text stringlengths 0 59.1k |
|---|
value: 100 |
periodSeconds: 15 |
selectPolicy: Max |
scaleDown: |
# The stabilizationWindowSeconds is set to 30 to prevent the HPA from |
# scaling down too aggressively. This means the controller will wait for |
# 30 seconds after a scale-down event before considering another one. |
# This helps to smooth out the scaling behavior and prevent "flapping" |
# (rapidly scaling up and down). A larger value will make the scaling |
# more conservative, which can be useful for workloads with fluctuating |
# metrics, but it may also result in higher costs if the resources are |
# not released quickly after a load decrease. |
stabilizationWindowSeconds: 30 |
policies: |
- type: Percent |
value: 100 |
periodSeconds: 15 |
selectPolicy: Max |
<|endoftext|> |
# source: k8s_examples/AI/vllm-deployment/hpa/gpu-dcgm-exporter-service-generic.yaml type: yaml |
# This Service provides a stable network endpoint for the NVIDIA DCGM Exporter |
# pods for users who have MANUALLY installed the exporter (e.g., on EKS/AKS). |
# The Prometheus Operator's ServiceMonitor will target this Service |
# to discover and scrape the GPU metrics. |
apiVersion: v1 |
kind: Service |
metadata: |
name: gpu-dcgm-exporter-service |
# The Helm chart for the DCGM exporter is instructed to deploy it in the 'monitoring' namespace. |
namespace: monitoring |
labels: |
# This label is critical. The generic ServiceMonitor uses this label to find |
# this specific Service. |
app.kubernetes.io/name: gpu-dcgm-exporter |
spec: |
type: ClusterIP |
selector: |
# This selector tells the Service which pods to route traffic to. |
# It must match the labels on the DCGM exporter pods deployed by the Helm chart. |
app.kubernetes.io/name: gpu-dcgm-exporter |
ports: |
- name: metrics |
port: 9400 |
protocol: TCP |
targetPort: 9400 |
<|endoftext|> |
# source: k8s_examples/AI/vllm-deployment/hpa/prometheus-rule.yaml type: yaml |
# This PrometheusRule defines a recording rule that is essential for making |
# the raw DCGM GPU metrics usable by the HPA. The raw 'DCGM_FI_DEV_GPU_UTIL' |
# metric scraped by Prometheus does not have the standard 'pod' and 'namespace' |
# labels that the Prometheus Adapter needs to associate the metric with a |
# specific workload pod. |
# |
# This rule creates a NEW metric, 'dcgm_fi_dev_gpu_util_relabelled', |
# and uses the 'label_replace' function to copy the pod and namespace |
# information from the 'exported_pod' and 'exported_namespace' labels into |
# the standard 'pod' and 'namespace' labels. The Prometheus Adapter will then |
# use this new, correctly-labelled metric. |
apiVersion: monitoring.coreos.com/v1 |
kind: PrometheusRule |
metadata: |
name: dcgm-relabel-rules |
namespace: monitoring |
labels: |
# This label ensures the Prometheus instance discovers this rule. |
release: prometheus |
spec: |
groups: |
- name: dcgm.rules |
rules: |
# 'record' specifies the name of the new metric to be created. |
- record: dcgm_fi_dev_gpu_util_relabelled |
# 'expr' contains the PromQL expression that generates the new metric. |
expr: | |
label_replace( |
label_replace( |
DCGM_FI_DEV_GPU_UTIL, |
"pod", |
"$1", |
"exported_pod", |
"(.+)" |
), |
"namespace", |
"$1", |
"exported_namespace", |
"(.+)" |
) |
<|endoftext|> |
# source: k8s_examples/AI/vllm-deployment/hpa/prometheus-adapter.yaml type: yaml |
# This manifest deploys the Prometheus Adapter, which is responsible for |
# reading metrics from Prometheus and exposing them to the Kubernetes |
# Custom Metrics API. The Horizontal Pod Autoscaler (HPA) uses this API |
# to query for the custom metrics that drive its scaling decisions. |
# This file also includes the necessary RBAC permissions and the critical |
# ConfigMap that defines the metric transformation rules. |
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