jaingxyz
UserComposable Anthropic skills for building real-time data pipelines on AWS (CDC, Iceberg, Redshift Serverless). Companion to dsql-redshift-cdc-pipeline.
Categories
Indexed Skills (4)
streaming-into-data-lake
Stream rows continuously into Apache Iceberg tables on S3 Tables (or standard Iceberg on a general purpose bucket) using Amazon Data Firehose with IcebergDestinationConfiguration. Covers the Firehose stream, the optional record-shaping Lambda (ProcessingConfiguration), the Lake Formation grants required for Firehose to write through Glue, and the three-phase CloudFormation deploy that gates the stream on grants existing. Triggers on: stream into data lake, Firehose to S3 Tables, Firehose to Iceberg, real-time ingestion to Iceberg, Firehose IcebergDestinationConfiguration, stream Kinesis to Iceberg, near real-time CDC to data lake, continuous append to Iceberg. Do NOT use for: batch file imports (use ingesting-into-data-lake), creating the destination Iceberg table itself (use creating-data-lake-table), the one-time Lake Formation onboarding (use setting-up-lake-formation), finding tables by fuzzy name (use finding-data-lake-assets), running queries (use querying-data-lake), Glue connections (Firehose does not
dsql-to-analytics-pipeline
Build a real-time analytics pipeline downstream of Aurora DSQL using the DSQL CDC stream. Covers consumer Lambda correctness, the append-only event log + ROW_NUMBER reconstruction pattern that absorbs unordered/duplicate delivery, Redshift Data API parameter-cap chunking, async statement polling, BisectBatchOnFunctionError, MaximumRecordAgeInSeconds, DLQ wiring, and the DSQL-preview gotcha that both INSERT and UPDATE arrive as op='c'. Triggers on phrases like: DSQL to analytics, DSQL to Redshift, analyze DSQL data, real-time DSQL analytics, DSQL CDC pipeline, Aurora DSQL change data capture, stream DSQL changes, replicate DSQL, DSQL to S3, DSQL to Iceberg, DSQL Kinesis Lambda, DSQL data warehouse.
cdc-streaming-pipeline
Build a real-time change-data-capture pipeline from a transactional database (Aurora DSQL, Aurora Postgres, RDS) to Redshift Serverless, S3, or any other sink, via Kinesis Data Streams (or MSK). Covers producer setup, consumer Lambda correctness, the append-only event log + reconstruction pattern, schema-drift handling with SUPER + JSON_PARSE, and the operational gotchas (Redshift Data API parameter caps, async statement polling, poison-record handling, retry-and-bisect). Use when the user asks for "CDC to Redshift", "stream change data capture", "Aurora CDC", "DSQL CDC", "Postgres replication to S3", or "build a Lambda consumer for Kinesis CDC". Aurora DSQL public-preview specifics are flagged; the rest is source-agnostic.
firehose-iceberg-pipeline
Build an Amazon Data Firehose delivery stream that writes to Apache Iceberg tables on S3 Tables via IcebergDestinationConfiguration. Covers the column-shape footgun (records land in the error bucket with Iceberg.MissingColumnWithinRecord unless a transform Lambda reshapes them), the microsecond timestamp requirement, the three-phase deploy pattern that works around Firehose's synchronous glue:GetTable validation at create time, parameter-inheritance traps in `aws cloudformation deploy`, Lake Formation grant ordering, and how to decode the error bucket. Use when you see "Firehose to Iceberg", "Firehose to S3 Tables", "IcebergDestinationConfiguration", "Firehose data transformation Lambda", "Firehose error bucket", "Iceberg.MissingColumnWithinRecord", "MissingColumnWithinRecord", or any time someone is wiring a Kinesis Data Stream / Direct PUT source to Iceberg tables and producer record shape does not match the Iceberg column layout.
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