Any documentation we can take a look at to diagnose the following error the propeller is logging on restart:

"msg":"failed to load plugin - spark: no matches for kind \"SparkApplication\" in version \"<http://sparkoperator.k8s.io/v1beta2|sparkoperator.k8s.io/v1beta2>\"

My propeller config map looks like this:

# Source: flyte-core/templates/propeller/configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: flyte-propeller-config
  namespace: flyte
  labels: 
    <http://app.kubernetes.io/name|app.kubernetes.io/name>: flyteadmin
data:
  admin.yaml: | 
    admin:
      clientId: 'flytepropeller'
      clientSecretLocation: /etc/secrets/client_secret
      endpoint: flyteadmin:81
      insecure: true
    event:
      capacity: 1000
      rate: 500
      type: admin
  catalog.yaml: | 
    catalog-cache:
      endpoint: datacatalog:89
      insecure: true
      type: datacatalog
  copilot.yaml: | 
    plugins:
      k8s:
        co-pilot:
          image: <http://cr.flyte.org/flyteorg/flytecopilot:v0.0.24|cr.flyte.org/flyteorg/flytecopilot:v0.0.24>
          name: flyte-copilot-
          start-timeout: 30s
  core.yaml: | 
    manager:
      pod-application: flytepropeller
      pod-template-container-name: flytepropeller
      pod-template-name: flytepropeller-template
    propeller:
      downstream-eval-duration: 30s
      enable-admin-launcher: true
      gc-interval: 12h
      kube-client-config:
        burst: 25
        qps: 100
        timeout: 30s
      leader-election:
        enabled: true
        lease-duration: 15s
        lock-config-map:
          name: propeller-leader
          namespace: flyte
        renew-deadline: 10s
        retry-period: 2s
      limit-namespace: all
      max-workflow-retries: 50
      metadata-prefix: metadata/propeller
      metrics-prefix: flyte
      prof-port: 10254
      queue:
        batch-size: -1
        batching-interval: 2s
        queue:
          base-delay: 5s
          capacity: 1000
          max-delay: 120s
          rate: 100
          type: maxof
        sub-queue:
          capacity: 1000
          rate: 100
          type: bucket
        type: batch
      rawoutput-prefix: s3://${ parameters.s3_bucket_name }/
      workers: 40
      workflow-reeval-duration: 30s
    webhook:
      certDir: /etc/webhook/certs
      serviceName: flyte-pod-webhook
  enabled_plugins.yaml: | 
    tasks:
      task-plugins:
        default-for-task-types:
          container: container
          container_array: k8s-array
          sidecar: sidecar
          spark: spark
        enabled-plugins:
        - container
        - sidecar
        - k8s-array
        - spark
  k8s.yaml: | 
    plugins:
      k8s:
        default-cpus: 100m
        default-env-vars: []
        default-memory: 100Mi
  resource_manager.yaml: | 
    propeller:
      resourcemanager:
        type: noop
  storage.yaml: | 
    storage:
      type: s3
      container: "${ parameters.s3_bucket_name }"
      connection:
        auth-type: iam
        region: ${ parameters.aws_region }
      limits:
        maxDownloadMBs: 10
  cache.yaml: |
    cache:
      max_size_mbs: 1024
      target_gc_percent: 70
  task_logs.yaml: | 
    plugins:
      logs:
        cloudwatch-enabled: false
        kubernetes-enabled: false
  spark.yaml: |
    plugins:
      spark:
        spark-config-default:
          - spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version: "2"
          - spark.kubernetes.allocation.batch.size: "50"
          - spark.hadoop.fs.s3a.acl.default: "BucketOwnerFullControl"
          - spark.hadoop.fs.s3n.impl: "org.apache.hadoop.fs.s3a.S3AFileSystem"
          - spark.hadoop.fs.AbstractFileSystem.s3n.impl: "org.apache.hadoop.fs.s3a.S3A"
          - spark.hadoop.fs.s3.impl: "org.apache.hadoop.fs.s3a.S3AFileSystem"
          - spark.hadoop.fs.AbstractFileSystem.s3.impl: "org.apache.hadoop.fs.s3a.S3A"
          - spark.hadoop.fs.s3a.impl: "org.apache.hadoop.fs.s3a.S3AFileSystem"
          - spark.hadoop.fs.AbstractFileSystem.s3a.impl: "org.apache.hadoop.fs.s3a.S3A"
          - spark.hadoop.fs.s3a.multipart.threshold: "536870912"
          - spark.blacklist.enabled: "true"
          - spark.blacklist.timeout: "5m"
          - spark.task.maxfailures: "8"

