Concurrency and scaling in GCP - Step-by-Step Execution

Process Flow - Concurrency and scaling

User Requests Arrive

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Load Balancer Distributes

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Multiple Instances Handle Requests

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Monitor Performance & Load

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Scale Up or Down Instances

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Maintain Service Availability

User requests come in and are spread by a load balancer to many instances. The system watches load and adds or removes instances to keep service smooth.

Execution Sample

GCP

1. User sends 10 requests
2. Load balancer sends 5 requests per instance
3. Instances process requests concurrently
4. Monitor detects high load
5. Add 2 more instances
6. Load balancer redistributes requests

This simulates how requests are handled concurrently by multiple instances and how scaling adds instances to handle more load.

Process Table

Step	Action	Instances Active	Requests per Instance	Total Requests	Scaling Event
1	10 user requests arrive	2	0	10	No
2	Load balancer distributes requests	2	5	10	No
3	Instances process requests concurrently	2	5	10	No
4	Monitor detects high CPU load	2	5	10	Yes - scale up
5	Add 2 more instances	4	0	10	Yes - added 2 instances
6	Load balancer redistributes requests	4	2.5	10	No
7	Instances process requests concurrently	4	2.5	10	No
8	Load decreases, monitor detects low load	4	2.5	10	Yes - scale down
9	Remove 2 instances	2	0	10	Yes - removed 2 instances
10	Load balancer redistributes requests	2	5	10	No
11	Instances process requests concurrently	2	5	10	No
12	No more scaling needed	2	5	10	No

💡 Load stabilizes, no further scaling needed

Status Tracker

Variable	Start	After Step 2	After Step 5	After Step 6	After Step 9	Final
Instances Active	2	2	4	4	2	2
Requests per Instance	0	5	0	2.5	0	5
Total Requests	10	10	10	10	10	10
Scaling Event	No	No	Yes - added 2	No	Yes - removed 2	No

Key Moments - 3 Insights

Why does the number of requests per instance drop after scaling up?

Because the total requests are shared among more instances, so each instance handles fewer requests (see execution_table step 6).

Why do we remove instances when load decreases?

To save resources and cost by having fewer instances when demand is low (see execution_table step 9).

Does scaling happen instantly when load changes?

No, monitoring detects load changes and triggers scaling events, which take some time to add or remove instances (see steps 4-5 and 8-9).

Visual Quiz - 3 Questions

Look at the execution_table at step 6, how many requests does each instance handle?

A 2.5

B 5

C 10

D 0

💡 Hint

Check the 'Requests per Instance' column at step 6 in the execution_table.

At which step does the system add more instances?

A Step 9

B Step 4

C Step 5

D Step 2

💡 Hint

Look for the 'Scaling Event' column indicating 'added 2 instances' in the execution_table.

If total requests increased to 20 at step 1, what would happen to requests per instance before scaling?

A It would be 20 per instance

B It would be 10 per instance

C It would be 5 per instance

D It would be 0

💡 Hint

Divide total requests by instances active before scaling (see variable_tracker and execution_table step 2).

Concept Snapshot

Concurrency and scaling in cloud means handling many user requests at once by spreading them across multiple instances.
A load balancer sends requests to instances.
Monitoring watches load and adds or removes instances to keep service smooth.
Scaling up means adding instances; scaling down means removing them.
This keeps the service fast and cost-effective.

Full Transcript

Concurrency and scaling in cloud infrastructure means that many user requests come in at the same time and are handled by multiple server instances working together. A load balancer spreads the requests evenly so no single instance is overloaded. The system monitors how busy the instances are. If they get too busy, it adds more instances to share the work. If they are not busy, it removes some instances to save resources. This process keeps the service running smoothly and efficiently. The execution table shows how requests are divided among instances and how scaling events add or remove instances based on load.