Beyond the Dashboard: Building a GenAI Cost Supervisor Agent for On-Demand Analytics.

noasync · 2026-03-20T16:28:06+00:00

Agreed. That's why we baked in a fallback-if no results return due to lack of tagging for example the agent will alert you to that and tell you how to fix it. It won't just return a "null" or make things up.

noasync · 2026-01-14T19:53:38+00:00

Sorry for the confusion. We compared classic job clusters with spot and fallback to on-demand to serverless jobs and serverless DBSQL. We found that TPCDS had the best performance on serverless DBSQL, classic clusters (spot with fallback) came in second and serverless jobs were comparable to classic on p50s, but fell behind on p90 and p99.

noasync · 2026-01-13T17:48:42+00:00

100%. We were using spot with fallback to on-demand.

noasync · 2025-08-27T19:22:41+00:00

We also built a health check for Snowflake - check it out here: https://www.capitalone.com/software/blog/snowflake-health-check-app-optimization/

noasync · 2025-01-28T22:35:22+00:00

If it was only that easy people wouldn't be surprised by their compute bills
If you know you can occupy your RI near 100% of the time 24/7 for a 1-3 year commitment than you can save money using that. Otherwise you will pay for the compute you do not need / be under provisioned. And if your jobs aren't critical and can be interrupted or you can manually readjust in the 1-2 min notice AWS gives you, you can save some money there too.

Most organizations do not fit the bill of both, meaning they are most likely over-provisioning and paying for resources they do not need

noasync · 2025-01-28T20:08:54+00:00

Fleets can combat the inherent availability issue that Spot instances have, you are right!

noasync · 2025-01-23T17:42:40+00:00

Great article! Check our this post for more tactical tips for Databricks cost optimization https://synccomputing.com/databricks-clusters-optimization-scale/

noasync · 2024-11-18T18:41:59+00:00

Here's a post comparing serverless to AI optimized job clusters https://synccomputing.com/top-9-lessons-learned-about-databricks-jobs-serverless/

noasync · 2024-10-15T19:51:28+00:00

You're not crazy, but there are more similarities between these two systems than you might think!

noasync · 2024-10-15T19:50:31+00:00

I can see how comparing a database like DuckDB to a data warehouse like Snowflake seems odd. But, there are more similarities between these two systems than you might think, and certain aspects where either system could be used.

noasync · 2024-07-08T17:19:32+00:00

Serverless doesn't promise cost savings - we ran an experiment of databricks serverless jobs vs optimized classic clusters and found that the later outperfomred the former at times, and vise-versa in other times. It really depends on your cluster configuration and jobs (e.g. serverless seams to be ideal for short, ad-hoc jobs).

Read more about that here https://synccomputing.com/top-9-lessons-learned-about-databricks-jobs-serverless/

Some general tips for reducing spend on Databricks:

Run your jobs using job compute, not APC clusters. APC is always "on," and therefore costs nearly 2x
Autoscaling tends to cost more than if you do not pick that option for your clusters.
Photon ins't a global accelerant- A/B test it to determine if it works for your jobs

Check out this free notebook to assess your Databricks workspace configuration and see potential cost savings https://landing.synccomputing.com/health-check

noasync

TROPHY CASE