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        "title": "Review CPU and memory allocatable before adding Kubernetes workloads",
        "summary": "Compare node capacity with allocatable resources and the reservations for Kubernetes and operating-system daemons. Review optional reservation enforcement separately from the workload budget.",
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        "potentially_affected": "Kubernetes node administrators reviewing Node Allocatable and kubelet reservations for CPU, memory and local ephemeral storage; validate the installed runtime and configuration.",
        "dse_recommendation": "DSE recommends reconciling reported allocatable resources with separately owned daemon reservations before increasing workload placement.",
        "primary_source": {
            "name": "Kubernetes — Reserve Compute Resources for System Daemons",
            "url": "https://kubernetes.io/docs/tasks/administer-cluster/reserve-compute-resources/",
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        "content_html": "<p><strong>Bottom line:</strong> Use the node resource budget actually exposed to workloads when planning additional placement. Keep physical capacity, daemon reservations and eviction headroom in separate rows so available hardware is not mistaken for an unrestricted Pod allowance.</p>\n<h2>Source fact: documented behavior</h2>\n<p>The <a href=\"https://kubernetes.io/docs/tasks/administer-cluster/reserve-compute-resources/\" target=\"_blank\" rel=\"noopener noreferrer\">Reserve Compute Resources for System Daemons</a> documentation is the primary reference.</p>\n<p>Node <code>Allocatable</code> represents compute resources available to Pods, and the scheduler does not oversubscribe that value. <code>kubeReserved</code> is intended for Kubernetes system daemons rather than daemons running as Pods, while <code>systemReserved</code> covers operating-system daemons and should include kernel memory. Resources reserved for the documented hard-eviction headroom are unavailable to Pods.</p>\n<h2>What the source does not establish</h2>\n<p>This article reviews the workload budget for CPU, memory and local storage. It supplies no universal reservation size or recommendation to enforce limits on critical operating-system services. Keep the separate PID budget, explicit CPU-set assignment and cgroup-driver selection under their own procedures. A reconciled capacity worksheet does not establish application throughput or node recovery.</p>\n<h2>Applicability questions</h2>\n<ul>\n<li>What capacity and allocatable values does the node report?</li>\n<li>Which daemons belong to each reservation category?</li>\n<li>What observed demand supports the chosen reservations?</li>\n<li>Which eviction headroom and optional enforcement settings are intended?</li>\n</ul>\n<h2>DSE recommendation: explain the difference before adding workloads</h2>\n<p>DSE recommends reconciling reported allocatable resources with separately owned daemon reservations before increasing workload placement.</p>\n<p>Build one worksheet for each materially different node configuration. Record physical capacity, reported allocatable resources, managed kubelet settings and the workloads eligible to land there. Identify which configuration system owns the values. Preserve an unexplained difference instead of correcting it with an emergency node edit that bypasses that source of truth.</p>\n<p>Have the platform and operating-system owners allocate responsibilities for their daemons. Review representative demand during ordinary operation, maintenance and expected workload density. Keep services deployed as Pods in the appropriate workload assessment rather than silently charging them twice to a daemon reservation. Size proposed headroom from the agreed operating case and measurements.</p>\n<p>Separate reserving capacity from deciding how strongly daemon groups should be constrained. Obtain the exact supported cgroup and recovery procedure before enabling additional enforcement. Review the effect on essential node services with their owner, and retain a way to recover an incorrectly constrained test node.</p>\n<p>Recalculate the proposed workload budget after an approved configuration change and compare it with the reported value. If eligible nodes differ, determine how workload placement should account for that difference before approving a denser rollout.</p>\n<h2>Verification and evidence</h2>\n<p>Proposed verification, not performed: use a representative nonproduction node and a bounded disposable workload. Capture capacity, allocatable resources, the reviewed reservation configuration and the workload requests before making any approved adjustment.</p>\n<p>Predict the new budget, apply the managed change through its supported workflow and read the node values again. Compare the result with the worksheet and separately observe essential daemon responsiveness. Stop the exercise if recovery access or an agreed resource margin is threatened; do not exhaust a shared node to prove a subtraction. Retain node identity, configuration revision, calculation, actual values and unresolved differences for another administrator to reconstruct.</p>\n<h2>Official references</h2>\n<ul>\n<li><a href=\"https://kubernetes.io/docs/tasks/administer-cluster/reserve-compute-resources/\" target=\"_blank\" rel=\"noopener noreferrer\">Reserve Compute Resources for System Daemons</a> — Kubernetes.</li>\n</ul>\n<p>Source review completed October 29, 2026. Recheck the official documentation and deployment-specific applicability before a production change.</p>\n",
