Cloud Functions pricing in GCP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the billing unit for Cloud Functions memory allocation.

GCP

memory: [1]

Drag options to blanks, or click blank then click option'

A256MB

B256

C256GB

D256KB

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number without unit like '256'

Using incorrect units like GB or KB

The memory for Cloud Functions is specified in megabytes (MB), such as '256MB'.

2fill in blank

medium

Complete the code to set the maximum function execution time in seconds.

GCP

timeout: [1]

Drag options to blanks, or click blank then click option'

A300ms

B540s

C540

D5m

Attempts:

3 left

💡 Hint

Common Mistakes

Using only a number without unit

Using 'ms' or 'm' instead of 's'

The timeout for Cloud Functions is set in seconds with 's' suffix, e.g., '540s' for 9 minutes.

3fill in blank

hard

Fix the error in the billing configuration by selecting the correct CPU allocation format.

GCP

cpu: [1]

Drag options to blanks, or click blank then click option'

A1000m

B1vCPU

C1cpu

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using '1' without units

Using '1vCPU' which is invalid

Using lowercase 'cpu' without 'm'

CPU allocation in Cloud Functions is specified in millicores, e.g., '1000m' means 1 full CPU.

4fill in blank

hard

Fill both blanks to correctly calculate the total billed GB-seconds for a function.

GCP

billed_gb_seconds = memory_in_gb [1] execution_time_seconds [2]

Drag options to blanks, or click blank then click option'

A*

B+

C/

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using division or subtraction instead of multiplication

Mixing operators incorrectly

The total billed GB-seconds is calculated by multiplying memory in GB by execution time in seconds, then adding any overhead if applicable.

5fill in blank

hard

Fill all three blanks to define a pricing formula for Cloud Functions including memory, CPU, and invocation count.

GCP

total_cost = (memory_gb [1] memory_rate) + (cpu_units [2] cpu_rate) + (invocations [3] invocation_rate)

Drag options to blanks, or click blank then click option'

A*

B+

C-

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition instead of multiplication for rates

Using division or subtraction incorrectly

The pricing formula multiplies each resource usage by its rate, then sums all costs.

Practice

1. What are the main factors that determine the cost of Google Cloud Functions?

easy

A. Number of API calls, database queries, and cache hits

B. Number of invocations, compute time, and outbound data

C. CPU type, memory size, and disk I/O

D. Number of users, storage size, and network speed

Solution

1. Step 1: Identify pricing components

   Google Cloud Functions pricing is based on how many times functions run (invocations), how long they run (compute time), and how much data they send out (outbound data).

2. Step 2: Match factors to options

   Number of invocations, compute time, and outbound data lists these exact factors, while others mention unrelated metrics like users or storage.

3. Final Answer:

   Number of invocations, compute time, and outbound data -> Option B

4. Quick Check:

   Pricing factors = invocations, compute time, outbound data [OK]

Hint: Remember: cost depends on usage, not users or storage [OK]

Common Mistakes:

• Confusing storage or users with function pricing
• Thinking CPU type alone affects cost
• Mixing up inbound and outbound data charges

2. Which of the following is the correct way to describe the free tier for Google Cloud Functions?

easy

A. It offers unlimited invocations and compute time for all users

B. It charges a small fee for every invocation regardless of usage

C. It provides a fixed number of free invocations and compute time each month

D. It only applies to functions running in specific regions

Solution

1. Step 1: Understand free tier basics

   The free tier gives a set amount of free invocations and compute time monthly, not unlimited usage.

2. Step 2: Compare options

   It provides a fixed number of free invocations and compute time each month correctly states the free tier provides fixed free usage. It offers unlimited invocations and compute time for all users is wrong because it says unlimited. It charges a small fee for every invocation regardless of usage is wrong because free tier means no charge up to limits. It only applies to functions running in specific regions is incorrect as free tier applies globally.

3. Final Answer:

   It provides a fixed number of free invocations and compute time each month -> Option C

4. Quick Check:

   Free tier = fixed free usage monthly [OK]

Hint: Free tier means limited free usage, not unlimited [OK]

Common Mistakes:

• Assuming free tier is unlimited
• Thinking free tier applies only in some regions
• Believing every invocation is charged

3. A Cloud Function runs 1,000,000 times in a month, each execution lasting 200 milliseconds with 256 MB memory allocated. Which factor primarily affects the compute time cost?

medium

A. Number of invocations only

B. Outbound data volume

C. Function trigger type

D. Execution duration and memory size

Solution

1. Step 1: Identify compute time cost factors

   Compute time cost depends on how long the function runs and how much memory it uses during execution.

2. Step 2: Analyze options

   Execution duration and memory size correctly identifies execution duration and memory size as key for compute cost. Invocations count affects invocation cost, not compute time alone. Outbound data and trigger type do not affect compute time cost.

3. Final Answer:

   Execution duration and memory size -> Option D

4. Quick Check:

   Compute cost = duration x memory [OK]

Hint: Compute cost = run time x memory size [OK]

Common Mistakes:

• Confusing invocation count with compute time cost
• Ignoring memory size in cost calculation
• Thinking trigger type affects compute cost

4. You notice your Cloud Function costs are unexpectedly high. Which of the following is the most likely cause?

medium

A. Function runs longer than expected or uses more memory

B. You exceeded the free tier for outbound data only

C. You deployed the function in multiple regions accidentally

D. You used a deprecated runtime version

Solution

1. Step 1: Identify common cost drivers

   High costs usually come from functions running longer or using more memory, increasing compute time charges.

2. Step 2: Evaluate other options

   You exceeded the free tier for outbound data only is less likely since outbound data is often smaller cost. You deployed the function in multiple regions accidentally might increase cost but is less common. You used a deprecated runtime version affects functionality, not pricing directly.

3. Final Answer:

   Function runs longer than expected or uses more memory -> Option A

4. Quick Check:

   Longer run or more memory = higher cost [OK]

Hint: Check function duration and memory to find cost spikes [OK]

Common Mistakes:

• Blaming deprecated runtime for cost increase
• Ignoring function execution time impact
• Assuming outbound data is main cost driver

5. You want to optimize costs for a Cloud Function that processes large files and sends results over the network. Which combination of strategies will most effectively reduce your bill?

hard

A. Reduce function memory allocation and minimize outbound data size

B. Increase function timeout and add more retries

C. Deploy multiple identical functions in different regions

D. Use a higher memory allocation to speed up execution regardless of data size

Solution

1. Step 1: Identify cost factors for large file processing

   Costs come from compute time (affected by memory and duration) and outbound data size.

2. Step 2: Evaluate optimization strategies

   Reducing memory allocation lowers compute cost if performance is sufficient. Minimizing outbound data reduces network charges. Increasing timeout or retries raises cost. Deploying multiple functions increases cost. Higher memory may speed execution but can increase cost if not balanced.

3. Final Answer:

   Reduce function memory allocation and minimize outbound data size -> Option A

4. Quick Check:

   Lower memory + less data = cost savings [OK]

Hint: Cut memory and data size to save costs effectively [OK]

Common Mistakes:

• Thinking more memory always reduces cost
• Adding retries without cost consideration
• Deploying duplicates increases cost unnecessarily