Best Practices for data pipeline costs and setting up Guardrails?

I don't have much details of what features are there in AWS, but just some ideas that you can combine

• Setup quotas: configure a soft and hard limit on how many nodes can be there in a cluster. Perhaps quotas per team?
• Two party control: any change to nodes in a cluster should be approved by one additional person.

Just a few quick thoughts.

> To prevent such instances in the future, we're exploring ways to streamline monitoring and accurately calculate the costs of each instance. However, this can be time-consuming.

You probably don't want to manually calculate it (whether each instance refer to each EMR cluster or node or incident). AWS has daily cost report and it should be straightforward to set up alarm / emails on those. https://docs.aws.amazon.com/cur/latest/userguide/what-is-cur.html I heard my manager would get monthly (or some other cadence) AWS usage report and based on that AWS doc, daily report seems possible.

You mentioned "multiple teams". Are all your orgs' EMR cost going into your team? If so, it's good to consider a campaign to have each team use their own accounts / bill. This feels like playing organizational politic to kick the bill around, but I guess it's fair to do so. Maybe some teams don't know they have a huge bill.

Depending on your specific situation, maybe it's time to consider other means of computation or the query. Are you using unnecessary joins and what are the bottleneck of the query? Are there duplicated computation across different workflows? Are you using parallelization effectively (e.g.Spark needs DRA enabled to utilize more nodes, maybe different file read function could help, just more perf tuning stuff like https://spark.apache.org/docs/latest/sql-performance-tuning.html

Process-wise, it's good to bring your team together to discuss ideas versus individuals thinking really hard in silos. Usually more discussions lead to more ideas and then you can funnel down which ideas to chase.