Google Cloud Functions vs App Engine vs Cloud Run vs GKE

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Google Cloud Functions vs App Engine vs Cloud Run vs GKE

Last updated on June 2, 2023

Serverless compute platforms like Cloud Functions, App Engine, and Cloud Run lets you build, develop, and deploy applications while simplifying the developer experience by eliminating all infrastructure management.

On the other hand, Google Kubernetes Engine (GKE) runs Certified Kubernetes that helps you facilitate the orchestration of containers via declarative configuration and automation.

Both Google serverless platforms and GKE allows you to scale your application based on your infrastructure requirement. Here’s a table to help you identify when to use these specific services.

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Cloud Functions

App Engine

  • Cloud Functions is a fully managed, serverless platform for creating stand-alone functions that respond to real-time events without the need to manage servers, configure software, update frameworks, and patch operating systems.
  • With Cloud Functions, you write simple, single-purpose functions that are attached to events produced from your cloud infrastructure and services.
  • Cloud Functions can be written using JavaScript, Python 3, Go, or Java runtimes which make both portability and local testing more familiar.
  • Functions are stateless. The execution environment is often initialized from scratch, which is called a cold start and they take significant amounts of time to complete.
  • It is a serverless execution environment that can be used for building and connecting your cloud services. It can serve IoT workloads, ETL, webhooks, Kafka messages, analytics, and event-driven services.
  • Cloud Functions are great for building serverless backends, doing real-time data processing, and creating intelligent apps.
  • App Engine is a fully managed, serverless platform for hosting and developing highly scalable web applications. It lets you focus on your code while App Engine manages infrastructure concerns.
  • You can scale your applications from zero to planet-scale without having to worry and manage infrastructure.
  • You can build your application in Node.js, Java, Ruby, C#, Go, Python, or PHP runtimes. Moreover, you can also bring any library and framework to App Engine by supplying a Docker container.
  • Each Cloud project can only contain a single App Engine application. Once App Engine is created on a project, you are not allowed to change the location of your application.
  • App Engine can seamlessly host different versions of your application, and help you effortlessly create development, test, staging, and production environments.
  • With App Engine, you can route incoming traffic to different versions of your application, A/B test it, and perform incremental feature rollouts by using traffic splitting.
  • App Engine easily integrates with Cloud Monitoring and Cloud Logging to monitor your app’s health and performance. It also works with Cloud Debugger and Error Reporting to help you diagnose and fix bugs quickly.
  • You can run your applications in App Engine using the standard or flexible environments. You are allowed to simultaneously use both environments for your application to take advantage of each environment’s individual benefits.

Cloud Run

Google Kubernetes Engine (GKE)

  • Cloud Run is a managed serverless compute platform that helps you run highly scalable containerized applications that can be invoked via web requests or Pub/Sub events.
  • It is built upon an open standard Knative, that enables the portability of your applications
  • You can pick the programming language of your choice, any operating system libraries, or even bring your own binaries.
  • You can leverage container workflows since Cloud Run integrates well with services in the container ecosystem like Cloud Build, Artifact Registry, Docker.
  • Your container instances run in a secure sandbox environment isolated from other resources.
  • With Cloud Run, you can automatically scale up or down from zero to N depending on traffic. 
  • Cloud Run services are regional and are automatically replicated across multiple zones.
  • Cloud Run provides an out-of-the-box integration with Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting to monitor the health performance of an application.
  • Google Kuberenetes Engine (GKE) is a managed Kubernetes service that facilitates the orchestration of containers via declarative configuration and automation.
  • It integrates with Identity Access Management (IAM) to control access in the cluster with your Google accounts and role permissions you set.
  • GKE runs Certified Kubernetes. This enables portability to other Kubernetes platforms across cloud and on-premises workloads.
  • You can eliminate operational overhead expenses by enabling auto-repair, auto-upgrade, and release channels
  • GKE lets you reserve a CIDR range for your cluster, allowing your cluster IPs to coexist with private network IPs via Google Cloud VPN.
  • With GKE, you can choose clusters designed to the availability, version stability, isolation, and pod traffic requirements of your mission-critical workloads.
  • You can automatically scale your application deployment up and down based on CPU and memory utilization.
  • By default, your cluster nodes are automatically updated with the latest release version of Kubernetes. Kubernetes release updates are quickly made available within GKE.
  • Google Kubernetes Engine integrates well with Cloud Logging and Cloud Monitoring via Cloud Console, making it easy to gain insight into your application.

 

References:
https://cloud.google.com/functions
https://cloud.google.com/functions/docs
https://cloud.google.com/appengine
https://cloud.google.com/appengine/docs
https://cloud.google.com/run
https://cloud.google.com/run/docs
https://cloud.google.com/kubernetes-engine
https://cloud.google.com/kubernetes-engine/docs

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Written by: Jon Bonso

Jon Bonso is the co-founder of Tutorials Dojo, an EdTech startup and an AWS Digital Training Partner that provides high-quality educational materials in the cloud computing space. He graduated from Mapúa Institute of Technology in 2007 with a bachelor's degree in Information Technology. Jon holds 10 AWS Certifications and is also an active AWS Community Builder since 2020.

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