Decompress Fastq Files from ORA to GZIP with serverless compute

3 Open Issues Need Help Last updated: Jul 23, 2025

Open Issues Need Help

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Data Science File Compression/Decompression

AI Summary: Modify the step functions orchestrating the ORA to GZIP fastq file decompression jobs to ensure that if a decompression task fails, the corresponding step function also fails. This change will improve monitoring by allowing easier tracking of failures via Slack.

Complexity: 4/5
enhancement good first issue

Decompress Fastq Files from ORA to GZIP with serverless compute

TypeScript
Data Science File Compression/Decompression

AI Summary: Evaluate the feasibility and implement the use of AWS Fargate Spot instances for the fastq decompression service, prioritizing cost optimization without significantly impacting job completion times. This involves analyzing current job durations, assessing potential risks associated with spot instance interruptions, and modifying the service's infrastructure (likely within the AWS CDK deployment) to utilize spot instances when appropriate, potentially incorporating mechanisms to handle interruptions gracefully.

Complexity: 4/5
enhancement good first issue

Decompress Fastq Files from ORA to GZIP with serverless compute

TypeScript
Data Science File Compression/Decompression

AI Summary: The task involves creating new event schemas for the Fastq Decompression Manager microservice, mirroring the structure found in the Dragen WGTS DNA Pipeline Manager's event schema directory. This includes defining the schema structure in JSON format and potentially registering these schemas with an event schema registry.

Complexity: 2/5
documentation enhancement good first issue

Decompress Fastq Files from ORA to GZIP with serverless compute

TypeScript