Releases: snowplow/quickstart-examples
25.10
Updates AWS, GCP and Azure to latest available components across the board.
Version bumps
- Collector to v3.7.0
- Enrich to v6.2.1
- Iglu Server to v0.14.1
- S3 Loader to v3.0.0 (AWS only)
- Snowflake Streaming Loader to v0.5.1 (AWS only)
- RDB Loader (Redshift + Databricks) to v6.1.5 (AWS only)
- BigQuery Loader to v2.0.1 (GCP only)
- Lake Loader to v0.7.0 (Azure only)
Future proofing
- Using Amazon Linux 2023 on AWS
- Using Ubuntu 24.04 on Azure and GCP
Breaking changes
- Collector by default now leverages Compression as default which requires Enrich v6+ to be able to decode the compressed payloads. Ensure to upgrade both applications to ensure data-flow doesn't stop.
- Removal of S3 Loader for RAW data from AWS.
- Removal of Postgres Loader from AWS and GCP - we are no longer maintaining this module going forward.
- Removal of Snowflake RDB Loader from AWS and Azure - we are no longer maintaining this module going forward.
Bug fixes
- Azure Iglu Server can now be deployed again with an upgraded base
vnetandpostgresmodule which supports the Flexible Postgres database offering from Azure
25.06
25.01 (Patch.1)
Update Enrich to v5.2.0
Update Iglu Server to v0.14.0
25.01
24.02 (Patch.1)
Add support for Snowflake Streaming Loader to AWS (#92)
24.02
23.10 (Patch.1)
This patch release fixes a fatal bug in the underlying AWS Service module with Amazon Linux 2 and Docker installations. See the following Discourse thread for details: https://discourse.snowplow.io/t/collector-server-failing-health-check/9581/2
Bump versions of ec2-based modules (#85)
Remove postgres_db_publicly_accessible tfvar from secure file (#86)
23.10
This release revamps the GCP quick-start to work in the same way as Azure and AWS in that all destinations can be deployed concurrently as well as bringing all of the provider versions and applications version back up to date with our latest recommendations.
23.07 (Patch.4)
23.07 (Patch.3)
This release adds support for Databricks and Azure Synapse as supported platforms to load data into via the Azure pipeline.