Kubeflow

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Channel Revision Published
latest/candidate 294 24 Jan 2022
latest/beta 430 30 Aug 2024
latest/edge 423 26 Jul 2024
1.9/stable 432 03 Dec 2024
1.9/beta 420 19 Jul 2024
1.9/edge 431 03 Dec 2024
1.8/stable 414 22 Nov 2023
1.8/beta 411 22 Nov 2023
1.8/edge 413 22 Nov 2023
1.7/stable 409 27 Oct 2023
1.7/beta 408 27 Oct 2023
1.7/edge 407 27 Oct 2023
juju deploy kubeflow --channel 1.9/stable
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Platform:

This guide presents the available Charmed Kubeflow (CKF) Loki logs.

The CKF charms that use the sidecar pattern can provide log information from its workloads. Those that do not use it need to leverage Promtail for doing so:

Loki does not provide a User Interface (UI). You can use the Grafana UI for checking Loki logs. See Visualize log data for more details on navigating Grafana Loki.

Sidecar pattern charms

The following subsections present CKF charms that use the sidecar pattern and can provide log information from their workloads.

Admission-webhook

Admission-webhook is a Go application that uses k8s.io/klog for logging.

You can check its logs through the Grafana UI using the query {pebble_service="admission-webhook", charm="admission-webhook"}.

See the logs source for more details.

Argo-controller

Argo-controller is a GO application that uses logrus for logging.

You can check its logs through the Grafana UI using the query {pebble_service="argo-controller", charm="argo-controller"}.

See the logs source for more details.

Dex-auth

Dex-auth is a GO application that uses slog for logging.

You can check its logs through the Grafana UI using the query {pebble_service="dex", charm="dex-auth"}

See the logs source for more details.

Envoy

Envoy is a C++ application that uses standard spdlog library for logging.

You can check its logs through the Grafana UI using the query {pebble_service="envoy", charm="envoy"}.

See the logs source for more details. Since this is a third-party application, you will only see the configuration of envoyproxy.

Jupyter-controller

Jupyter-controller is a GO application that uses controller-runtime/pkg/log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="jupyter-controller", charm="jupyter-controller"}.

See the logs source for more details.

Jupyter-ui

Jupyter-ui is a Python application that uses the logging library for logging.

You can check its logs through the Grafana UI using the query {pebble_service="jupyter-ui", charm="jupyter-ui"}.

See the logs source for more details.

Katib-controller

Katib-controller is a GO application that uses controller-runtime/pkg/log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="katib-controller", charm="katib-controller"}.

See the logs source for more details.

Katib-db-manager

Katib-db-manager is a Go application that uses k8s.io/klog for logging.

You can check its logs through the Grafana UI using the query {pebble_service="katib-db-manager", charm="katib-db-manager"}.

See the logs source for more details.

Katib-ui

Katib-ui is a Go application that uses log library for logging.

You can check its logs through the Grafana UI using the query {pebble_service="katib-ui", charm="katib-ui"}.

See the logs source for more details.

Kfp-api

Kfp-api is a GO application that uses logrus for logging.

You can check its logs through the Grafana UI using the query {pebble_service="apiserver", charm="kfp-api"}.

See the logs source for more details.

Kfp-metadata-writer

Kfp-metadata-writer is a Python application that uses print for logging.

You can check its logs through the Grafana UI using the query {pebble_service="kfp-metadata-writer", charm="kfp-metadata-writer"}.

See the logs source for more details.

Kfp-persistence

Kfp-persistence is a GO application that uses logrus for logging.

You can check its logs through the Grafana UI using the query {pebble_service="persistenceagent", charm="kfp-persistence"}.

See the logs source for more details.

Kfp-profile-controller

Kfp-profile-controller is a GO application that uses controller-runtime for logging.

You can check its logs through the Grafana UI using the query {pebble_service="kfp-profile-controller", charm="kfp-profile-controller"}.

See the logs source for more details.

Kfp-schedwf

Kfp-schedwf is a GO application that uses logrus for logging.

You can check its logs through the Grafana UI using the query {pebble_service="controller", charm="kfp-schedwf"}.

See the logs source for more details.

Kfp-ui

Kfp-ui is a TypeScript application that uses console.log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="ml-pipeline-ui", charm="kfp-ui"}.

See the logs source for more details.

Kfp-viewer

Kfp-viewer is a Go application that uses glog for logging.

