Cloud Functions pricing in GCP - Cheat Sheet & Quick Revision

Recall & Review

beginner

What are the main factors that affect the cost of Google Cloud Functions?

The main factors are the number of function invocations, the compute time (how long your function runs), and the amount of memory allocated to the function.

beginner

How does Google Cloud Functions charge for compute time?

Compute time is charged based on the time your function runs, measured in 100-millisecond increments, multiplied by the memory size allocated to the function.

beginner

What is a free tier in Cloud Functions pricing?

The free tier offers a monthly allowance of free invocations, compute time, and networking, so you can run small workloads without cost.

intermediate

Why is memory allocation important in Cloud Functions pricing?

Because cost depends on memory size and execution time, choosing the right memory size helps balance performance and cost.

intermediate

How does network egress affect Cloud Functions pricing?

Network egress (data sent out from the function) is charged separately based on the volume of data leaving Google Cloud, which can add to the total cost.

Which of the following does NOT directly affect Cloud Functions pricing?

A Number of function invocations

B Function execution time

C Memory allocated to the function

D Number of users accessing the function's website

Pricing depends on invocations, execution time, and memory, not on the number of users accessing a website.

How is compute time measured for billing in Cloud Functions?

A Per 100 milliseconds

B Per second

C Per minute

D Per hour

Compute time is billed in 100-millisecond increments.

What does the free tier for Cloud Functions include?

A Unlimited invocations

B Free invocations, compute time, and networking up to a limit

C Free storage space

D Free database queries

The free tier includes a monthly limit of free invocations, compute time, and networking.

Why should you choose the right memory size for your Cloud Function?

A To improve security

B To reduce latency only

C To balance performance and cost

D Memory size does not affect cost

Memory size affects both performance and cost, so choosing the right size is important.

What is network egress in Cloud Functions pricing?

A Data sent out from the function

B Data sent into the function

C Internal data processing

D Function invocation count

Network egress is the data sent out from the function and is charged separately.

Explain how Google Cloud Functions pricing works including the main cost factors and the role of the free tier.

Think about what you pay for when your function runs and how Google offers some free usage.

Describe why memory size and execution time are important when estimating Cloud Functions cost.

Consider how longer running or bigger memory functions cost more.

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