Mit Desai created YUNIKORN-3122:
-----------------------------------
Summary: Optimize Node Evaluation by Pre-filtering Tainted Nodes
Based on Pod Tolerations
Key: YUNIKORN-3122
URL: https://issues.apache.org/jira/browse/YUNIKORN-3122
Project: Apache YuniKorn
Issue Type: New Feature
Reporter: Mit Desai
Assignee: Mit Desai
h3. Summary
Implement intelligent node pre-filtering in YuniKorn to avoid evaluating nodes
with taints that don't match pod tolerations during scheduling cycles. This
optimization will significantly improve scheduling performance in large
clusters with mixed tainted and untainted nodes.
h3. Background
In large Kubernetes clusters with node taints for workload isolation (e.g.,
different nodepools for security, compliance, or resource requirements),
YuniKorn currently evaluates all nodes during each scheduling cycle regardless
of whether the pod being scheduled has the necessary tolerations. This leads to
significant performance overhead as the scheduler:
# {*}Evaluates Incompatible Nodes{*}: Processes nodes that will ultimately be
rejected due to taint mismatches
# {*}Wastes CPU Cycles{*}: Performs unnecessary predicate checks on unsuitable
nodes
# {*}Increases Scheduling Latency{*}: Adds overhead proportional to the number
of tainted nodes in the cluster
h4. Real-World Impact
* {*}Cluster Size{*}: 700+ nodes with ~50% having nodepool taints
* {*}Current Behavior{*}: Scheduler evaluates all 700 nodes per cycle
* {*}Optimal Behavior{*}: Should only evaluate ~350 compatible nodes per cycle
* {*}Performance Gain{*}: Potential 50% reduction in node evaluation overhead
YuniKorn's current node evaluation logic:
{code:go}
// Current inefficient approach
for each_node in cluster {
evaluate_node_predicates(node, pod) // Includes taint/toleration check
if predicates_pass {
attempt_allocation(node, pod)
}
}
{code}
This approach evaluates nodes that are guaranteed to fail taint/toleration
checks, wasting computational resources.
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