Function scaling behavior in Azure - Step-by-Step Execution

Process Flow - Function scaling behavior

Function receives request

↓

Check current load

↓

Is load high?

No→Process request with current instances

Yes↓

Add more function instances

↓

Distribute requests among instances

↓

Process requests in parallel

↓

Monitor load and scale down if low

When a function app gets requests, Azure checks the load. If load is high, it adds more instances to handle requests in parallel, then scales down when load decreases.

Execution Sample

Azure

Trigger function with 1 request
Load increases
Add 2 more instances
Distribute 3 requests
Process in parallel
Scale down when load drops

Shows how Azure Functions scale out by adding instances when load increases and scale in when load decreases.

Process Table

Step	Current Instances	Incoming Requests	Load Check	Action Taken	Result
1	1	1	Low	Process request	1 request processed by 1 instance
2	1	3	High	Add 2 instances	Total 3 instances available
3	3	3	High	Distribute requests	Each instance processes 1 request
4	3	0	Low	Scale down	Reduce to 1 instance
5	1	1	Low	Process request	1 request processed by 1 instance

💡 Load is low, so scaling stabilizes at 1 instance

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
Current Instances	1	1	3	3	1	1
Incoming Requests	0	1	3	3	0	1
Load Status	Low	Low	High	High	Low	Low

Key Moments - 2 Insights

Why does Azure add more instances when requests increase?

Because the load check shows 'High' (see Step 2 in execution_table), Azure adds instances to handle requests in parallel and avoid delays.

Why does Azure reduce instances when no requests come in?

When load is 'Low' again (Step 4), Azure scales down to save resources, keeping only needed instances active.

Visual Quiz - 3 Questions

Look at the execution_table at Step 3, how many requests does each instance process?

A 3 requests per instance

B 1 request per instance

C No requests processed

D All requests processed by one instance

💡 Hint

Check the 'Result' column at Step 3 in execution_table

At which step does Azure add more function instances?

A Step 2

B Step 1

C Step 4

D Step 5

💡 Hint

Look at the 'Action Taken' column for adding instances

If incoming requests stayed at 1, how would the number of instances change?

A Instances would increase to 3

B Instances would decrease to 0

C Instances would stay at 1

D Instances would randomly change

💡 Hint

Refer to variable_tracker for load and instances when requests are low

Concept Snapshot

Azure Functions scale automatically based on load.
When requests increase, Azure adds instances to handle them in parallel.
When load decreases, Azure scales down to save resources.
This ensures efficient processing and cost management.

Full Transcript

Azure Functions automatically adjust the number of running instances based on the incoming request load. When a function app receives more requests than a single instance can handle efficiently, Azure detects the high load and adds more instances to process requests in parallel. This scaling out helps maintain performance. When the load decreases, Azure scales back down to fewer instances to save resources and cost. This behavior ensures that functions run efficiently without manual intervention.