This topic describes how to optimize CPU performance in different scenarios.
Scenario | Method | Performance |
---|---|---|
Nodes of a Container Service for Kubernetes (ACK) cluster run on ECS bare metal instances
that have Non-Uniform Memory Access (NUMA) enabled.
|
|
|
Nodes of an ACK cluster run on ECS bare metal instances or ECS instances, each of
which has 32 vCPUs or more.
|
|
Maximize the utilization of CPU time fragments to improve CPU utilization. |
Nodes of an ACK cluster run on the following instances that have NUMA enabled: ECS bare metal instances or ECS instances, each of which has 32 vCPUs or more. Hybrid deployment of latency-sensitive workloads and BestEffort workloads that allow bindings to vCPUs. |
|
Maximize the RT, CPU time fragments, and memory reclaim policies for latency-sensitive workloads. |
Nodes of an ACK cluster run on ECS bare metal instances or ECS instances, each of which has 32 vCPUs or more. Hybrid deployment of multiple workloads that have the CPUShare mode enabled. |
|
Maximize the RT of latency-sensitive workloads. The impact of BestEffort workloads on latency-sensitive workloads is within 5%. |
Nodes of an ACK cluster run on ECS bare metal instances that use the AMD architecture.
|
|
|
Nodes of an ACK cluster run on ECS bare metal instances that use the ARM architecture.
|
Topology-aware CPU scheduling |
|
Registered clusters that manage the scheduling of on-premises physical nodes.
|
Topology-aware CPU scheduling | The CPU performance is related to the CPU type. |
The following figure shows that the efficiency of the L3 cache, dynamic memory bandwidth isolation, CCX/CCD affinity scheduling, and topology-aware CPU scheduling are improved after the CPU performance is optimized.