Introducing Google Cloud Functions: deploying serverless microservices

Google Cloud Functions

Google Cloud Functions are the new guys in town and they come fully packed with great features such as:

  • Serverless Architecture
  • Triggered Based Behaviour
  • Optimized runtimes for Node.js 6,¬†Node.js 8, and Python3
  • Automatic Scaling
  • Pay Only for Function Executions

Continue reading “Introducing Google Cloud Functions: deploying serverless microservices”

Git: Pushing Commits to Multiple Remote Repositories

Image: Git push to multiple repositories

It’s possible in practise to have multiple remote repositories for a single git project. This is a useful technique that every savvy programmer should use when dealing with highly distributed applications.

Let’s say you wish to push to the following two repositories simultaneously: Continue reading “Git: Pushing Commits to Multiple Remote Repositories”

Reading Files from Google Cloud Storage using Python

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It is very common to develop Python applications on Google Cloud Platform that read various files as blobs, which are then used for some further processing. To be able to achieve this ensure you have created a service account and you have downloaded the private key credential file as a JSON.¬† This is used to authenticate all requests sent to GCP resources such as Cloud Storage by the Python application. Continue reading “Reading Files from Google Cloud Storage using Python”

NodePort vs LoadBalancer vs Ingress on Google Kubernetes Engine

It can be quite daunting deciding the type of service that manages external traffic for your Workloads containing the pods running in a cluster on Google Kubernetes Engine (GKE). The best way to come to an optimal decision would first involve having a clear understanding of the different types of services and how they operate in comparison to each other.

There are three methods for dealing with external traffic namely:

  1. Proxy
  2. NodePort
  3. Ingress

By default the Kubernetes engine provisions a ClusterIP service inside your cluster to enable pods to communicate with each other internally, with external access. Continue reading “NodePort vs LoadBalancer vs Ingress on Google Kubernetes Engine”

Using Google Cloud Kubernetes Engine for faster CI/CD operations

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The race for faster CI/CD operations has been the central focus for most software companies that provide devops solutions. Google Cloud Platform currently sits at the top of the list when it comes to seamless continuous integration and delivery.

I am going to talk about how we can deploy a simple Pub/Sub Python application in Google Cloud Kubernetes Engine. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. Now Google has built a solution thats sits on top Kubernetes and it has revolutionized the use of containers for enterprise applications that require a clustered distributed architecture, to ensure that services are highly scalable and robust during future upgrades and rollouts and even during application failures using various self-healing mechanisms. Continue reading “Using Google Cloud Kubernetes Engine for faster CI/CD operations”