Cloud Functions pricing in GCP - Commands & Configuration

Introduction

Cloud Functions pricing helps you understand how much you pay when your small pieces of code run in the cloud. It solves the problem of knowing your costs based on how often and how long your code runs.

When you want to know how much your serverless functions cost after running them.

When you need to estimate your monthly bill based on function usage.

When you want to control costs by understanding what affects pricing.

When you want to compare costs between different cloud providers.

When you plan to optimize your functions to reduce expenses.

Commands

This command shows details about your deployed Cloud Function, including its configuration and usage metrics that affect pricing.

Terminal

gcloud functions describe example-function --region=us-central1

Expected Output

name: projects/my-project/locations/us-central1/functions/example-function

status: ACTIVE

entryPoint: helloWorld

runtime: nodejs18

availableMemoryMb: 256

timeout: 60s

httpsTrigger:

  url: https://us-central1-my-project.cloudfunctions.net/example-function

sourceUploadUrl: https://storage.googleapis.com/gcf-upload-us-central1/...

updateTime: '2024-06-01T12:00:00Z'

versionId: '1'

→

--region - Specifies the region where the function is deployed.

This command fetches the last 5 log entries for your function to help you see how often it runs and if there are any errors affecting cost.

Terminal

gcloud functions logs read example-function --limit=5 --region=us-central1

Expected Output

2024-06-01 12:01:00 example-function: Function execution started

2024-06-01 12:01:01 example-function: Function execution finished

2024-06-01 12:02:00 example-function: Function execution started

2024-06-01 12:02:01 example-function: Function execution finished

2024-06-01 12:03:00 example-function: Function execution started

→

--limit - Limits the number of log entries returned.

→

--region - Specifies the region of the function.

This command lists your billing budgets to help you monitor and control your Cloud Functions spending.

Terminal

gcloud billing budgets list

Expected Output

NAME                AMOUNT  FILTERS

monthly-budget      100.00  service=cloudfunctions.googleapis.com

Key Concept

If you remember nothing else from this pattern, remember: Cloud Functions pricing depends mainly on how many times your function runs, how long it runs, and how much memory it uses.

Common Mistakes

Ignoring the function's memory size when estimating costs.

Memory size affects the price per 100ms of execution, so ignoring it leads to wrong cost estimates.

Always check and include the memory allocation of your function when calculating pricing.

Not considering the number of invocations in cost calculations.

Each function call counts as an invocation and adds to the cost, so missing this leads to underestimating expenses.

Count all invocations when estimating your monthly cost.

Assuming free tier covers all usage.

Free tier has limits; exceeding them results in charges.

Track your usage to know when you go beyond the free tier.

Summary

Use 'gcloud functions describe' to see function details affecting pricing.

Check function logs to understand invocation frequency and errors.

Use billing budgets to monitor and control your Cloud Functions 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