update
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20
infra/argocd/templates/litellm.yaml
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20
infra/argocd/templates/litellm.yaml
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apiVersion: argoproj.io/v1alpha1
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kind: Application
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metadata:
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name: litellm
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namespace: argocd
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spec:
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project: default
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source:
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repoURL: https://gitlab.com/developerdurp/homelab.git
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targetRevision: main
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path: infra/litellm
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destination:
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namespace: litellm
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name: in-cluster
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syncPolicy:
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automated:
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prune: true
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selfHeal: true
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syncOptions:
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- CreateNamespace=true
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12
infra/litellm/Chart.yaml
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infra/litellm/Chart.yaml
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apiVersion: v2
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name: litellm
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description: A Helm chart for Kubernetes
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type: application
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version: 0.1.0
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appVersion: "1.16.0"
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dependencies:
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- name: "litellm-helm"
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version: 0.1.636
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repository: oci://ghcr.io/berriai/litellm
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197
infra/litellm/values.yaml
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197
infra/litellm/values.yaml
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litellm:
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# Default values for litellm.
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# This is a YAML-formatted file.
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# Declare variables to be passed into your templates.
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replicaCount: 1
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image:
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# Use "ghcr.io/berriai/litellm-database" for optimized image with database
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repository: ghcr.io/berriai/litellm-database
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pullPolicy: Always
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# Overrides the image tag whose default is the chart appVersion.
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# tag: "main-latest"
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tag: ""
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imagePullSecrets: []
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nameOverride: "litellm"
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fullnameOverride: ""
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serviceAccount:
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# Specifies whether a service account should be created
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create: false
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# Automatically mount a ServiceAccount's API credentials?
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automount: true
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# Annotations to add to the service account
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annotations: {}
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# The name of the service account to use.
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# If not set and create is true, a name is generated using the fullname template
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name: ""
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podAnnotations: {}
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podLabels: {}
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# At the time of writing, the litellm docker image requires write access to the
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# filesystem on startup so that prisma can install some dependencies.
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podSecurityContext: {}
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securityContext: {}
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# capabilities:
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# drop:
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# - ALL
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# readOnlyRootFilesystem: false
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# runAsNonRoot: true
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# runAsUser: 1000
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# A list of Kubernetes Secret objects that will be exported to the LiteLLM proxy
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# pod as environment variables. These secrets can then be referenced in the
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# configuration file (or "litellm" ConfigMap) with `os.environ/<Env Var Name>`
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environmentSecrets: []
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# - litellm-env-secret
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# A list of Kubernetes ConfigMap objects that will be exported to the LiteLLM proxy
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# pod as environment variables. The ConfigMap kv-pairs can then be referenced in the
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# configuration file (or "litellm" ConfigMap) with `os.environ/<Env Var Name>`
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environmentConfigMaps: []
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# - litellm-env-configmap
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service:
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type: ClusterIP
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port: 4000
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ingress:
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enabled: false
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className: "nginx"
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annotations: {}
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# kubernetes.io/ingress.class: nginx
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# kubernetes.io/tls-acme: "true"
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hosts:
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- host: api.example.local
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paths:
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- path: /
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pathType: ImplementationSpecific
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tls: []
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# - secretName: chart-example-tls
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# hosts:
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# - chart-example.local
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# masterkey: changeit
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# The elements within proxy_config are rendered as config.yaml for the proxy
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# Examples: https://github.com/BerriAI/litellm/tree/main/litellm/proxy/example_config_yaml
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# Reference: https://docs.litellm.ai/docs/proxy/configs
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proxy_config:
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model_list:
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# At least one model must exist for the proxy to start.
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- model_name: gpt-3.5-turbo
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litellm_params:
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model: gpt-3.5-turbo
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api_key: eXaMpLeOnLy
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- model_name: fake-openai-endpoint
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litellm_params:
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model: openai/fake
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api_key: fake-key
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api_base: https://exampleopenaiendpoint-production.up.railway.app/
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general_settings:
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master_key: os.environ/PROXY_MASTER_KEY
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resources: {}
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# We usually recommend not to specify default resources and to leave this as a conscious
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# choice for the user. This also increases chances charts run on environments with little
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# resources, such as Minikube. If you do want to specify resources, uncomment the following
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# lines, adjust them as necessary, and remove the curly braces after 'resources:'.
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# limits:
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# cpu: 100m
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# memory: 128Mi
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# requests:
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# cpu: 100m
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# memory: 128Mi
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autoscaling:
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enabled: false
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minReplicas: 1
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maxReplicas: 100
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targetCPUUtilizationPercentage: 80
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# targetMemoryUtilizationPercentage: 80
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# Additional volumes on the output Deployment definition.
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volumes: []
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# - name: foo
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# secret:
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# secretName: mysecret
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# optional: false
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# Additional volumeMounts on the output Deployment definition.
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volumeMounts: []
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# - name: foo
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# mountPath: "/etc/foo"
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# readOnly: true
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nodeSelector: {}
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tolerations: []
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affinity: {}
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db:
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# Use an existing postgres server/cluster
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useExisting: false
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# How to connect to the existing postgres server/cluster
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endpoint: localhost
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database: litellm
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url: postgresql://$(DATABASE_USERNAME):$(DATABASE_PASSWORD)@$(DATABASE_HOST)/$(DATABASE_NAME)
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secret:
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name: postgres
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usernameKey: username
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passwordKey: password
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# Use the Stackgres Helm chart to deploy an instance of a Stackgres cluster.
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# The Stackgres Operator must already be installed within the target
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# Kubernetes cluster.
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# TODO: Stackgres deployment currently unsupported
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useStackgresOperator: false
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# Use the Postgres Helm chart to create a single node, stand alone postgres
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# instance. See the "postgresql" top level key for additional configuration.
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deployStandalone: true
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# Settings for Bitnami postgresql chart (if db.deployStandalone is true, ignored
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# otherwise)
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postgresql:
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architecture: standalone
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auth:
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username: litellm
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database: litellm
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# You should override these on the helm command line with
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# `--set postgresql.auth.postgres-password=<some good password>,postgresql.auth.password=<some good password>`
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password: NoTaGrEaTpAsSwOrD
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postgres-password: NoTaGrEaTpAsSwOrD
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# A secret is created by this chart (litellm-helm) with the credentials that
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# the new Postgres instance should use.
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# existingSecret: ""
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# secretKeys:
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# userPasswordKey: password
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# requires cache: true in config file
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# either enable this or pass a secret for REDIS_HOST, REDIS_PORT, REDIS_PASSWORD or REDIS_URL
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# with cache: true to use existing redis instance
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redis:
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enabled: false
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architecture: standalone
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# Prisma migration job settings
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migrationJob:
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enabled: true # Enable or disable the schema migration Job
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retries: 3 # Number of retries for the Job in case of failure
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backoffLimit: 4 # Backoff limit for Job restarts
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disableSchemaUpdate: false # Skip schema migrations for specific environments. When True, the job will exit with code 0.
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annotations: {}
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ttlSecondsAfterFinished: 120
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# Additional environment variables to be added to the deployment
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envVars: {
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# USE_DDTRACE: "true"
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}
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Reference in New Issue
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