Google Cloud Functions vs. AWS Lambda: The Fight for Serverless Cloud Domination

Serverless computing: What is it and why is it important?

A quick background

The general concept of serverless computing was introduced to the market by Amazon Web Services (AWS) around 2014 with the release of AWS Lambda. As we know, cloud computing has made it possible for users to manage virtual computers and services, but customers still have to be proficient with provisioning and managing compute resources. 

AWS decided to take another step in making cloud computing easier and more accessible by managing the underlying compute layer (or abstracting the infrastructure layer as you might hear it said). In the case of AWS, Lambda runs a code function without requiring you to provision the virtual machine and the operating system that runs that code. 

In this article, we’ll cover the basic functions of serverless computing. To deep-dive into this topic and learn how to build, deploy, and manage the Serverless framework, check out Cloud Academy’s Serverless Training Library. With Learning Paths, Courses, Quizzes, Exams, and Hands-on Labs, you’ll gain the technical knowledge and practical experience that you need to integrate serverless architecture into your cloud IT environment.

Google Cloud Functions vs. AWS Lambda

Why is serverless computing important?

Let’s clear something up first: There is still a server involved in the serverless model, but the cloud provider manages that resource, not you, so serverless computing can possibly be better described as Functions-as-a-Service. Serverless computing is a bit like a car rental service. You just want a vehicle to get you to your destination, whether that is just across town or across the country. It is expected you will drive carefully when using the vehicle, and you will report any damage. But you are not expected to pay for the car to be built or delivered to the pickup facility first before you use it, and you are not expected to contribute to the cost of buying or preparing the car. You only pay for the time that we use the service. 

The second thing to bear in mind with serverless computing — and this is the main benefit — is the effect of all the managing that the cloud provider does for you, namely, you have more time to work on developing and delivering the application! 

To summarize, you get these advantages from serverless computing:

  • Less worry — you don’t have to provision or manage the server
  • Scalability — can handle any workloads so your work remains viable
  • Cost — costs can stay under control as you cannot overprovision

General info on AWS Lambda and Google Cloud Functions

Amazon was first to market with serverless functions through their Lambda offering in 2014, and as such has been at the forefront of development. Google Cloud Functions was launched to beta in 2017 and to general availability in 2018. Google’s offering was about four years behind but has managed to catch up in many ways.

Lambda can be used in conjunction with other like services on AWS such as: 

  • Serverless Application Model (SAM) — an open-source framework for building serverless applications
  • Serverless Application Repository — a managed repository for serverless applications
  • Cloud9 — an integrated development environment (IDE) for writing, running, and debugging code

Google is part of a larger family of serverless offerings which include:

  • Cloud Functions — serverless code
  • App Engine — serverless application development platform
  • Cloud Run —  stateless containers

It’s good to remember that in general, both Lambda and Cloud Functions have been designed to play nicely with tons of other services, as long as they’re in the same provider ecosystem.

Practical Applications of Google Cloud Functions and AWS Lambda

Here are a couple of real-world examples of serverless computing, whether they’re implemented on Google Cloud Functions or Amazon Lambda:

  • Realtime stream processing — gather data without setting up infrastructure or logging. This can be event-driven so that it the functions work whether you have a few requests per day or thousands per second.
  • Connecting to third party applications/hardware — you can use serverless functions as lightweight integrations to other applications automate certain tasks within your cloud environment.

You can get more detailed and concrete insight and (importantly) hands-on practice by testing out Cloud Academy’s Hands-on Labs for Google Cloud Functions and AWS Lambda.

Hands-on Lab for Google Cloud Functions Events

In the Cloud Functions Hands-on Lab, you can:

  • Learn basic tenets of serverless architecture
  • Create functions from the GCP console
  • Test your skills against a subject matter expert’s real-world tasks

You can also try out our Intro to AWS Lambda Hands-on Lab guides you through building functions with Node.js. 

Hands-on Lab on Intro to Lambda

Google Cloud Functions and AWS Lambda Features

Functionality AWS Lambda Google Cloud Functions
Scalability & availability Automatic scaling (transparent) Automatic scaling
Max. # of functions Unlimited functions 1000 functions per project
Concurrent executions 1000 parallel executions per account per region  1000 parallel executions (per function, for background functions)
Max. execution time 900 seconds (15 minutes) 540 seconds (9 minutes)
Supported Languages Java, Go, PowerShell, Node.js, C#, Python, and Ruby code, and a Runtime API which allows you to use any additional programming languages to author your functions Node.js, Python, Go
Deployments .zip or .jar file consisting of your code and any dependencies ZIP upload, Cloud Storage, or Cloud Source Repositories
Versioning Versions and aliases Cloud Source branch/tag
Event-driven Event Sources (S3, SNS, SES, DynamoDB, Kinesis, CloudWatch) Cloud Pub/Sub or Cloud Storage Object Change Notifications
HTTP(S) invocation API Gateway HTTP trigger
Logging CloudWatch Logs Stackdriver Logging
Monitoring CloudWatch and X-Ray Stackdriver Monitoring
In-browser code editor Only if you don’t have dependencies Only with Cloud Source Repositories
Granular IAM IAM roles IAM roles
Pricing 1M requests for free, then $0.20/1M requests, plus $0.00001667/GB-sec 2M requests for free, then $0.40/1M invocations, plus $0.0000025/GB-sec

Conclusion

Serverless functions are a great way to leverage the elasticity of cloud deployments. Make sure to consider the big picture in your environment, such as your medium- to long-term plans and how you want to maintain code that you create for serverless architecture. 

You can get further detailed guidance on serverless architecture by checking out our huge catalog of Learning Paths, Courses, Quizzes, Exams, and Hands-on Labs.

Joe Nemer

Written by

Joe Nemer

Joe is a Technical Researcher at Cloud Academy and works to help readers connect concepts in ways they haven't thought of before.


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