Cloud infrastructure cost management

Infrastructure cost management

Data health insights you need to manage and reduce storage and compute costs

That’s the beauty of Monte Carlo because it allows us to see who is using data and where it is being consumed. This has allowed us to actually free up some of our processing time from unused data elements which were no longer relevant.

Valerie Rogoff, Director of Analytics Data Architecture

Optimize data storage and compute

With end-to-end observability, Monte Carlo equips your team with automated circuit breakers to avoid costly backfill costs, and on-demand data health insights to optimize storage and compute.

Avoid costly data backfills

Automatically stop Airflow DAGs and other transformation jobs as soon as an error occurs with Monte Carlo’s circuit breakers.

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Avoid costly data backfills

Reduce compute costs

Monte Carlo automatically identifies high consumption and deteriorating queries to help your team reduce your compute bill.

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Reduce compute costs

Optimize data warehouse storage

Identify and sunset unused data tables to reduce your warehouse storage costs.

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Optimize data warehouse storage

End-to-end data observability

Monte Carlo enables data teams to ensure reliable data and accelerate the adoption of data; learn more about data observability platforms:

Anomaly detection

Anomaly detection

Pipeline health coverage across all your production tables and data quality monitors for your most critical assets.

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Incident resolution

Incident resolution

Automated troubleshooting to resolve data incidents and anomalies as soon as they occur.

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Proactive data reliability

Proactive data reliability

Data health insights enable your team to proactively ensure data quality, and make better infrastructure investment decisions.

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Getting pressure to reduce your infrastructure costs?

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