Request-based auto scaling in GCP - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

How does request-based auto scaling respond to traffic spikes?

In Google Cloud Run, when request-based auto scaling is enabled, what happens if your service suddenly receives a large number of requests?

A Cloud Run rejects new requests until the traffic decreases to the previous level.

B Cloud Run instantly creates new instances to handle all incoming requests without delay.

C Cloud Run queues all requests until the existing instances finish processing, then creates new instances.

D Cloud Run gradually adds new instances based on the number of concurrent requests per instance until the traffic is handled efficiently.

💡 Hint

Think about how Cloud Run balances load and scales instances smoothly.

Cloud Run uses request-based auto scaling to add instances gradually based on concurrent requests per instance. It does not instantly create all instances nor reject requests.

❓ Configuration

intermediate

Configuring max instances for request-based auto scaling

You want to limit the maximum number of instances your Cloud Run service can scale to during high traffic. Which configuration setting controls this limit?

A Setting the <code>min-instances</code> flag to zero in the Cloud Run service configuration.

B Setting the <code>max-instances</code> flag in the Cloud Run service deployment configuration.

C Setting the <code>concurrency</code> value to 1 in the Cloud Run service configuration.

D Setting the <code>timeout</code> value to the lowest possible number.

💡 Hint

Think about which setting limits the upper bound of instances.

The max-instances setting limits how many instances Cloud Run can create, controlling maximum scale.

❓ Architecture

advanced

Designing a Cloud Run service for efficient request-based auto scaling

You have a Cloud Run service that processes image uploads. To optimize cost and performance, which architecture choice best supports efficient request-based auto scaling?

A Set concurrency to 1 and allow max-instances to scale to 100, so each instance handles one request at a time but many instances can run.

B Set concurrency to 1 and max-instances to 1, so only one instance handles all requests sequentially.

C Set concurrency to a higher number like 80 and limit max-instances to a moderate number like 10, so each instance handles multiple requests concurrently.

D Set concurrency to 1000 and max-instances to 1, so one instance handles all requests concurrently.

💡 Hint

Think about balancing instance count and concurrency for cost and performance.

Higher concurrency with moderate max-instances allows efficient use of resources and smooth scaling.

❓ security

advanced

Security considerations with request-based auto scaling in Cloud Run

When using request-based auto scaling in Cloud Run, what is a key security best practice to protect your service from sudden traffic spikes caused by malicious requests?

A Use Cloud Armor or similar tools to filter and block malicious traffic before it reaches Cloud Run.

B Increase the request timeout to allow long-running requests to complete.

C Set max-instances to unlimited to handle any traffic volume without restrictions.

D Disable authentication to allow all requests to pass through quickly for scaling.

💡 Hint

Think about how to prevent bad traffic from causing resource waste.

Using Cloud Armor helps filter malicious traffic, protecting your service and controlling scaling costs.

✅ Best Practice

expert

Optimizing request-based auto scaling for cost and latency

You want to optimize your Cloud Run service to balance cost and latency during unpredictable traffic. Which combination of settings and practices achieves this best?

A Set concurrency moderate, max-instances moderate, and enable minimum instances to reduce cold starts while controlling cost.

B Set concurrency high, max-instances low, and disable minimum instances to save cost but accept cold starts.

C Set concurrency to 1, max-instances high, and enable minimum instances to keep some instances always warm.

D Set concurrency low, max-instances low, and disable minimum instances to minimize resource usage.

💡 Hint

Think about trade-offs between keeping instances warm and controlling max scale.

Moderate concurrency and max-instances with minimum instances enabled balances latency and cost effectively.

Practice

1. What does request-based auto scaling primarily adjust in a cloud service?

easy

A. The number of server instances based on incoming requests

B. The amount of storage space available

C. The network bandwidth allocation

D. The security settings of the service

Solution

1. Step 1: Understand the purpose of request-based auto scaling

   Request-based auto scaling changes resources based on the number of incoming requests to handle load efficiently.

2. Step 2: Identify what is adjusted

   The main resource adjusted is the number of server instances to match demand.

