Google Cloud, as any cloud provider, needs to expand and open new regions (view the history on Wikipedia). Today 28 regions are up and running, any 6 are coming.

New datacenter means new hardware installation and configuration. Then, the hardware continues to live for a while up to its replacement…

In cloud environments, it’s common to create and destroy resources as we need them. It’s also common to strongly separate the resources for security or confidentiality reasons; or simply to limit the blast radius in case of incidents. …

Cloud Run has redefined the serverless paradigm a few years ago. Cloud Run has also made a promise: portability on any Kubernetes cluster with Knative installed on top of them. I demonstrated this portability which is great!

Knative and Cloud Run implement the same APIs and the same principle: You…

Google is a large company with a large number of applications that you can reach by APIs. To leverage and duplicate the power of each of these products, you can plug them together and create something bigger! …

Function as a Service, or FaaS, has been a cornerstone in app development. Popularized by AWS Lambda service, all the major Cloud Providers offer their version, with different features. And they also extend this principle to containers, with Cloud Run on Google Cloud for example.

On Google Cloud, Cloud Functions…

The cloud cost is one of the most scary aspect: you pay for what you use! To prevent any overcost, one of best practices is to estimate roughly the cost of a project and to set a budget alert on it.

On Google Cloud, you can achieve that on the…

The secrets are the ultimate piece to protect: password, API Keys, private keys, root certificates,… There are several types of secrets but all needs to be kept safe and private. On Google Cloud, Secret Manager service helps to achieve this by keeping the secrets encrypted and protected by IAM.

IAM secret protection


The cloud has many benefits and one of them is the innovation speed with the motto “Fail fast, iterate faster”. Indeed, the cloud providers propose tons of services to easily test and experiment, when the same would be expensive, or impossible, on premise environment.

  • Create a cluster with Hadoop or…

I tried in Node (and I'm bad in Node) and I can propose you this piece of working code

const {WorkflowsClient} = require('@google-cloud/workflows');
const client = new WorkflowsClient();
const [workflows] = await client.listWorkflows({
parent: client.locationPath("<PROJECT_ID>", "us-central1"),
for (const workflow of workflows) {`name: ${}`);
const {ExecutionsClient} = require('@google-cloud/workflows');
const execclient = new ExecutionsClient();
const [resp] = await execclient.createExecution({
parent: client.workflowPath("<PROJECT_ID>", "us-central1", "run-long-process"),
execution: {
argument: '{"wait":5}'
});`name: ${}`);

Cloud components are useful and powerful. However, they are all disconnected from the others and when you want to deploy a full pipeline, you need to glue them. You can achieve this with PubSub and Cloud Functions.
However, it quickly becomes a spaghetti design with a lot of topics and…

guillaume blaquiere

GDE Google Cloud Platform, scrum master, speaker, writer and polyglot developer, Google Cloud platform 3x certified, serverless addict and Go fan.

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