Data pipelines and data integrity
Designing data processing pipelines that deliver correct, complete data, with the ability to detect and repair problems.
Data pipelines and data integrity
Designing data processing pipelines that deliver correct, complete data, with the ability to detect and repair problems.
Pipelines as production systems
Batch and streaming pipelines power analytics, ML, and user-facing features, so their reliability matters as much as that of user-facing services.
SREs often apply the same principles—SLOs, monitoring, and incident response—to pipelines as to online services.
Ensuring data integrity
End-to-end checksums, idempotent processing, and reconciliation jobs help ensure that what you read is what you wrote.
Ready to see how this works in the cloud?
Switch to Career Paths for structured paths (e.g. Developer, DevOps) and provider-specific lessons.
View role-based pathsSign in to track your progress and mark lessons complete.
Discussion
Questions? Discuss in the community or start a thread below.
Join DiscordIn-app Q&A
Sign in to start or join a thread.