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  1. Stackups
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  3. Chalice vs Serverless

Chalice vs Serverless

OverviewDecisionsComparisonAlternatives

Overview

Serverless
Serverless
Stacks1.3K
Followers1.2K
Votes28
GitHub Stars46.9K
Forks5.7K
Chalice
Chalice
Stacks46
Followers107
Votes0

Chalice vs Serverless: What are the differences?

Introduction

Chalice and Serverless are both frameworks that enable developers to build and deploy serverless applications easily. They have some key differences that make them distinct from each other. Below are six key differences between Chalice and Serverless:

  1. Main Programming Language Support: Chalice is primarily designed for Python developers, as it uses Python as its main programming language. On the other hand, Serverless supports multiple programming languages like JavaScript, Python, Ruby, Java, C#, and more.

  2. Deployment and Management: Chalice simplifies the deployment process by leveraging AWS CloudFormation. It automatically provisions and manages the necessary AWS resources for the application. Serverless, on the other hand, allows deployment to multiple cloud providers and also provides additional features like plugin architecture for easy integration with different services.

  3. Developer Experience: Chalice is focused on providing a minimalistic and easy-to-use experience for Python developers. It provides a built-in local development server, automatic IAM role creation, and seamless integration with AWS services. Serverless has a more extensive ecosystem and provides a rich set of plugins and integrations, making it suitable for more complex use cases.

  4. Architecture and Framework: Chalice is designed to be a lightweight framework, aimed at building simpler serverless applications with less configuration. It follows a straightforward AWS Lambda-based architecture and provides abstractions for common serverless patterns. Serverless is a comprehensive framework that enables developers to build complex applications by offering a higher level of abstraction. It supports various providers, not just AWS Lambda, and includes features like event handling, resource provisioning, and infrastructure management.

  5. Vendor Lock-In: Chalice is tightly integrated with AWS and is focused on building serverless applications specifically on AWS Lambda. This can lead to vendor lock-in, as it may be challenging to migrate to a different cloud provider. Serverless, on the other hand, offers multi-cloud support and allows developers to write applications that can be deployed on different cloud providers. It provides a more portable and vendor-agnostic solution.

  6. Community and Support: Chalice is an AWS-supported project and benefits from the extensive AWS developer community and resources. It has an active GitHub repository and regular updates. Serverless is an open-source project with a larger community and ecosystem, leading to a broader range of plugins, integrations, and community support.

In summary, Chalice is a lightweight and Python-focused framework tailored for simpler serverless applications, tightly integrated with AWS Lambda. Serverless, on the other hand, is a comprehensive framework supporting multiple programming languages, multiple cloud providers, and offering a higher level of abstraction for building complex serverless applications.

Advice on Serverless, Chalice

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS 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
Serverless
Chalice
Chalice

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.

The python serverless microframework for AWS allows you to quickly create and deploy applications that use Amazon API Gateway and AWS Lambda.

Statistics
GitHub Stars
46.9K
GitHub Stars
-
GitHub Forks
5.7K
GitHub Forks
-
Stacks
1.3K
Stacks
46
Followers
1.2K
Followers
107
Votes
28
Votes
0
Pros & Cons
Pros
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    Auto scale
  • 1
    Openwhisk
No community feedback yet
Integrations
Azure Functions
Azure Functions
AWS Lambda
AWS Lambda
Amazon API Gateway
Amazon API Gateway
Amazon API Gateway
Amazon API Gateway
AWS Lambda
AWS Lambda

What are some alternatives to Serverless, Chalice?

AWS Lambda

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

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

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

Google Cloud Functions

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

Knative

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

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

Nuclio

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

Apache OpenWhisk

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.

Cloud Functions for Firebase

Cloud Functions for Firebase

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.

AWS Batch

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.

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