You can check its logs through the Grafana UI using the query {pebble_service="controller", charm="kfp-viewer"}.

See the logs source for more details.

Kfp-viz

Kfp-viz is a Python application that uses the Tornado framework for logging.

You can check its logs through the Grafana UI using the query {pebble_service="vis-server", charm="kfp-viz"}.

See the logs source for more details.

Knative-operator

Knative-operator comes with two workloads containers and both are a GO application that uses go-kit/log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="knative-operator", charm="knative-operator"} and {pebble_service="knative-operator-webhook", charm="knative-operator"}.

See the logs source for more details.

Kserve-controller

Kserve-controller is a Go application that uses k8s.io/klog for logging. This app also uses kube-rbac-proxy.

You can check its logs through the Grafana UI using the query {pebble_service="kserve-controller", charm="kserve-controller"} and {pebble_service="kube-rbac-proxy", charm="kserve-controller"}

See the logs source for more details.

Kubeflow-dashboard

Kubeflow-dashboard is a TypeScript application that uses console.log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="kubeflow-dashboard", charm="kubeflow-dashboard"}.

See the logs source for more details.

Kubeflow-profiles

Kubeflow-profiles is a GO application that uses logrus for logging.

You can check its logs through the Grafana UI using the query {pebble_service="kubeflow-kfam", charm="kubeflow-profiles"}.

See the logs source for more details.

Kubeflow-volumes

Kubeflow-volumes is a Python application that uses the logging library for logging.

You can check its logs through the Grafana UI using the query {pebble_service="kubeflow-volumes", charm="kubeflow-volumes"}.

See the logs source for more details.

Mlmd

Mlmd is a C++ application that uses the google/glog library for logging.

You can check its logs through the Grafana UI using the query {pebble_service="mlmd", charm="mlmd"}.

See the logs source for more details.

Oidc-gatekeeper

Oidc-gatekeeper is a GO application that uses logrus for logging.

You can check its logs through the Grafana UI using the query {pebble_service="oidc-authservice", charm="oidc-gatekeeper"}.

See the logs source for more details.

Pvcviewer-operator

Pvcviewer-operator is a GO application that uses controller-runtime/pkg/log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="pvcviewer-operator", charm="pvcviewer-operator"}.

See the logs source for more details.

Seldon-core

Seldon-core is a GO application that uses controller-runtime/pkg/log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="seldon-core", charm="seldon-core"}.

See the logs source for more details.

Tensorboard-controller

Tensorboard-controller is a GO application that uses controller-runtime/pkg/log for logging.

You can check its logs through the Grafana UI using the query {pebble_service="pvcviewer-operator", charm="pvcviewer-operator"}.

See the logs source for more details.

Tensorboards-web-app

Tensorboards-web-app is a Python application that uses the logging library for logging.

You can check its logs through the Grafana UI using the query {pebble_service="tensorboards-web-app", charm="tensorboards-web-app"}.

See the logs source for more details.

Non sidecar pattern charms

The following CKF charms do not use the sidecar pattern and cannot use the log forwarding principle:

  • Istio-gateway
  • Istio-pilot
  • Knative-eventing
  • Knative-serving
  • Metacontroller
  • Training-operator

For monitoring these charms, you can use Promtail.

Promtail configuration

You can configure Promtail for a more efficient log collection, avoiding scraping all logs within the clusters and adding the correct Juju topology.

To do so, you need to configure the following:

  1. Clients section
  2. Scrape jobs configuration

Clients section

The clients section requires adding:

  • The <URL> to Loki.
  • The Juju model name <JUJU_MODEL>.
  • The Juju model uuid <JUJU_MODEL_UUID>.
clients:
  - url: <URL>
    external_labels:
      juju_model: <JUJU_MODEL>
      juju_model_uuid: <JUJU_MODEL_UUID>

The URL is required for accessing the Loki server. The external labels are part of the Juju topology required for querying logs.

