Infrastructural management and server maintenance can trap IT teams and distract their focus from more critical and complex tasks. Serverless computing eliminates those hurdles by shifting responsibilities for infrastructure management to the cloud provider.
Serverless computing – also known as Function as a Service (FaaS) – is an event-driven model in which functions are code units that execute in response to predefined or on-demand triggers. Serverless functions are the most suitable option to run code, build mobile and web applications, manage containers, and handle other cloud computing tasks.
Public cloud providers provide a variety of serverless tools and services that alleviate cloud users from handling infrastructure management tasks. Let’s evaluate AWS, Google and Microsoft’s big serverless computing offerings and determine which platform best fits your needs.
Developers can use this event-driven cloud computing service to run AWS cloud functions without the need to manage or supply resources, such as servers and storage. With AWS Lambda, AWS handles the infrastructure, and developers write the code. This service supports many languages like Node.js, Python, Java, and C#, etc.
AWS Lambda performs specific, programmatic tasks through Lambda functions in response to events from other Amazon cloud services such as Amazon S3, Amazon Simple Notification Service, and CloudWatch. With AWS Step Functions, Lambda may also be orchestrated into workflows.
Users can use the AWS Lambda dashboard, command-line interface, or software development kit to update and track the Lambda functions. AWS Lambda can be used in the AWS cloud for data processing, web application building, and various other capabilities. Lambda functions are priced according to pay-per-use.
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To run Lambda functions at the edge of AWS’s global delivery network, developers prefer AWS Lambda@Edge. This serverless compute function executes code closer to end-users geographically to reduce latency. Lamdba@Edge takes the IT teams burden of managing and provisioning of infrastructure in multiple locations. Amazon CloudFront generates events that trigger the execution and delivery of location-specific code at Lambda@Edge.
AWS Fargate is a serverless compute engine in AWS Cloud for containers. It operates with Amazon Elastic Container Service and Elastic Kubernetes Service. AWS users can develop and run AWS Kubernetes applications without the need for provisioning and managing pods.
With Fargate, developers can control the parameters and access policies of their containerized applications while Amazon manages the underlying infrastructure. Fargate scales automatically for containers to run in a highly available environment. This service can launch thousands of containers simultaneously. Users may opt for Fargate Spot, a discounted version of the service designed for interruption-tolerant applications.
Google Cloud Functions
Google Cloud Functions is the serverless, event-driven computing service available on the platform. Like AWS Lambda, Google Cloud Functions abstracts the underlying infrastructure management and allows developers to focus on writing code and other tasks. With Google Cloud Functions, small segments of programmatic code perform functions in a cloud environment in response to specific events.
Ressources within or outside Google Cloud Platform (GCP) can trigger this service. Google Cloud Functions connect with other services of GCP along with third party services. Google’s serverless compute tool can trigger log analysis and data backups and executes redundant tasks on data sets, among other tasks. Users pay for the number of functions they use.
Google App Engine
App Engine is a serverless PaaS service from Google where developers can create mobile and web applications. App Engine can scale resources of any size with automatic infrastructure management and server maintenance. This tool provides integrated services, including load balancing, application logging, and health checks. The serverless compute platform also offers capabilities for storing and configuring data.
Users of the App Engine can access the Google Cloud Security Scanner to detect security issues with the application. App Engine comes in standard or flexible environments. The instances run in a sandbox environment in the standard App Engine environment and support a specific set of programming languages. The standard environment is more suitable for those applications that deal with rapid scaling.
The flexible environment for App Engine instances runs your applications within the docker container on Google’s Compute Engine virtual machine. This flexible environment works best with the applications that will receive consistent traffic or might experience fluctuation in traffic and applications that scale gradually. There are fewer restrictions on such type of environment and supports more source code languages than the standard environment, such as Python, Java, Node.js, Go, Ruby, PHP, or .NET.
Google Cloud Run
Google Cloud Run is a serverless compute platform container management application that runs stateless containers on a fully managed environment. It is built on Knative, an open-source set of Kubernetes tools to build serverless apps. It allows portability of workloads and supports all programming languages and open source libraries.
HTTPS requests to trigger Cloud Run services. Cloud Run is used to create portable, container-based mobile, and web applications with automatic scalability. This service works with other container management tools and technologies like CodeBuild, Docker, and Container Registry.
Cloud users can deploy the managed, pay-per-use version of Google Cloud Run that deploys stateless containers on Google Cloud. Or, users may opt for Anthos’ Cloud Run, which runs containers on Google Cloud, on-site, or in VMware environments. Cloud Run for Anthos supports custom machine types and offers additional network capabilities.
Azure Functions is the serverless computing software provided by Microsoft with equivalent functionality to AWS Lambda and Google Cloud. This event-driven serverless compute platform, by managing the infrastructure, simplifies the application development for IT teams. Functions are executed through event triggers from Azure services or third-party sources, such as the Azure Event Hub, HTTPS requests, GitHub, and messaging traffic from Azure Storage services.
Among other capabilities, Azure Functions handles development tasks such as data processing, file maintenance, and data collection from IoT devices. This service also includes other Azure offerings such as Azure Cosmos DB, Azure Mobile Apps, and Azure Service Bus. Users pay for Azure Functions depending on how long a feature runs in a billing period.
Azure App Service:
Azure App Service is yet another Microsoft serverless offering. This service is used by developers to run mobile, web, and Azure API applications in a managed environment. Azure App Service supports Java, .NET, .NET Core, Node.js, Python, PHP, and Ruby. Azure App deploys applications in containers or as code and can run these on Windows or Linux operating systems.
This serverless compute service offers features such as on-demand code, load balancing, and autoscaling, and continuous integration and deployment with Azure DevOps, BitBucket, Docker Hub, GitHub, or Azure Container Registry. Users can customize their Azure App Service model by selecting from one of several pricing plans, which range from Free to Premium.
Azure Kubernetes Service
Microsoft Azure presents serverless container management with Azure Kubernetes Service (AKS). This serverless tool provides clusters orchestrated by Kubernetes, which scale automatically depending on traffic spikes.
With AKS, Microsoft manages overhead management, configuration, and integration with services like Azure Active Directory. For Docker image storage and Azure disks, AKS can be integrated with Azure Container Registry. Azure cloud users can use the AKS management platform, AKS command-line interface, or Azure Resource Manager templates to access the service. Cloud users aren’t charged for AKS-managed Kubernetes clusters. Pricing on the cloud is based on the resources used in containers.