        "content_text": "Bottom line: Use the node resource budget actually exposed to workloads when planning additional placement. Keep physical capacity, daemon reservations and eviction headroom in separate rows so available hardware is not mistaken for an unrestricted Pod allowance.\nSource fact: documented behavior\nThe Reserve Compute Resources for System Daemons documentation is the primary reference.\nNode Allocatable represents compute resources available to Pods, and the scheduler does not oversubscribe that value. kubeReserved is intended for Kubernetes system daemons rather than daemons running as Pods, while systemReserved covers operating-system daemons and should include kernel memory. Resources reserved for the documented hard-eviction headroom are unavailable to Pods.\nWhat the source does not establish\nThis article reviews the workload budget for CPU, memory and local storage. It supplies no universal reservation size or recommendation to enforce limits on critical operating-system services. Keep the separate PID budget, explicit CPU-set assignment and cgroup-driver selection under their own procedures. A reconciled capacity worksheet does not establish application throughput or node recovery.\nApplicability questions\n\nWhat capacity and allocatable values does the node report?\nWhich daemons belong to each reservation category?\nWhat observed demand supports the chosen reservations?\nWhich eviction headroom and optional enforcement settings are intended?\n\nDSE recommendation: explain the difference before adding workloads\nDSE recommends reconciling reported allocatable resources with separately owned daemon reservations before increasing workload placement.\nBuild one worksheet for each materially different node configuration. Record physical capacity, reported allocatable resources, managed kubelet settings and the workloads eligible to land there. Identify which configuration system owns the values. Preserve an unexplained difference instead of correcting it with an emergency node edit that bypasses that source of truth.\nHave the platform and operating-system owners allocate responsibilities for their daemons. Review representative demand during ordinary operation, maintenance and expected workload density. Keep services deployed as Pods in the appropriate workload assessment rather than silently charging them twice to a daemon reservation. Size proposed headroom from the agreed operating case and measurements.\nSeparate reserving capacity from deciding how strongly daemon groups should be constrained. Obtain the exact supported cgroup and recovery procedure before enabling additional enforcement. Review the effect on essential node services with their owner, and retain a way to recover an incorrectly constrained test node.\nRecalculate the proposed workload budget after an approved configuration change and compare it with the reported value. If eligible nodes differ, determine how workload placement should account for that difference before approving a denser rollout.\nVerification and evidence\nProposed verification, not performed: use a representative nonproduction node and a bounded disposable workload. Capture capacity, allocatable resources, the reviewed reservation configuration and the workload requests before making any approved adjustment.\nPredict the new budget, apply the managed change through its supported workflow and read the node values again. Compare the result with the worksheet and separately observe essential daemon responsiveness. Stop the exercise if recovery access or an agreed resource margin is threatened; do not exhaust a shared node to prove a subtraction. Retain node identity, configuration revision, calculation, actual values and unresolved differences for another administrator to reconstruct.\nOfficial references\n\nReserve Compute Resources for System Daemons — Kubernetes.\n\nSource review completed October 29, 2026. Recheck the official documentation and deployment-specific applicability before a production change.",
        "content_markdown": "Bottom line: Use the node resource budget actually exposed to workloads when planning additional placement. Keep physical capacity, daemon reservations and eviction headroom in separate rows so available hardware is not mistaken for an unrestricted Pod allowance.\n\n## Source fact: documented behavior\n\nThe [Reserve Compute Resources for System Daemons](https://kubernetes.io/docs/tasks/administer-cluster/reserve-compute-resources/) documentation is the primary reference.\n\nNode Allocatable represents compute resources available to Pods, and the scheduler does not oversubscribe that value. kubeReserved is intended for Kubernetes system daemons rather than daemons running as Pods, while systemReserved covers operating-system daemons and should include kernel memory. Resources reserved for the documented hard-eviction headroom are unavailable to Pods.\n\n## What the source does not establish\n\nThis article reviews the workload budget for CPU, memory and local storage. It supplies no universal reservation size or recommendation to enforce limits on critical operating-system services. Keep the separate PID budget, explicit CPU-set assignment and cgroup-driver selection under their own procedures. A reconciled capacity worksheet does not establish application throughput or node recovery.\n\n## Applicability questions\n\n- What capacity and allocatable values does the node report?\n\n- Which daemons belong to each reservation category?\n\n- What observed demand supports the chosen reservations?\n\n- Which eviction headroom and optional enforcement settings are intended?\n\n## DSE recommendation: explain the difference before adding workloads\n\nDSE recommends reconciling reported allocatable resources with separately owned daemon reservations before increasing workload placement.\n\nBuild one worksheet for each materially different node configuration. Record physical capacity, reported allocatable resources, managed kubelet settings and the workloads eligible to land there. Identify which configuration system owns the values. Preserve an unexplained difference instead of correcting it with an emergency node edit that bypasses that source of truth.