The Loki URL can be obtained as follows:

juju show-unit grafana-agent-k8s/0 -m cos-controller:cos --endpoint logging-consumer | yq '.[]."relation-info".[]."related-units".[].data.endpoint | fromjson | .url'

The Juju model name is always kubeflow in this use case. You can obtain the Juju model uuid as follows:

juju models --format json | jq '.models.[] | select(."short-name"=="kubeflow") | ."model-uuid"'

Scrape jobs configuration

You can configure Promtail to optimize your scrape jobs. To do so, you need to follow these steps:

  1. Define a namespace for the kubernetes_sd_config.
  2. Define a label selectors to scrape only required Pods. This is recommended to save resources.
  3. [Optional] Enable all original labels from Pods via relabel_configs and action labelmap.
  4. [Optional] Add the rest of Juju topology to each log via pipeline stages and static_labels.

Here’s an example of scrape jobs for istio-pilot and istio-gateway controllers:

- job_name: istio
  kubernetes_sd_configs:
    - role: pod
      namespaces:
        names:
          - kubeflow
      selectors:
        - role: pod
          label: "app in (istio-ingressgateway, istiod)"
  relabel_configs:
    - action: replace
      source_labels:
        - __meta_kubernetes_pod_container_name
      target_label: workload
    - action: labelmap
      regex: __meta_kubernetes_pod_label_(.+)
    - action: replace
      source_labels:
        - __meta_kubernetes_namespace
      target_label: namespace
    - action: replace
      source_labels:
        - __meta_kubernetes_pod_name
      target_label: pod
    - source_labels:
        - __meta_kubernetes_pod_node_name
      target_label: __host__
    - replacement: /var/log/pods/*$1/*.log
      separator: /
      source_labels:
        - __meta_kubernetes_pod_uid
        - __meta_kubernetes_pod_container_name
      target_label: __path__
  pipeline_stages:
    - labeldrop:
      - filename
    - match:
        selector: '{app="istio-ingressgateway"}'
        stages:
          - static_labels:
              juju_application: istio-ingressgateway
              juju_unit: istio-ingressgateway/0
              charm: istio-gateway
    - match:
        selector: '{app="istiod"}'
        stages:
          - static_labels:
              juju_application: istio-pilot
              juju_unit: istio-pilot/0
              charm: istio-pilot

Full example of Promtail deployment

This section provides an example that monitors all non sidecar pattern charms. You can check their logs through the Grafana UI using the query:

{juju_model="kubeflow", charm=~"istio-pilot|istio-gateway|knative-serving|knative-eventing|metacontroller-operator|training-operator"}`

Use the example code by specifying your Promtail configuration. This Promtail deployment .yaml file can be applied to the kubeflow model as follows:

kubectl apply -f ./CKF_promtail.yaml -n kubeflow

Here’s the code snippet:

--- # Deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: promtail
  labels:
    app: promtail
spec:
  selector:
    matchLabels:
      app: promtail
  template:
    metadata:
      labels:
        app: promtail
    spec:
      serviceAccount: promtail-serviceaccount
      containers:
        - name: promtail
          image: grafana/promtail
          args:
            - -config.file=/etc/promtail/promtail.yaml
          env:
            - name: 'HOSTNAME' # needed when using kubernetes_sd_configs
              valueFrom:
                fieldRef:
                  fieldPath: 'spec.nodeName'
          volumeMounts:
            - name: logs
              mountPath: /var/log/pods
            - name: promtail-config
              mountPath: /etc/promtail
      volumes:
        - name: logs
          hostPath:
            path: /var/log/pods
        - name: promtail-config
          configMap:
            name: promtail-config

--- # configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: promtail-config
data:
  promtail.yaml: |
    server:
      http_listen_port: 9080
      grpc_listen_port: 0

    clients:
      - url: http://10.64.140.43/cos-loki-0/loki/api/v1/push
        external_labels:
          juju_model: kubeflow
          juju_model_uuid: f9e6966e-d7bb-4f19-8c4e-276c95880d39

    positions:
      filename: /tmp/positions.yaml

    target_config:
      sync_period: 10s

    scrape_configs:
      - job_name: istio
        kubernetes_sd_configs:
          - role: pod
            namespaces:
              names:
                - kubeflow
            selectors:
              - role: pod
                label: "app in (istio-ingressgateway, istiod)"
        relabel_configs:
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_container_name
            target_label: workload
          - action: labelmap
            regex: __meta_kubernetes_pod_label_(.+)
          - action: replace
            source_labels:
              - __meta_kubernetes_namespace
            target_label: namespace
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_name
            target_label: pod
          - source_labels:
              - __meta_kubernetes_pod_node_name
            target_label: __host__
          - replacement: /var/log/pods/*$1/*.log
            separator: /
            source_labels:
              - __meta_kubernetes_pod_uid
              - __meta_kubernetes_pod_container_name
            target_label: __path__
        pipeline_stages:
          - labeldrop:
            - filename
          - match:
              selector: '{app="istio-ingressgateway"}'
              stages:
                - static_labels:
                    juju_application: istio-ingressgateway
                    juju_unit: istio-ingressgateway/0
                    charm: istio-gateway
          - match:
              selector: '{app="istiod"}'
              stages:
                - static_labels:
                    juju_application: istio-pilot
                    juju_unit: istio-pilot/0
                    charm: istio-pilot

