Azure Monitor capability that adds or removes instances on a schedule or once a metric rule has been true for its full duration. The maximum instance count merely sets a ceiling and never triggers scaling itself.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Autoscale in context, with comparison tables and the common traps.
Terms in this definition
- Azure Monitor
Observability platform for Azure that brings together metrics, logs and traces from both Azure and hybrid resources so they can be analysed and alerted on.
- Capability
Something that a person, organisation or system is able to do.
- metric
Measurement over time that VCF Operations gathers for an object, such as CPU usage. A policy turns collection of each one on or off, or lets it inherit the setting.
- Instance count
In a DLP rule condition, the minimum and maximum number of distinct matches of a sensitive information type that an item needs before the condition is met.
Related terms
- App Service
Managed PaaS hosting for web apps and Web App for Containers, run in a sandbox without OS access. Deployment slots and autoscale start at the Standard tier.
- Availability set
Grouping that distributes VMs across as many as 3 fault domains and 20 update domains inside a single datacentre, backed by a 99.95% SLA. It offers neither autoscale nor zone distribution.
- Capacity Planner
In preview, this eventhouse option stops the eventhouse from suspending when it's idle by keeping it always on. You can also set a floor of CUs for each hour-long slot across the week, while autoscale continues to operate.
- Cooldown
How long autoscale waits after scaling before any rule may act again, 5 minutes by default; this differs from the period over which the metric is evaluated.
- Custom Spark pool
A Spark pool built by a workspace Admin to their own specification, choosing the size and family of nodes, autoscale limits and whether executors scale dynamically. It needs a capacity that allows pool customisation and usually takes about three minutes to start, unless it's running as a live pool.
- Dedicated plan
Running Azure Functions on App Service plan instances, paying App Service rates. Instance counts change manually or through autoscale, not in response to incoming events, and enabling Always On stops non-HTTP triggers going idle.
- Dynamic allocation
Lets a Spark application grow and shrink its executor count with demand, adding them when busy and giving them up when idle, up to a ceiling set by the workspace admin. In Spark pools the option is named Dynamically allocate executors and is enabled by default together with Autoscale.
- Managed online endpoint
Azure Machine Learning online endpoint where Azure provisions and runs the compute for you; it offers autoscale, traffic mirroring and splitting traffic between deployments.