In previous posts, we’ve talked about designing tables, distributing data, and writing efficient queries. Now let’s turn our attention to resource management—a crucial area for both performance and cost control in Azure Synapse Dedicated SQL Pools.
Synapse gives you tools to scale compute, manage concurrency, and minimize costs by controlling when and how resources are used. Let’s break it down.
Scale Compute with DWUs
Synapse uses Data Warehousing Units (DWUs) to represent a blend of CPU, memory, and I/O resources.
- Scale up for intensive ETL jobs or large report workloads.
- Scale down when usage is light or predictable.
- Changes can be made dynamically—without data reloads.
This makes it easy to right-size your environment based on demand.
Pause Compute When Idle
One of Synapse’s most powerful cost-saving features is the ability to pause your dedicated SQL pool when it's not in use.
- Storage remains intact and accessible.
- You only pay for storage while paused.
- Schedule automatic pauses outside business hours to reduce cost.
This is ideal for dev/test environments or overnight/off-peak workloads.
Manage Concurrency with Resource Classes
Resource classes control how much memory a query can use and how many queries can run in parallel.
- Assign users to
smallrc,mediumrc, orlargercdepending on their workload needs. - High memory users take up more slots—balance accordingly.
- Helps prevent one query from consuming all available memory.
Workload Isolation
To avoid performance issues from “noisy neighbor” workloads, you can segment users and queries.
- Use Synapse roles and permissions to isolate workloads.
- Combine with resource classes to define resource boundaries.
- Ideal for separating data science, BI, and ETL users.
Monitor Usage & Performance
Visibility into usage helps you optimize both performance and spending.
- Use Synapse Studio and built-in monitoring dashboards.
- Query DMVs (Dynamic Management Views) to analyze query patterns.
- Set up alerts for long-running queries or cost thresholds.
In Part 6, we’ll wrap up the series with a look at monitoring, troubleshooting, and best practices for keeping your Synapse workloads healthy and efficient.