record control relationships. Compare labels, endpoints, and intended membership when diagnosing errors.
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Control Loop
Continuous reconciliation can coexist with completed rollouts and Jobs. Observe progress, controller health, and service outcomes separately.
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Desired State
A recorded target needs a working reconciler. Check completion, managed scope, and repeated effects rather than treating acceptance as success.
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How Kubernetes Reconciles Declared State
An accepted manifest starts reconciliation. Confirm the intended rollout, inspect failures, and verify service behavior before declaring a release successful.
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GPU Scheduling and Resource Isolation
A GPU cluster can show free devices and still be unable to start a job. This guide covers GPU memory and compute, placement and fragmentation, gang scheduling, quotas with borrowing, sharing modes and their isolation limits, and capacity under failure, with local simulations.
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Running Data Workloads on Kubernetes
A batch job on Kubernetes can be restarted, replaced, skipped, or started twice. This article explains the Pod, Job, and CronJob rules behind that, how requests and limits decide placement and failure, and what the program must do to stay correct.
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GPU Fragmentation
A cluster can report plenty of idle GPUs while a job waits, because the idle devices are scattered across nodes. Packing, reservation, and defragmentation keep large blocks of free capacity available.
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Gang Scheduling
Gang scheduling admits a group of interdependent workers only when all of them can be placed together. It prevents jobs from holding resources while waiting for each other, at the price of waiting for a large enough block of free capacity.
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Resource Requests and Limits
Distinguish resource requests used for placement from runtime limits, interpret CPU and memory differently, and measure demand before setting values.
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Kubernetes Pod
Understand a Pod as a scheduling unit, distinguish container restart from Pod replacement, and keep durable output separate from an attempt’s identity.
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Kubernetes Job and CronJob
Separate finite work from scheduled Job creation, scope concurrency and deadline policies, and keep repeat-safe output independent of controller success.
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Platform Unit Economics and Cost Controls
A platform bill is one number. Learn to allocate it, divide it by a workload unit that drives cost, price headroom and commitments, and tune without breaking objectives.
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Kubernetes vs. Managed Services Comparison
The right runtime depends on the workload, the team, and what each provider actually operates. This guide builds an evaluation from workload needs, burden, boundaries, tests, cost, and migration triggers.
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Operating Shared Kubernetes Clusters
A shared cluster saves capacity and creates shared fate. This guide covers isolation, quotas, admission policies, version compatibility, staged upgrades, and what rollback can and cannot undo.
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Kubernetes Networking and Stateful Workloads
Pods are replaceable, but their addresses, names, and data are not. This guide follows traffic and storage from Service to disk, then shows how to diagnose and recover.
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Kubernetes Controllers and Workload Lifecycle
Kubernetes keeps workloads running by repeatedly comparing declared intent with observed state. This post explains controllers, probes, scheduling, and failure recovery.