Coverage
Azure data and analytics cost optimisation for MSPs
Much data platform spend goes on compute that is provisioned but idle. Microsoft's Azure Databricks guidance notes that teams often leave warehouses running through quiet periods to avoid start-up delays, and that always-on streaming costs money every hour even when the business only needs data refreshed a few times a day.
23
automated finders for data and analytics
Read-only, across every connected client tenant, tied to real billing data.
- Commitments
- Modernise
- Remove unused
- Rightsizing
- Scaling
- Off-hours schedules
Where data and analytics spend goes to waste
The main cost levers Microsoft documents for data and analytics, and the ones an MSP should check across every client.
Pause idle Fabric capacity on a schedule
F SKU capacities can be paused when they aren't in use, and billing only resumes with the capacity. Pausing makes content on that capacity unavailable, so confirm it is idle first, and schedule pause and resume with automation rather than relying on manual clicks. [2]
Auto-terminate clusters and use job compute
Scheduled, non-interactive workloads cost significantly less on job compute than on all-purpose clusters, and every interactive cluster should shut down after a set idle period. Compute policies can enforce auto-termination, autoscaling and cost-efficient VM types. [1]
Pause or scale down dedicated SQL pools
Compute and storage are priced separately, so pausing a dedicated SQL pool cuts compute charges to zero and keeps the data. Scale out before heavy loads and back in afterwards, and let in-flight transactions finish first, because pausing or scaling cancels running queries. [3]
Pick the lightest AI Search tier that fits
Dedicated search services are billed hourly for every search unit, which is replicas multiplied by partitions. Add partitions only for index size or ingestion, and replicas only for query volume or high availability. [4]
Rightsize Redis and plan the migration
The Basic tier runs on a single VM without an SLA and suits development, test and non-critical workloads. A cache can move up a tier after creation but can't move down. Microsoft has announced retirement for all Azure Cache for Redis SKUs and recommends moving to Azure Managed Redis. [5]
Stop, downsize and reserve flexible servers
Run dev, test and staging databases on the Burstable tier and stop them when unused. For steady PostgreSQL production servers, reserved capacity can save up to 40% on a one-year term and up to 60% on three years, compared with pay-as-you-go. [6]
How Cerberus Cloud covers data and analytics
Cerberus Cloud runs 23 automated finders for data and analytics across every connected client tenant. Each one ties a technical signal to real billing data, so findings arrive with an estimated recoverable value, ranked by impact, effort and risk, with evidence and remediation scripts for your engineers to review.
Access is read-only, so nothing changes in a client environment until your team decides it should. See how it works or the multi-tenant portfolio view.
- Commitments
- Modernise
- Remove unused
- Rightsizing
- Scaling
- Off-hours schedules
Frequently asked questions
- Is it worth reserving Fabric capacity that we also plan to pause?
- Usually not for the same capacity units. The reservation discount is applied hour by hour, and reserved units with no matching capacity running in that hour are lost, so pausing reserved capacity doesn't cut its cost. Reserve the always-on baseline instead.
- Can we pause a client's AI Search service out of hours?
- Not on the dedicated model. Those services run continuously, and the only way to stop billing is to delete the service and its data. Scale replicas and partitions down to what the workload needs instead.
- Can we keep a client's MySQL flexible server stopped long term?
- No. A stopped MySQL flexible server is started automatically after 30 days, and billing resumes when it restarts. For longer, Microsoft suggests exporting the data and deleting the instance.
See data and analytics findings on a sample portfolio
A 15-minute walkthrough: tenant connection, prioritised findings, remediation scripts and savings history.
Sources
Last checked . Product details change; tell us if something here is out of date.
- Microsoft Learn: Azure Databricks cost optimisation best practices
- Microsoft Learn: Pause and resume Fabric capacity
- Microsoft Learn: Manage compute for dedicated SQL pools
- Microsoft Learn: Plan and manage costs for Azure AI Search
- Microsoft Learn: What is Azure Cache for Redis?
- Microsoft Learn: Cost optimisation for Azure Database for PostgreSQL
- Microsoft Learn: Fabric capacity reservations
- Microsoft Learn: Stop and start an Azure Database for MySQL flexible server