Overview

Serverless

Stacks1.3K

Followers1.2K

Votes28

GitHub Stars46.9K

Forks5.7K

Cloud Functions for Firebase

Stacks477

Followers397

Votes6

Cloud Functions for Firebase vs Serverless: What are the differences?

Platform Integration: Cloud Functions for Firebase is tightly integrated with Google Cloud Platform services, such as Firebase, Cloud Firestore, and Cloud Storage, making it easier to build end-to-end serverless applications with these services. On the other hand, Serverless is a platform-agnostic solution that can be used with various cloud providers, offering more flexibility in choosing the underlying infrastructure and services.
Vendor Lock-in: Cloud Functions for Firebase locks users into the Google Cloud Platform ecosystem, making it challenging to switch to a different cloud provider. Serverless, on the other hand, allows developers to build and deploy functions without being tied to a specific cloud provider, reducing the risk of vendor lock-in and promoting portability.
Pricing Model: Cloud Functions for Firebase follows a pay-as-you-go pricing model, where users are charged based on the number of invocations, execution time, and resources consumed. Serverless, on the other hand, offers more pricing flexibility as it supports various pricing models, such as pay-per-use, reserved instances, and spot instances, allowing users to choose the most cost-effective option for their needs.
Scaling: Cloud Functions for Firebase automatically scales functions based on incoming traffic and resource demands, ensuring optimal performance without manual intervention. Serverless also provides auto-scaling capabilities, allowing functions to scale up or down based on workload, but users may need to configure scaling parameters and thresholds to achieve desired performance.
Development Environment: Cloud Functions for Firebase offers a more streamlined development experience with built-in support for Firebase features and tools, such as Firebase CLI, local testing, and deployment integrations. Serverless, on the other hand, provides a more generic development environment, requiring additional setup and configuration to work with specific cloud services and tools, which may require more effort from developers.
Community Support: Cloud Functions for Firebase benefits from a thriving community of Firebase developers and resources, providing abundant tutorials, documentation, and community support for building serverless applications. Serverless, being a more general-purpose solution, has a larger community encompassing developers from various cloud platforms, offering a wide range of resources and support but may lack the depth of Firebase-specific resources.

In Summary, Cloud Functions for Firebase offers tighter integration with Google Cloud services, but may lead to vendor lock-in, while Serverless provides more flexibility in platform choice, pricing models, and scaling options.

Advice on Serverless, Cloud Functions for Firebase

Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceon

Heroku

AWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

Developer Experience trumps everything.
AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

Pure, uncut, self hosted Kubernetes — way too much complexity
Managed Kubernetes in various flavors — still too much complexity
Zeit — Maybe, but no Docker support
Elastic Beanstalk — Maybe, bit old but does the job
Heroku
Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

Developer Experience / DX 🤓
Ops Experience / OX 🐂 (?)
Cost 💵
Lock in 🔐

Read the full post linked below for all details

357k views357k

Comments

Detailed Comparison

Serverless	Cloud Functions for Firebase
Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.	Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.
Statistics
GitHub Stars 46.9K	GitHub Stars -
GitHub Forks 5.7K	GitHub Forks -
Stacks 1.3K	Stacks 477
Followers 1.2K	Followers 397
Votes 28	Votes 6
Pros & Cons
Pros 14 API integration 7 Supports cloud functions for Google, Azure, and IBM 3 Lower cost 1 5. Built-in Redundancy and Availability: 1 3. Simplified Management for developers to focus on cod	Pros 4 Up and running 1 Affordable 1 Multi-region
Integrations
Azure Functions AWS Lambda Amazon API Gateway	Firebase Google Cloud Storage Google Cloud Functions

What are some alternatives to Serverless, Cloud Functions for Firebase?

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Apache OpenWhisk

OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.

AWS Batch

It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.

Fission

Write short-lived functions in any language, and map them to HTTP requests (or other event triggers). Deploy functions instantly with one command. There are no containers to build, and no Docker registries to manage.