\n\nHave the platform and operating-system owners allocate responsibilities for their daemons. Review representative demand during ordinary operation, maintenance and expected workload density. Keep services deployed as Pods in the appropriate workload assessment rather than silently charging them twice to a daemon reservation. Size proposed headroom from the agreed operating case and measurements.\n\nSeparate reserving capacity from deciding how strongly daemon groups should be constrained. Obtain the exact supported cgroup and recovery procedure before enabling additional enforcement. Review the effect on essential node services with their owner, and retain a way to recover an incorrectly constrained test node.\n\nRecalculate the proposed workload budget after an approved configuration change and compare it with the reported value. If eligible nodes differ, determine how workload placement should account for that difference before approving a denser rollout.\n\n## Verification and evidence\n\nProposed verification, not performed: use a representative nonproduction node and a bounded disposable workload. Capture capacity, allocatable resources, the reviewed reservation configuration and the workload requests before making any approved adjustment.\n\nPredict the new budget, apply the managed change through its supported workflow and read the node values again. Compare the result with the worksheet and separately observe essential daemon responsiveness. Stop the exercise if recovery access or an agreed resource margin is threatened; do not exhaust a shared node to prove a subtraction. Retain node identity, configuration revision, calculation, actual values and unresolved differences for another administrator to reconstruct.\n\n## Official references\n\n- [Reserve Compute Resources for System Daemons](https://kubernetes.io/docs/tasks/administer-cluster/reserve-compute-resources/) — Kubernetes.\n\nSource review completed October 29, 2026. Recheck the official documentation and deployment-specific applicability before a production change."
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                "articleBody": "Bottom line: Use the node resource budget actually exposed to workloads when planning additional placement. Keep physical capacity, daemon reservations and eviction headroom in separate rows so available hardware is not mistaken for an unrestricted Pod allowance.\nSource fact: documented behavior\nThe Reserve Compute Resources for System Daemons documentation is the primary reference.\nNode Allocatable represents compute resources available to Pods, and the scheduler does not oversubscribe that value. kubeReserved is intended for Kubernetes system daemons rather than daemons running as Pods, while systemReserved covers operating-system daemons and should include kernel memory. Resources reserved for the documented hard-eviction headroom are unavailable to Pods.\nWhat the source does not establish\nThis article reviews the workload budget for CPU, memory and local storage. It supplies no universal reservation size or recommendation to enforce limits on critical operating-system services. Keep the separate PID budget, explicit CPU-set assignment and cgroup-driver selection under their own procedures. A reconciled capacity worksheet does not establish application throughput or node recovery.\nApplicability questions\n\nWhat capacity and allocatable values does the node report?\nWhich daemons belong to each reservation category?\nWhat observed demand supports the chosen reservations?\nWhich eviction headroom and optional enforcement settings are intended?\n\nDSE recommendation: explain the difference before adding workloads\nDSE recommends reconciling reported allocatable resources with separately owned daemon reservations before increasing workload placement.\nBuild one worksheet for each materially different node configuration. Record physical capacity, reported allocatable resources, managed kubelet settings and the workloads eligible to land there. Identify which configuration system owns the values. Preserve an unexplained difference instead of correcting it with an emergency node edit that bypasses that source of truth.\nHave the platform and operating-system owners allocate responsibilities for their daemons. Review representative demand during ordinary operation, maintenance and expected workload density. Keep services deployed as Pods in the appropriate workload assessment rather than silently charging them twice to a daemon reservation. Size proposed headroom from the agreed operating case and measurements.\nSeparate reserving capacity from deciding how strongly daemon groups should be constrained. Obtain the exact supported cgroup and recovery procedure before enabling additional enforcement. Review the effect on essential node services with their owner, and retain a way to recover an incorrectly constrained test node.\nRecalculate the proposed workload budget after an approved configuration change and compare it with the reported value. If eligible nodes differ, determine how workload placement should account for that difference before approving a denser rollout.\nVerification and evidence\nProposed verification, not performed: use a representative nonproduction node and a bounded disposable workload. Capture capacity, allocatable resources, the reviewed reservation configuration and the workload requests before making any approved adjustment.\nPredict the new budget, apply the managed change through its supported workflow and read the node values again. Compare the result with the worksheet and separately observe essential daemon responsiveness. Stop the exercise if recovery access or an agreed resource margin is threatened; do not exhaust a shared node to prove a subtraction. Retain node identity, configuration revision, calculation, actual values and unresolved differences for another administrator to reconstruct.\nOfficial references\n\nReserve Compute Resources for System Daemons — Kubernetes.\n\nSource review completed October 29, 2026. Recheck the official documentation and deployment-specific applicability before a production change.",
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