And my cluster resource template

# Source: flyte-core/templates/clusterresourcesync/cluster_resource_configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: clusterresource-template
  namespace: flyte
  labels: 
    <http://app.kubernetes.io/name|app.kubernetes.io/name>: flyteadmin
    <http://helm.sh/chart|helm.sh/chart>: flyte-core-v0.1.10
data:
  aa_namespace.yaml: | 
    apiVersion: v1
    kind: Namespace
    metadata:
      name: {{ namespace }}
    spec:
      finalizers:
      - kubernetes
    
  aab_default_service_account.yaml: | 
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: default
      namespace: {{ namespace }}
    
  ab_project_resource_quota.yaml: | 
    apiVersion: v1
    kind: ResourceQuota
    metadata:
      name: project-quota
      namespace: {{ namespace }}
    spec:
      hard:
        limits.cpu: {{ projectQuotaCpu }}
        limits.memory: {{ projectQuotaMemory }}
    
  ac_spark_role.yaml: | 
    apiVersion: <http://rbac.authorization.k8s.io/v1|rbac.authorization.k8s.io/v1>
    kind: Role
    metadata:
      name: spark-role
      namespace: {{ namespace }}
    rules:
    - apiGroups: ["*"]
      resources:
      - pods
      verbs:
      - '*'
    - apiGroups: ["*"]
      resources:
      - services
      verbs:
      - '*'
    - apiGroups: ["*"]
      resources:
      - configmaps
      verbs:
      - '*'
    
  ad_spark_service_account.yaml: | 
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: spark
      namespace: {{ namespace }}
    
  ae_spark_role_binding.yaml: | 
    apiVersion: <http://rbac.authorization.k8s.io/v1|rbac.authorization.k8s.io/v1>
    kind: RoleBinding
    metadata:
      name: spark-role-binding
      namespace: {{ namespace }}
    roleRef:
      apiGroup: <http://rbac.authorization.k8s.io|rbac.authorization.k8s.io>
      kind: Role
      name: spark-role
    subjects:
    - kind: ServiceAccount
      name: spark
      namespace: {{ namespace }}

Hey @Katrina P do you have the spark k8s operator deployed on the cluster? It looks like the spark plugin does not detect the CRD.

Yes, its been deployed on the cluster before Flyte even

So for

python-task

this is normal. Basically, under the plugins configuration there is a mapping of task types to the plugin id. Typically these are the same so it seems a little redundant, example:

enabled_plugins.yaml: | 
    tasks:
      task-plugins:
        default-for-task-types:
          container: container
          container_array: k8s-array
          sidecar: sidecar
          spark: spark
        enabled-plugins:
        - container
        - sidecar
        - k8s-array
        - spark

In propeller if we register a task-type that doesn't have an associated plugin it fallsback to the

container

plugin. As I mentioned, this is normal for

python-task

but for

spark

it could be an issue. Did you change this configuration?

Config seems right

I guess this means that my spark jobs are running via container rather than SparkOperator -- my configs are as you posted my propeller configmap

@Katrina P not at my desk, will tal in a bit. @Samhita Alla / @Yuvraj / if you folks are around

@Katrina P Can you please post the output of these command ?

kubectl api-versions | grep '<http://sparkoperator.k8s.io|sparkoperator.k8s.io>'
kubectl api-resources | grep '<http://sparkoperator.k8s.io|sparkoperator.k8s.io>'

Sure, I don't have kubectl access on our cluster so gotta find an on call engineer but will report back

can you also send me your command for spark operator installation ? Also can you restart propeller deployment and send me startup logs. Did you follow the plugin docs https://docs.flyte.org/en/latest/deployment/plugin_setup/k8s/index.html#deployment-plugin-setup-k8s ?

The Spark Operator was already installed in our cluster by dev ops before we installed Flyte, I can ask how they installed it; we did follow the k8s plugin instructions to update the helm chart; we then used the chart to generate the updates to configmaps for propeller (above), admin custer role, and resource template (above) manifests

helm template flyte flyteorg/flyte-core -f <https://raw.githubusercontent.com/flyteorg/flyte/master/charts/flyte-core/values-sandbox.yaml> -f values-override.yaml -n flyte > spark-override.yaml

@Katrina P did you get it working?