      - job_name: knative
        kubernetes_sd_configs:
          - role: pod
            namespaces:
              names:
                - knative-eventing
                - knative-serving
        relabel_configs:
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_container_name
            target_label: workload
          - action: labelmap
            regex: __meta_kubernetes_pod_label_(.+)
          - action: replace
            source_labels:
              - __meta_kubernetes_namespace
            target_label: namespace
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_name
            target_label: pod
          - source_labels:
              - __meta_kubernetes_pod_node_name
            target_label: __host__
          - replacement: /var/log/pods/*$1/*.log
            separator: /
            source_labels:
              - __meta_kubernetes_pod_uid
              - __meta_kubernetes_pod_container_name
            target_label: __path__
        pipeline_stages:
          - labeldrop:
            - filename
          - match:
              selector: '{namespace="knative-eventing"}'
              stages:
                - static_labels:
                    juju_application: knative-eventing
                    juju_unit: knative-eventing/0
                    charm: knative-eventing
          - match:
              selector: '{namespace="knative-serving"}'
              stages:
                - static_labels:
                    juju_application: knative-serving
                    juju_unit: knative-serving/0
                    charm: knative-serving

      - job_name: metacontroller
        kubernetes_sd_configs:
          - role: pod
            namespaces:
              names:
                - kubeflow
            selectors:
              - role: pod
                label: "app.kubernetes.io/name=metacontroller-operator"
        relabel_configs:
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_container_name
            target_label: workload
          - action: labelmap
            regex: __meta_kubernetes_pod_label_(.+)
          - action: replace
            source_labels:
              - __meta_kubernetes_namespace
            target_label: namespace
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_name
            target_label: pod
          - source_labels:
              - __meta_kubernetes_pod_node_name
            target_label: __host__
          - replacement: /var/log/pods/*$1/*.log
            separator: /
            source_labels:
              - __meta_kubernetes_pod_uid
              - __meta_kubernetes_pod_container_name
            target_label: __path__
        pipeline_stages:
          - labeldrop:
            - filename
          - static_labels:
              juju_application: metacontroller-operator
              juju_unit: metacontroller-operator/0
              charm: metacontroller-operator

      - job_name: training-operator
        kubernetes_sd_configs:
          - role: pod
            namespaces:
              names:
                - kubeflow
            selectors:
              - role: pod
                label: "control-plane=kubeflow-training-operator"
        relabel_configs:
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_container_name
            target_label: workload
          - action: labelmap
            regex: __meta_kubernetes_pod_label_(.+)
          - action: replace
            source_labels:
              - __meta_kubernetes_namespace
            target_label: namespace
          - action: replace
            source_labels:
              - __meta_kubernetes_pod_name
            target_label: pod
          - source_labels:
              - __meta_kubernetes_pod_node_name
            target_label: __host__
          - replacement: /var/log/pods/*$1/*.log
            separator: /
            source_labels:
              - __meta_kubernetes_pod_uid
              - __meta_kubernetes_pod_container_name
            target_label: __path__
        pipeline_stages:
          - labeldrop:
            - filename
          - static_labels:
              juju_application: training-operator
              juju_unit: training-operator/0
              charm: training-operator

--- # Clusterrole.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: promtail-clusterrole
rules:
  - apiGroups: [""]
    resources:
    - nodes
    - services
    - pods
    verbs:
    - get
    - watch
    - list

--- # ServiceAccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: promtail-serviceaccount

--- # Rolebinding.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: promtail-clusterrolebinding
subjects:
  - kind: ServiceAccount
    name: promtail-serviceaccount
    namespace: kubeflow
roleRef:
    kind: ClusterRole
    name: promtail-clusterrole
    apiGroup: rbac.authorization.k8s.io

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