Friday, April 5, 2019

Google Cloud Functions: a (looong overdue) "hello, world!" on GCP

In early 2018, Google Cloud Functions went GA. Some time before that - in March 2018, while it was still in beta - I took some screenshots while taking my first shot at Cloud Functions. But then one thing led to another, and to another, and another, and this blog post was never born.

Now, after a whole year of downright obsoletion, I present to you my "getting started with Google Cloud Functions [beta]" guide.

Surely a lot has changed; beta tag gone, hordes of new features introduced: Python runtime, environment variables, in-built test invocations and logs, and a lot that I haven't even seen yet.

Activate billing on your GCP account

Now, if you rush to the Cloud Functions dashboard, you may notice that you need to enable the Cloud Functions API - unless you have done so already, with your currently active GCP project.

'Cloud Functions' link on the GCP console's left menu

'Cloud Functions API not enabled'

Cloud Functions need a billing enabled GCP project, so that's the first thing we need to do. Google's official guide is fairly easy to follow.

filling in payment details for your billing account

Google promises that we won't be charged during our 1-year, $300 free trial so we're covered here.

Create a cloud function

When done, go ahead to the Cloud Functions dashboard and click Create function.

a fresh Cloud Functions dashboard (back from the beta days)

This will take you to a Create function wizard. The first phase would resemble:

GCP Create Function: configuration phase 1

Here you define most of the basics of your cloud function: name, max memory limit, trigger, and source code.

Later on, you get the chance to define the handler/entrypoint (NodeJS function to invoke when the Cloud Function is hit); and other settings like the function deployment region and timeout (maximum running time per request).

GCP Create Function: name (handler), region and timeout

Trigger options

Triggers can invoke your cloud function in response to external actions: active ones like HTTP requests or passive ones like events from Cloud Storage buckets or Cloud Pub/Sub topics.

In platforms like AWS this may not make much difference: Lambda configures and handles both event types in the same way. But in GCP they are handled quite differently; so different that the cloud function method signature itself is different.

If you try switching between the trigger types, you would see how the sample code under Source code changes:

HTTP functions

Google generates the signature:

 * Responds to any HTTP request that can provide a "message" field in the body.
 * @param {!Object} req Cloud Function request context.
 * @param {!Object} res Cloud Function response context.
exports.helloWorld = (req, res) => {
  // Example input: {"message": "Hello!"}
  if (req.body.message === undefined) {
    // This is an error case, as "message" is required.
    res.status(400).send('No message defined!');
  } else {
    // Everything is okay.
    res.status(200).send('Success: ' + req.body.message);

A HTTP function accepts a request and writes back to a response.

The HTTP(S) endpoint is automatically provisioned by Google, at https://{region}-{project-name}{function-name}. So there is nothing more to configure in terms of triggers.

Event-based functions

Google's signature looks like:

 * Triggered from a message on a Cloud Pub/Sub topic.
 * @param {!Object} event The Cloud Functions event.
 * @param {!Function} The callback function.
exports.subscribe = (event, callback) => {
  // The Cloud Pub/Sub Message object.
  const pubsubMessage =;

  // We're just going to log the message to prove that
  // it worked.
  console.log(Buffer.from(, 'base64').toString());

  // Don't forget to call the callback.

Event-based functions accept an event and convey success/failure (and optionally a result) via a callback.

Here we need to configure an event source (Pub/Sub topic or Storage bucket) to trigger the function.

configuring a Cloud Storage bucket to trigger a function

Good thing is, GCP allows you to pick an existing topic/bucket, or create a new one, right there inside the cloud function wizard page.

defining a new Cloud Storage bucket via the 'Create new bucket' pop-up

defining a new Cloud Pub/Sub topic via the 'Create new topic' pop-up

Picking an existing entity is just as easy:

selecting an existing Cloud Storage bucket

Automatic retry

These non-HTTP functions also have a retry mechanism: you can configure GCP to redeliver an event back to the function automatically, if the function failed to process it during the last time.

Cloud Function retry configuration

This is good for taking care of temporary failures, but it can be dangerous if the error is due to a bug in your code: GCP will keep on retrying the failing event for up to 7 days, draining your quotas and growing your bill.

A function is born

Now we are done with the configurations; click Create.

GCP takes you back to the function dashboard, where the new function will be listed; with a "pending" or "creating" status.

Cloud Functions dashboard, while your new function gets created

It may take a while, but finally you would see the successfully created function in Active status:

Cloud Function created and in 'Active' status

Back in the beta days, I got some sporadic errors when trying to create functions; for no apparent reason. Hopefully nobody is that much unlucky these days.

create function: 'Request failed with unknown error'

It is a good practice to label your functions, so you can find and manage them easily. GCP allows you to do this right from the dashboard.

labelling your Cloud Functions, right from the dashboard

Function actions

Click the three-dots button at the far right end of the function entry, to see what you can do next:

Cloud Function actions

Back in the beta days, there were some hiccups with some of these options (like Copy Function; hopefully they are long gone now!

Copy Function: 'no source code location' error


Test Function gives a nice interface where you can invoke the function with a custom payload, and view the output and execution logs right away. However it still lacks the ability to define and run predefined custom test events, like in AWS or Sigma. Another caveat is that the test invocations also hit the same production function instance (unlike, say, the test environment of Sigma), so they count towards the logs and statistics of your actual function.

'Test Function' tab of the function detailed view

Test result for the standard HTTP function sample


View Logs takes you to the familiar StackDriver Logging page, where you can browse, sort, search stream and do all sorts of things with the logs of your function. It takes a few seconds for the latest logs to appear, as is the case with other platforms as well.

'View Logs' takes you to StackDriver Logging

More function details

You can click the function entry to see more details:

  • General tab shows a nice stats graph, along with basic function configs like runtime, memory etc.

'General' tab of our new function

  • Trigger tab shows the trigger config of the function.

'Triggers' tab with an HTTP trigger config

As of now, GCP doesn't allow you to edit/change the trigger after you have created the function; we sincerely hope this would be relaxed in the future!

a read-only trigger config

  • Source tab has the familiar code viewer (although you cannot directly update and deploy the code from there). It also has a Download zip button for the code archive.

'Source' tab with function code

  • Testing tab we have already seen. It's also pretty neat, for something that went GA just a few months ago.

So, that's what a cloud function looks like.

Or, to be precise, how it used to be - back in the pre- and post-beta days.

I'm sure Google will catch up on the serverless race - with more event sources, languages, monitoring and so forth.

But do we need to wait? Absolutely not.

Cloud Functions are mature enough for most of your routine integrations. One major bummer is that it doesn't yet support timer schedules, but folks are already using workarounds.

Plus, many of the leading serverless development frameworks are already supporting GCP!

So hop in - write your own serverless success story on GCP!

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