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View All on GitHubAI 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.
Decompress Fastq Files from ORA to GZIP with serverless compute
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.
Decompress Fastq Files from ORA to GZIP with serverless compute
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.
Decompress Fastq Files from ORA to GZIP with serverless compute