Inefficient warehouse utilization and queries can increase Snowflake costs and limit the amount of resources used within the platform. Because efficient use of Snowflake resources is an important concern for any organization, Hakkoda has created an AI monitoring tool to optimize Snowflake computation through interactive alerts and visualizations.
Introducing Hakkoda Resource Monitoring. HakkodaRM works by flagging inefficient warehouse utilization, scanning SQL, rewriting queries, and allocating warehouse use through a machine learning engine. HakkodaRM offers a full portfolio of solutions for businesses across verticals and use cases, improving time-series warehouse computation, increasing task and stream transparency, and improving forecasting for users.
Through AI optimizations, HakkodaRM is also able to work on inefficient queries and databases by alerting users across teams, sending email and Microsoft Teams notifications, as well as deploying an interactive Slack bot to assist users with managing alerts. The drag and drop Query Optimizer has proven incredibly useful for teams looking to prevent rising costs and manage Snowflake’s consumption-based model in an effective environment for multiple users.
In the near future, HakkodaRM will include fully autonomous Query Optimization.