Auto Scaling with ELB integration in AWS - Step-by-Step Execution

Process Flow - Auto Scaling with ELB integration

Start: Define Launch Configuration

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Create Auto Scaling Group

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Attach ELB to Auto Scaling Group

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Monitor Metrics (CPU, etc.)

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Scale Out: Increase Instances

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ELB Distributes Traffic to New Instances

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Scale In: Decrease Instances

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ELB Removes Terminated Instances

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End: Desired Capacity Maintained

The flow starts by defining how instances launch, then creates a group that can grow or shrink. The ELB is attached to balance traffic. Metrics trigger scaling, and ELB updates targets accordingly.

Execution Sample

AWS

1. Define Launch Configuration
2. Create Auto Scaling Group with min=1, max=3
3. Attach ELB to Auto Scaling Group
4. CPU > 70% triggers scale out
5. CPU < 30% triggers scale in

This setup automatically adds or removes instances based on CPU load, with ELB balancing traffic among active instances.

Process Table

Step	CPU Utilization (%)	Auto Scaling Action	Instance Count	ELB Target Instances
1	25	No action	1	[Instance1]
2	75	Scale out	2	[Instance1, Instance2]
3	80	No action	2	[Instance1, Instance2]
4	20	Scale in	1	[Instance1]
5	50	No action	1	[Instance1]

💡 CPU stabilizes between thresholds, no further scaling needed

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5
CPU Utilization (%)	N/A	25	75	80	20	50
Instance Count	1	1	2	2	1	1
ELB Target Instances	[Instance1]	[Instance1]	[Instance1, Instance2]	[Instance1, Instance2]	[Instance1]	[Instance1]

Key Moments - 2 Insights

Why does the ELB remove Instance1 after scaling in at step 4?

Because the Auto Scaling Group terminated Instance2 to reduce capacity, ELB updates its targets to only include active instances, as shown in execution_table step 4.

Why is there no scaling action at step 3 even though CPU is 80%?

Scaling out already happened at step 2, so the group is at increased capacity. The policy waits for metrics to drop before scaling again, as seen in execution_table step 3.

Visual Quiz - 3 Questions

Look at the execution table, what is the instance count after step 2?

A 1

B 2

C 3

D 0

💡 Hint

Check the 'Instance Count' column in execution_table row for step 2

At which step does the ELB remove an instance from its targets?

A Step 4

B Step 2

C Step 1

D Step 5

💡 Hint

Look at the 'ELB Target Instances' column changes in execution_table

If CPU stayed at 85% after step 3, what would likely happen next?

A No scaling action

B Scale in to 1 instance

C Scale out to 3 instances

D Terminate all instances

💡 Hint

Refer to the scaling policy in execution_sample and instance count limits

Concept Snapshot

Auto Scaling with ELB integration:
- Define launch config and Auto Scaling Group
- Attach ELB to distribute traffic
- Monitor metrics (e.g., CPU)
- Scale out when metric > threshold
- Scale in when metric < threshold
- ELB updates targets automatically

Full Transcript

This visual execution shows how Auto Scaling works with an Elastic Load Balancer (ELB). First, a launch configuration defines how instances start. Then, an Auto Scaling Group is created with minimum and maximum instance counts. The ELB is attached to this group to balance incoming traffic. The system monitors CPU utilization. When CPU goes above 70%, the group adds an instance (scale out). When CPU drops below 30%, it removes an instance (scale in). The ELB updates its target list to include only active instances. This keeps the application responsive and efficient automatically.