Chalice vs Google Cloud Run

Overview

Chalice

Stacks46

Followers107

Votes0

Google Cloud Run

Stacks291

Followers243

Votes62

Chalice vs Google Cloud Run: What are the differences?

In the bustling world of serverless computing, developers often need to choose between multiple options. Two popular choices are AWS Chalice and Google Cloud Run. Below are the key differences between Chalice and Google Cloud Run:

Deployment Environment: Chalice is designed specifically for AWS Lambda, meaning it can only be deployed on AWS. In contrast, Google Cloud Run is a container-based service that allows you to run containers on Google Cloud Platform or even on-premises. This difference in deployment flexibility can be a crucial factor in choosing between the two services.
Automated Scaling: Google Cloud Run offers automated scaling of containers based on incoming requests, ensuring that your application can handle sudden spikes in traffic without manual intervention. While Chalice can also scale automatically to some extent based on Lambda's scaling capabilities, Google Cloud Run's fine-grained control over container scaling sets it apart in certain scenarios.
Cold Start Performance: AWS Lambda, which Chalice is based upon, is known to have cold start performance issues where the first request to a new container can have a higher latency. Google Cloud Run, on the other hand, offers faster cold start times due to its container-based architecture. This can be a critical factor for latency-sensitive applications.
Pricing Structure: Chalice pricing is intertwined with AWS Lambda pricing, which is based on the number of requests and duration of executions. On the other hand, Google Cloud Run pricing is based on the number of vCPU-seconds and GB-seconds consumed by the container, offering a different pricing model that may be more suitable for certain workloads.
Vendor Lock-in: Using Chalice ties you to the AWS ecosystem, which may be advantageous if you are already heavily invested in AWS services. Google Cloud Run, being more vendor-agnostic, can offer easier migration options if you decide to switch cloud providers in the future. Consider this factor carefully while choosing between the two services.
Ecosystem Integration: Chalice seamlessly integrates with other AWS services such as API Gateway, DynamoDB, and S3, making it a preferred choice for AWS-centric applications. Google Cloud Run offers integrations with Google Cloud services, allowing you to leverage the broader Google Cloud ecosystem. Consider the ecosystem compatibility of each service based on your existing infrastructure and requirements.

In Summary, evaluating the deployment environment, scaling capabilities, cold start performance, pricing structure, vendor lock-in, and ecosystem integration can help you determine whether Chalice or Google Cloud Run is the right choice for your serverless application.

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CLI (Node.js)

Manual

Advice on Chalice, Google Cloud Run

Clifford

Software Engineer at Bidvest Advisory Services

Mar 28, 2020

Decided

Run cloud service containers instead of cloud-native services

Running containers means that your microservices are not "cooked" into a cloud provider's architecture.
Moving from one cloud to the next means that you simply spin up new instances of your containers in the new cloud using that cloud's container service.
Start redirecting your traffic to the new resources.
Turn off the containers in the cloud you migrated from.

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Comments

Detailed Comparison

Chalice	Google Cloud Run
The python serverless microframework for AWS allows you to quickly create and deploy applications that use Amazon API Gateway and AWS Lambda.	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.
-	Simple developer experience; Fast autoscaling; Managed; Any language, any library, any binary; Leverage container workflows and standards; Redundancy; Integrated logging and monitoring; Built on Knative; Custom domains
Statistics
Stacks 46	Stacks 291
Followers 107	Followers 243
Votes 0	Votes 62
Pros & Cons
No community feedback yet	Pros 11 HTTPS endpoints 10 Pay per use 10 Fully managed 7 Concurrency: multiple requests sent to each container 7 Serverless
Integrations
Amazon API Gateway AWS Lambda	Google Kubernetes Engine Google Cloud Build Docker Knative

What are some alternatives to Chalice, Google Cloud Run?

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.

Serverless

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.

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.

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

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.

Related Comparisons

Chalice vs Google Cloud Run: What are the differences?

Deployment Environment: Chalice is designed specifically for AWS Lambda, meaning it can only be deployed on AWS. In contrast, Google Cloud Run is a container-based service that allows you to run containers on Google Cloud Platform or even on-premises. This difference in deployment flexibility can be a crucial factor in choosing between the two services.
Automated Scaling: Google Cloud Run offers automated scaling of containers based on incoming requests, ensuring that your application can handle sudden spikes in traffic without manual intervention. While Chalice can also scale automatically to some extent based on Lambda's scaling capabilities, Google Cloud Run's fine-grained control over container scaling sets it apart in certain scenarios.
Cold Start Performance: AWS Lambda, which Chalice is based upon, is known to have cold start performance issues where the first request to a new container can have a higher latency. Google Cloud Run, on the other hand, offers faster cold start times due to its container-based architecture. This can be a critical factor for latency-sensitive applications.
Pricing Structure: Chalice pricing is intertwined with AWS Lambda pricing, which is based on the number of requests and duration of executions. On the other hand, Google Cloud Run pricing is based on the number of vCPU-seconds and GB-seconds consumed by the container, offering a different pricing model that may be more suitable for certain workloads.
Vendor Lock-in: Using Chalice ties you to the AWS ecosystem, which may be advantageous if you are already heavily invested in AWS services. Google Cloud Run, being more vendor-agnostic, can offer easier migration options if you decide to switch cloud providers in the future. Consider this factor carefully while choosing between the two services.
Ecosystem Integration: Chalice seamlessly integrates with other AWS services such as API Gateway, DynamoDB, and S3, making it a preferred choice for AWS-centric applications. Google Cloud Run offers integrations with Google Cloud services, allowing you to leverage the broader Google Cloud ecosystem. Consider the ecosystem compatibility of each service based on your existing infrastructure and requirements.

Chalice vs Google Cloud Run

Overview