Function deployment and testing in GCP - Step-by-Step Execution

Process Flow - Function deployment and testing

Write function code

↓

Package code and dependencies

↓

Deploy function to GCP

↓

Trigger function (HTTP, event)

↓

Function executes

↓

Check logs and output

↓

Fix issues or confirm success

This flow shows how you write, deploy, trigger, and test a cloud function on GCP step-by-step.

Execution Sample

GCP

gcloud functions deploy helloWorld --runtime python312 --trigger-http --allow-unauthenticated

# Then test with:
curl https://REGION-PROJECT.cloudfunctions.net/helloWorld

Deploy a simple HTTP-triggered Python function and test it by sending an HTTP request.

Process Table

Step	Action	Input/Command	Result/Output
1	Write function code	def helloWorld(request): return 'Hello, World!'	Function code ready
2	Package and prepare	N/A	Code and dependencies ready for deployment
3	Deploy function	gcloud functions deploy helloWorld --runtime python312 --trigger-http --allow-unauthenticated	Function deployed, URL provided
4	Trigger function	curl https://REGION-PROJECT.cloudfunctions.net/helloWorld	HTTP 200 OK, response: 'Hello, World!'
5	Check logs	gcloud functions logs read helloWorld	Logs show function executed successfully
6	Fix or confirm	N/A	If errors, update code and redeploy; else confirm success

💡 Function tested successfully or redeployed after fixes

Status Tracker

Variable	Start	After Deploy	After Trigger	After Logs Check	Final
function_code	empty	helloWorld function code	helloWorld function code	helloWorld function code	helloWorld function code
deployment_status	not deployed	deployed	deployed	deployed	deployed or redeployed
trigger_response	none	none	'Hello, World!'	'Hello, World!'	'Hello, World!' or error
logs	empty	empty	execution logs	execution logs	logs reviewed

Key Moments - 3 Insights

Why do we need to redeploy the function after fixing code?

Because the deployed function runs the old code until you deploy the new version, as shown in step 6 of the execution_table.

What does the trigger step do in testing?

It sends a request to the deployed function URL to run the function and get the output, as shown in step 4.

Why check logs after triggering the function?

Logs show if the function ran correctly or had errors, helping to debug, as shown in step 5.

Visual Quiz - 3 Questions

Look at the execution_table, what is the output after triggering the function at step 4?

A Deployment URL

B Error message

C 'Hello, World!'

D Empty response

💡 Hint

Check the 'Result/Output' column at step 4 in the execution_table.

At which step do you check if the function executed successfully by reading logs?

A Step 5

B Step 2

C Step 3

D Step 6

💡 Hint

Look for the step mentioning 'Check logs' in the execution_table.

If the function code changes, what must you do next according to the flow?

A Check logs only

B Redeploy the function

C Trigger function again without redeploying

D Delete the function

💡 Hint

Refer to step 6 in the execution_table and key_moments about redeployment.

Concept Snapshot

Function Deployment & Testing on GCP:
1. Write your function code.
2. Deploy using gcloud with runtime and trigger.
3. Trigger function via HTTP or event.
4. Check output and logs.
5. Fix code and redeploy if needed.
Repeat testing until success.

Full Transcript

This visual execution shows how to deploy and test a cloud function on Google Cloud Platform. First, you write the function code. Then you deploy it using the gcloud command specifying runtime and trigger type. After deployment, you trigger the function by sending an HTTP request. The function runs and returns output. You check logs to confirm success or find errors. If errors exist, you fix the code and redeploy. This cycle repeats until the function works correctly.