3. Final Answer:

   The number of server instances based on incoming requests -> Option A

4. Quick Check:

   Scaling adjusts instances = A [OK]

Hint: Auto scaling changes instance count, not storage or security [OK]

Common Mistakes:

• Confusing scaling with storage or bandwidth changes
• Thinking it adjusts security settings
• Assuming it changes fixed resources regardless of requests

2. Which of the following is the correct way to set the minimum number of instances in a GCP service YAML configuration for request-based auto scaling?

easy

A. min-instances: 2

B. minInstances: 2

C. minimum_instances: 2

D. min_instances: 2

Solution

1. Step 1: Recall GCP YAML syntax for scaling parameters

   GCP uses kebab-case for configuration keys like min-instances.

2. Step 2: Identify the correct key format

   The correct key to set minimum instances is min-instances, not camelCase or underscored.

3. Final Answer:

   min-instances: 2 -> Option A

4. Quick Check:

   Use kebab-case keys like min-instances [OK]

Hint: Use kebab-case keys like min-instances in GCP YAML [OK]

Common Mistakes:

• Using camelCase or underscores instead of kebab-case
• Misspelling the key name
• Confusing min-instances with max-instances

3. Given this snippet of a GCP service configuration for request-based auto scaling:

concurrency: 10
min-instances: 1
max-instances: 5

What happens when the service receives 50 simultaneous requests?

medium

A. The service scales down to 0 instances to save cost

B. The service stays at 1 instance because min-instances is set

C. The service scales up to 10 instances because concurrency is 10

D. The service scales up to 5 instances to handle the load

Solution

1. Step 1: Understand concurrency and instance limits

   Concurrency 10 means each instance can handle 10 requests at once. Max-instances is 5, min-instances is 1.

2. Step 2: Calculate needed instances for 50 requests

   50 requests / 10 concurrency = 5 instances needed, which matches max-instances.

3. Final Answer:

   The service scales up to 5 instances to handle the load -> Option D

4. Quick Check:

   Requests/concurrency = instances needed = 5 [OK]

Hint: Divide requests by concurrency, respect max-instances limit [OK]

Common Mistakes:

• Ignoring max-instances limit
• Confusing concurrency with max-instances
• Assuming scaling down when load increases

4. You configured a GCP service with:

concurrency: 5
min-instances: 2
max-instances: 4

But the service never scales above 2 instances even under heavy load. What is the most likely cause?

medium

A. The concurrency value is too high, limiting scaling

B. The max-instances value is too low to allow scaling beyond 2

C. The min-instances value is preventing scaling down

D. The service needs a restart to apply scaling changes

Solution

1. Step 1: Analyze max-instances and min-instances settings

   Max-instances is set to 4, min-instances is 2. Scaling cannot exceed max-instances.

2. Step 2: Understand why scaling stops at 2

   If the service never goes above 2 instances, max-instances might be set too low or misinterpreted.

3. Final Answer:

   The max-instances value is too low to allow scaling beyond 2 -> Option B

4. Quick Check:

   Max-instances limits max scale = B [OK]

Hint: Check max-instances to allow scaling beyond min-instances [OK]

Common Mistakes:

• Confusing min-instances with max-instances
• Assuming concurrency limits scaling up
• Forgetting to check applied config values

5. You want to optimize cost and performance for a GCP service that experiences unpredictable traffic spikes. Which configuration best balances fast scaling up and cost savings during idle times?

hard

A. Set concurrency to 1, min-instances to 0, max-instances to 10

B. Set concurrency to 50, min-instances to 5, max-instances to 5

C. Set concurrency to 10, min-instances to 1, max-instances to 10

D. Set concurrency to 100, min-instances to 10, max-instances to 20

Solution

1. Step 1: Understand concurrency and instance settings impact

   Lower concurrency means more instances needed; min-instances controls baseline cost; max-instances limits scale.

2. Step 2: Evaluate options for balancing cost and performance

   Set concurrency to 10, min-instances to 1, max-instances to 10 uses moderate concurrency (10), low min-instances (1) to save cost, and high max-instances (10) to handle spikes.

3. Final Answer:

   Set concurrency to 10, min-instances to 1, max-instances to 10 -> Option C

4. Quick Check:

   Moderate concurrency + low min + high max = balanced scaling [OK]

Hint: Moderate concurrency with low min and high max balances cost and spikes [OK]

Common Mistakes:

• Setting concurrency too low causing many instances
• Setting min-instances too high increasing cost
• Setting max-instances too low limiting scaling