Manage reasoners
Reasoners are virtual machines that process queries and other RelationalAI jobs. They run in the RelationalAI (RAI) Native App’s dedicated Snowflake compute pools on Snowpark Container Services in your Snowflake account. This section of the docs covers how reasoners work and how to manage them to support PyRel users’ workloads.
What reasoners do
Section titled “What reasoners do”Different reasoners can run different types of workloads:
| Type of reasoner | What it does |
|---|---|
| Logic reasoners | Process PyRel semantic model definitions and execute queries. |
| Prescriptive reasoners | Run prescriptive reasoning workloads, like processing and solving decision problems defined in a PyRel model. |
| Predictive reasoners | Run predictive reasoning workloads, like training and using GNNs through PyRel. |
How reasoners are managed
Section titled “How reasoners are managed”PyRel creates and manages reasoners based on its configuration file and the workloads required by the model. As an admin, you can:
- View and monitor reasoners and reasoner usage
- Manage warm (standby) reasoners to reduce startup latency for PyRel programs.
- Scale reasoner capacity to support heavier workloads or reduce costs when workloads are lighter.
Where to go next
Section titled “Where to go next”Monitor reasoner usageMonitor reasoner health and resource use.
Manage reasoner jobsInspect or stop work on a specific reasoner.
Manage logic reasonersLearn how to configure and manage logic reasoners.
Manage prescriptive reasonersLearn how to configure and manage prescriptive reasoners.
Manage predictive reasonersLearn how to configure and manage predictive reasoners.
Enable warm reasonersReduce cold-start latency for logic reasoners.
Scale reasoner capacityIncrease or decrease reasoner capacity to meet workload demands.