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chore(release): Update stackableRelease to 26.3
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stacks/stacks-v2.yaml

Lines changed: 18 additions & 18 deletions
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@@ -2,7 +2,7 @@
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stacks:
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argo-cd-git-ops:
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description: Deploying Stackable Operators with ArgoCD
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stackableRelease: dev # This does not matter -> managed by ArgoCD
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stackableRelease: 26.3 # This does not matter -> managed by ArgoCD
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stackableOperators: ["argo-deploys-operators"] # This does not matter -> managed by ArgoCD
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labels:
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- argocd
@@ -43,7 +43,7 @@ stacks:
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default: $2y$10$HhJC3pGHTlk8RyBoS39N/.wC72mdWxV2X8QS1wROUwCFxl.2tGfky
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monitoring:
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description: Stack containing Prometheus and Grafana
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -69,7 +69,7 @@ stacks:
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default: adminadmin
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logging:
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description: Stack containing OpenSearch, OpenSearch Dashboards (Kibana) and Vector aggregator
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -108,7 +108,7 @@ stacks:
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observability:
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description: >-
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An observability stack with auto-injection of the opentelemetry-collector sidecar to receive traces/logs/metrics via OTLP, and send them to Jaeger/Tempo/Loki.
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -133,7 +133,7 @@ stacks:
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default: adminadmin
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airflow:
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description: Stack containing Airflow scheduling platform
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -183,7 +183,7 @@ stacks:
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default: airflowSecretKey
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data-lakehouse-iceberg-trino-spark:
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description: Data lakehouse using Iceberg lakehouse on S3, Trino as query engine, Spark for streaming ingest and Superset for data visualization
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -239,7 +239,7 @@ stacks:
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default: supersetSecretKey
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hdfs-hbase:
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description: HBase cluster using HDFS as underlying storage
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -262,7 +262,7 @@ stacks:
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parameters: []
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nifi-kafka-druid-superset-s3:
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description: Stack containing NiFi, Kafka, Druid, MinIO and Superset for data visualization
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -308,7 +308,7 @@ stacks:
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default: adminadmin
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spark-trino-superset-s3:
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description: Stack containing MinIO, Trino and Superset for data visualization
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -355,7 +355,7 @@ stacks:
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default: supersetSecretKey
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trino-superset-s3:
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description: Stack containing MinIO, Trino and Superset for data visualization
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -397,7 +397,7 @@ stacks:
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default: supersetSecretKey
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trino-iceberg:
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description: Stack containing Trino using Apache Iceberg as a S3 data lakehouse
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -431,7 +431,7 @@ stacks:
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default: adminadmin
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jupyterhub-pyspark-hdfs:
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description: Jupyterhub with PySpark and HDFS integration
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -464,7 +464,7 @@ stacks:
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The bind user credentials are: ldapadmin:ldapadminpassword.
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No AuthenticationClass is configured, The AuthenticationClass is created manually in the tutorial.
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Use the 'openldap' Stack for an OpenLDAD with an AuthenticationClass already installed.
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -487,7 +487,7 @@ stacks:
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The bind user credentials are: ldapadmin:ldapadminpassword.
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The LDAP AuthenticationClass is called 'openldap' and the SecretClass for the bind credentials is called 'openldap-bind-credentials'.
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The stack already creates an appropriate Secret, so referring to the 'openldap' AuthenticationClass in your ProductCluster should be enough.
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -511,7 +511,7 @@ stacks:
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Note that this stack is tightly coupled with the demo.
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So if you install the stack you will get demo-specific parts (such as Keycloak users or regorules).
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -584,7 +584,7 @@ stacks:
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signal-processing:
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description: >-
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A stack used for creating, streaming and processing in-flight data and persisting it to TimescaleDB before it is displayed in Grafana
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
@@ -620,7 +620,7 @@ stacks:
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jupyterhub-keycloak:
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description: >-
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A stack used to demonstrate JupyterHub and Keycloak, using parts of the end-to-end security demo.
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener
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default: jupyterhubjupyterhub
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opensearch-rag:
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description: OpenSearch RAG (Retrieval Augmented Generation) demo with vector search
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stackableRelease: dev
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stackableRelease: 26.3
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stackableOperators:
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- commons
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- listener

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