feat: Refactor feature server helm charts to allow passing feature_store.yaml in environment variables #3113
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…ore.yaml in environment variables Signed-off-by: Danny Chiao <danny@tecton.ai>
Signed-off-by: Danny Chiao <danny@tecton.ai>
Signed-off-by: Danny Chiao <danny@tecton.ai>
Signed-off-by: Danny Chiao <danny@tecton.ai>
Signed-off-by: Danny Chiao <danny@tecton.ai>
Codecov Report
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## master #3113 +/- ##
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+ Coverage 67.86% 76.63% +8.77%
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Files 176 210 +34
Lines 15507 17468 +1961
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+ Hits 10524 13387 +2863
+ Misses 4983 4081 -902
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Signed-off-by: Danny Chiao <danny@tecton.ai>
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[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: adchia, kevjumba The full list of commands accepted by this bot can be found here. The pull request process is described here
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verified that the tutorial works on mac m1! |
kevjumba
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Aug 25, 2022
# [0.24.0](v0.23.0...v0.24.0) (2022-08-25) ### Bug Fixes * Check if on_demand_feature_views is an empty list rather than None for snowflake provider ([#3046](#3046)) ([9b05e65](9b05e65)) * FeatureStore.apply applies BatchFeatureView correctly ([#3098](#3098)) ([41be511](41be511)) * Fix Feast Java inconsistency with int64 serialization vs python ([#3031](#3031)) ([4bba787](4bba787)) * Fix feature service inference logic ([#3089](#3089)) ([4310ed7](4310ed7)) * Fix field mapping logic during feature inference ([#3067](#3067)) ([cdfa761](cdfa761)) * Fix incorrect on demand feature view diffing and improve Java tests ([#3074](#3074)) ([0702310](0702310)) * Fix Java helm charts to work with refactored logic. Fix FTS image ([#3105](#3105)) ([2b493e0](2b493e0)) * Fix on demand feature view output in feast plan + Web UI crash ([#3057](#3057)) ([bfae6ac](bfae6ac)) * Fix release workflow to release 0.24.0 ([#3138](#3138)) ([a69aaae](a69aaae)) * Fix Spark offline store type conversion to arrow ([#3071](#3071)) ([b26566d](b26566d)) * Fixing Web UI, which fails for the SQL registry ([#3028](#3028)) ([64603b6](64603b6)) * Force Snowflake Session to Timezone UTC ([#3083](#3083)) ([9f221e6](9f221e6)) * Make infer dummy entity join key idempotent ([#3115](#3115)) ([1f5b1e0](1f5b1e0)) * More explicit error messages ([#2708](#2708)) ([e4d7afd](e4d7afd)) * Parse inline data sources ([#3036](#3036)) ([c7ba370](c7ba370)) * Prevent overwriting existing file during `persist` ([#3088](#3088)) ([69af21f](69af21f)) * Register BatchFeatureView in feature repos correctly ([#3092](#3092)) ([b8e39ea](b8e39ea)) * Return an empty infra object from sql registry when it doesn't exist ([#3022](#3022)) ([8ba87d1](8ba87d1)) * Teardown tables for Snowflake Materialization testing ([#3106](#3106)) ([0a0c974](0a0c974)) * UI error when saved dataset is present in registry. ([#3124](#3124)) ([83cf753](83cf753)) * Update sql.py ([#3096](#3096)) ([2646a86](2646a86)) * Updated snowflake template ([#3130](#3130)) ([f0594e1](f0594e1)) ### Features * Add authentication option for snowflake connector ([#3039](#3039)) ([74c75f1](74c75f1)) * Add Cassandra/AstraDB online store contribution ([#2873](#2873)) ([feb6cb8](feb6cb8)) * Add Snowflake materialization engine ([#2948](#2948)) ([f3b522b](f3b522b)) * Adding saved dataset capabilities for Postgres ([#3070](#3070)) ([d3253c3](d3253c3)) * Allow passing repo config path via flag ([#3077](#3077)) ([0d2d951](0d2d951)) * Contrib azure provider with synapse/mssql offline store and Azure registry store ([#3072](#3072)) ([9f7e557](9f7e557)) * Custom Docker image for Bytewax batch materialization ([#3099](#3099)) ([cdd1b07](cdd1b07)) * Feast AWS Athena offline store (again) ([#3044](#3044)) ([989ce08](989ce08)) * Implement spark offline store `offline_write_batch` method ([#3076](#3076)) ([5b0cc87](5b0cc87)) * Initial Bytewax materialization engine ([#2974](#2974)) ([55c61f9](55c61f9)) * Refactor feature server helm charts to allow passing feature_store.yaml in environment variables ([#3113](#3113)) ([85ee789](85ee789))
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What this PR does / why we need it:
The old python feature server helm chart relied on users to build their own Docker image to bundle in a
feature_store.yamlfile. This change makes it so users instead pass a base64 encoded version of this as an environment variable (similar to the AWS lambda feature server approach) to hopefully reduce time to productionWhich issue(s) this PR fixes:
Fixes #