Over the past two decades, numerous technologies have revolutionized IT with a singular focus: enabling developers to focus on coding without the burden of managing underlying infrastructure. Among these innovations, GCP Serverless Computing stands out as an ideal choice.
With serverless computing, developers don’t have to get slowed down with managing servers or OS as everything’s taken care of by a cloud provider. A provider handles any routine work, including provisioning, maintaining, and scaling the server infrastructure, hardware, and container management. Developers can write and deploy code to containers tackling business logic without hassle.
Serverless offerings from public cloud providers are billed based on execution time and resource usage, rather than a fixed monthly fee for maintaining physical or virtual machines. Billing starts when execution begins and stops when it ends. This ‘pay-as-you-go’ model ensures that developers incur no costs when a serverless function is idle.
The term ‘serverless’ might suggest the absence of servers, but servers are very much present in the backend. However, these servers are fully managed by the cloud provider. ‘Serverless’ essentially means that developers don’t need to handle server management, allowing them to focus solely on building and deploying applications.
The Serverless framework generally falls into two categories: Backend-as-a-Service (BaaS) and Function-as-a-service (FaaS). The most common serverless computing model used is FaaS. This cloud computing service enables developers to write application code as a set of event-driven functions and run them as containers managed by cloud service providers. Each function is triggered by specific events or HTTP requests, and the cloud provider executes them on a running or new server. This entire execution process is invisible to developers, and hence serverless computing.
Most of the major public cloud providers have FaaS offerings, including AWS with AWS Lambda functions, Microsoft Azure with Microsoft Azure Functions, Google Cloud with Cloud Run, Apache Openwhisk, IBM with IBM Cloud functions.
In recent years, there has been a significant increase in serverless adoption. According to the O’Reilly serverless survey 2019, 40% of organizations have adopted serverless architecture in some form or another. Global multinational companies and startups alike are leveraging serverless computing. The benefits of serverless computing includes:
Google Cloud Platform offers a fully managed GCP serverless compute platform with multiple components to develop and deploy highly scalable serverless applications. GCP serverless computing model automatically scales servers depending on traffic and adopts a pay-as-you-use model.
Cloud Run is a serverless fully-managed platform to develop and deploy highly-scalable containerized applications on GCP. It allows the use of any programming language or operating system libraries. It also allows bringing your own binaries to build websites. Further, Cloud Run charges only for the resources that are used. Cloud Run works well together with other Google Cloud services so that full-featured applications can be built.
Cloud Run also enhances developer experience by providing a simple command-line and user interface to quickly deploy and manage applications and services. It also allows integration with Cloud Build, a turnkey CI/CD solution, and Cloud Code, a set of IDE plugins, for continuous deployment.
Cloud Functions is GCP’s scalable FaaS platform that allows users to run code in the cloud in response to events triggered by Firebase features and HTTPS requests. No need to manage servers or containers. It runs functions across multiple environments (on-premise, local environment, Cloud Run, and Knative-based open serverless runtime environment) and prevents lock-in. Google Cloud Functions can also be used to connect with third-party cloud services to streamline orchestration problems.
This pay-as-you-go platform helps write and run small code snippets on the GCP console or write them locally and deploy them using Google Cloud tooling on the local machine.
GCP also provides service integration products to integrate and orchestrate services and help developers focus on building applications. These products integrate services such that it is inherently asynchronous and loosely coupled. This ensures that the agility of each individual service is preserved and rapid innovation is enabled. They also offer multiple benefits, such as observability, security, scalability, and reliability.
Eventarc: Eventarc makes it easy to connect Cloud Run services with events from a variety of sources (Google Cloud services with Cloud Storage buckets, SaaS, or own code). It requires no infrastructure management and optimizes productivity and costs.
Scheduler: Cloud Scheduler on Google Cloud helps trigger batch processes and automation on a schedule. It is a fully managed enterprise-grade cron job scheduler that allows developers to schedule any job, such as batch and cloud infrastructure operations.
Workflows: Workflows enable developers to combine GCP services and APIs to build applications, ML pipelines, and process automation. It allows calling any service, whether it’s Cloud Functions or third-party APIs.
Tasks: GCP allows offloading asynchronous work with its Cloud Tasks queues. Cloud Tasks is a fully-managed service that enables managing execution, dispatch, and delivery of distributed tasks. Tasks can be executed on App Engine or any HTTP endpoint.
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