Unveiling Serverless Computing: AWS Lambda and Google Cloud Functions

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Imagine how liberated you’d feel if you ran a business and had the opportunity to outsource administrative tasks, freeing you up to focus on your core services. Well, if you’re exploring the realm of cloud computing, serverless computing does precisely that for developers and businesses. Cloud computing offloads the hassles of infrastructure management to cloud service providers liberating users from the complexities of maintaining or scaling servers

Let’s dive, rather float, into two serverless cloud computing services, AWS Lambda, and GCP Cloud Functions, both of which serve the same purpose but have their own unique differences and similarities as well, which can help you choose one from the other.

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AWS Lambda: Unveiling the 'Serverless' Magic

AWS Lambda is a service provided by Amazon's cloud, known as AWS. This serverless service means you don't have to worry about managing servers or any other hardware to run your code.

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So, how does it work?

Think of AWS Lambda as a super helper which only gets triggered on certain events. One such event can be when someone clicks on your website or adds a new file to your database - now that the trigger has occurred, Lambda jumps in and runs the right piece of your code to deal with it.

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Imagine you have a big box full of different tools. AWS Lambda is like a smart toolbox that works on Amazon's computers (they call these "Linux servers"). You can put almost any kind of tool in it (or in this case, any kind of code for a web service or app), as long as it's a type that Lambda knows how to use.

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A Quick Tour of AWS Lambda Features

Let's look at some key features that make AWS Lambda such a robust choice:
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• Code Signing: AWS has a tool called AWS Signer. You can use it to digitally sign your code, ensuring it's trusted and originates from a reliable source.
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• Automatic Scaling: Depending on the traffic or incoming requests, it automatically scales up or down, making it easy to handle many trigger requests.
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• Lambda Extensions: It’s noteworthy that AWS Lambda seamlessly integrates with other services, allowing for robust security, monitoring, and governance capabilities.
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• Fault Tolerance: To ensure that your code isn’t affected by data center issues, AWS Lambda maintains high tolerance by distributing compute capacity across multiple Availability Zones.
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• Automated Administration: AWS Lambda takes care of everything from security monitoring and patches to code deployment and administration.
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Google Cloud Functions: The Google Approach to Serverless

Google's answer to serverless computing is Google Cloud Functions. Similar to AWS Lambda, it allows you to focus on writing code while Google takes care of the server management.
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Breaking Down Google Cloud Functions Features

Here are some standout features of Google Cloud Functions:
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• No Server Management: The GCP runs and scales your code, so you don’t have to worry about it and shift your focus on more important to-do tasks with developing your applications.
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• End to End Development and Diagnosable: You can leverage Cloud Debugger and Cloud Trace to diagnose and observe your code deployment.
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• Extendable Platform: Google Cloud Functions lets you utilize third-party services as building blocks, enabling you to construct complex workflows and build applications faster.
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On the upside, Google Cloud Functions provide automatic and flexible scaling, managed dependencies, and real-time processing. On the downside, there are fewer integrations, reduced network performance, and it only supports JavaScript, Python, or Go programming languages.
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Comparing AWS Lambda and Google Cloud Functions: The Similarities and Differences

Both AWS Lambda and Google Cloud Functions offer serverless computing services, reducing the need to manage and maintain servers. They also provide automatic scaling based on the incoming requests. However, their offerings differ in several ways.
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The Similarities
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• Serverless computing platforms: Both provide you with platforms where you can run your code without worrying about server management.
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• Event-driven: Both systems are designed to trigger your code based on specific events.
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• Automatic scaling: Both AWS Lambda and Google Cloud Functions will automatically scale to handle the volume of incoming requests.
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The Differences

Pricing

Pricing for both platforms depends on usage. AWS Lambda charges $0.20 per 1 million requests, and its computing costs are comparatively lower than Google Cloud Functions, especially when your requests exceed 2 million.
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Supported Programming Languages

The notable difference with AWS Lambda is that Cloud Functions lacks support for PowerShell. Azure, on its self, lacks support for Go. That’s expected, as Go was developed by Google.
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Number of Functions

AWS Lambda allows unlimited functions per project, whereas Google Cloud Functions limits you to 1,000 functions per project.
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Event Sources

The services differ in their sources of events. AWS Lambda events can originate from a wide variety of services like SQS, SNS, SES, S3, Kafka, CloudWatch, DynamoDB, HTTP, or Kinesis. On the other hand, Google Cloud Functions' events come from Firebase, Cloud Storage, HTTP, or Cloud Pub/Sub.
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Persistent Storage

AWS Lambda has a limit of 75 GB storage for functions, while Google Cloud Functions lets you control your persistent storage via Firebase or Cloud Storage.
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Execution Time

AWS Lambda allows an execution time of 15 minutes per function, while Google Cloud Functions only allows 9 minutes.
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What Factors Determine the Choice Between These Platforms?

Choosing between AWS Lambda and Google Cloud Functions depends on several factors:
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• Cost: Which platform fits your budget and expected workload?
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• Supported languages: Which platform supports the programming languages your team is proficient in?
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• Number of functions: Do you need more than 1,000 functions per project?
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• Event sources: Which platform's event sources align with your expected event triggers?
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• Persistent Storage: Do you need more than 75 GB of storage for your functions?
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• Execution Time: Do you need more than 540 seconds of execution time per function?
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The decision you make in selecting which serverless cloud platform you want to utilize depends quite a lot on the kind of requirements you have for your platform and the kind of expertise available you have for the platforms. There are several factors you should keep in mind to ensure that the selection you make is the most cost-effective and computing efficient. This is where Data Pilot's expert consultation comes in handy prescribing you with the right tools apt for your particular business needs.

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Regardless of which platform you select, you’ll be able to develop apps faster and at a reduced cost, which is always good news!

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Written by: Muhammad Irfan Umar & Shaafay Zia