CI/CD Pipeline Dual Helm Github Repo With Similar Canary Deployment

#webdev #node

Continuous Integration/Continuous Delivery VM Instance Pipeline:

$ gcloud config list project
[core]
GCP 2nd Gen Cloud Function Inflated With One Pub/Sub CLI Run For Squeezed Cloud Shell

gcloud pubsub(-Module 1) subscriptions create --topic myTopic mySubscription

        1.Inflated Pub/Sub index.js - 

              fun sleep(){
                      Pub/Sub Module 1.()

                                    - Module 2.() -Function 2(Here,Let us now identify if similar Cloud Function can be run in ingress way for another docker container enabled randomly to a subsequent Pub/Sub object) 

                       }

Java 11 Open JDK CLI: public class PipelineOptions implements Serializable
public String Module 2(){-Now let us redirect for one atomic Cloud Function to test its Dataflow API for another Similar Docker Container for a browser
void aq()
}
{
PipelineOptions xd = new PipelineOptions(new FileInputStream());
xd.Module 2() Function 2;
String xd = "";

--Subsequent Module Function's Cloud Storage Bucket

    gsutil ls gs://Storage_Bucket/().txt
                              1.CI/CD Pipeline API Analytics In Ingress Mode For Its Function In Storage Bucket 1

}

Conclusion:

Whenever We run GCP Kubernetes pod for one Storage Bucket,FileInputStream class are managed for its Java 11/Kotlin CLI for one ingress Dataflow Docker Container

How to reduce TTFB

In the past few years in the web dev world, we’ve seen a significant push towards rendering our websites on the server. Doing so is better for SEO and performs better on low-powered devices, but one thing we had to sacrifice is TTFB.

In this article, we’ll see how we can identify what makes our TTFB high so we can fix it.