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  5. AWS Lambda vs Kestrel

AWS Lambda vs Kestrel

OverviewDecisionsComparisonAlternatives

Overview

Kestrel
Kestrel
Stacks37
Followers58
Votes0
AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432

AWS Lambda vs Kestrel: What are the differences?

Introduction:

AWS Lambda and Kestrel are two different technologies used in web development. AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS), while Kestrel is an open-source cross-platform web server used in ASP.NET Core applications. Both serve different purposes and have specific features that set them apart.

1. Scalability: AWS Lambda is highly scalable, allowing automatic scaling based on the incoming request volume. It is designed to handle a large number of concurrent requests efficiently, making it suitable for applications with fluctuating workloads. On the other hand, Kestrel can also scale to handle increased traffic, but it requires manual configuration and additional infrastructure to ensure optimal performance.

2. Pricing Model: AWS Lambda follows a pay-per-use pricing model, where you only pay for the actual requests processed and the compute time used. It offers a free tier for limited usage. In contrast, Kestrel is an open-source web server that does not have any associated costs, as it is included with ASP.NET Core framework.

3. Execution Environment: AWS Lambda executes functions in a managed environment, abstracting away the underlying infrastructure. It supports multiple programming languages and automatically takes care of resource allocation and scaling. On the other hand, Kestrel runs within the application process and provides a web server functionality specifically for ASP.NET Core applications.

4. Flexibility & Language Support: AWS Lambda supports a wide range of programming languages, including Node.js, Python, Java, C#, and more. It allows developers to choose the most suitable language for their application logic. In contrast, Kestrel is primarily used with ASP.NET Core applications, limiting the language choices to .NET languages such as C#.

5. Deployment and Management: AWS Lambda provides a fully managed service, handling deployment, runtime environment, scalability, and monitoring. It integrates well with other AWS services and offers development tools for efficient management. On the other hand, Kestrel requires manual deployment and management, although it can be integrated with various deployment tools and platforms through the ASP.NET Core ecosystem.

6. Application Purpose: AWS Lambda is commonly used for serverless architectures, event-driven applications, and microservices. It excels in scenarios where quick scalability, cost efficiency, and low maintenance are crucial. In contrast, Kestrel is typically used as the web server component for ASP.NET Core applications, providing the foundation for hosting and serving web content.

In summary, AWS Lambda and Kestrel have significant differences in terms of scalability, pricing model, execution environment, language support, deployment, and application purpose. While Lambda is a fully managed serverless computing service with a scalable pay-per-use model, Kestrel is an open-source web server specifically designed for ASP.NET Core applications.

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Advice on Kestrel, AWS Lambda

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

Kestrel
Kestrel
AWS Lambda
AWS Lambda

Kestrel is based on Blaine Cook's "starling" simple, distributed message queue, with added features and bulletproofing, as well as the scalability offered by actors and the JVM.

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.

Written by Robey Pointer;Starling clone written in Scala (a port of Starling from Ruby to Scala);Queues are stored in memory, but logged on disk
Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
Statistics
Stacks
37
Stacks
26.0K
Followers
58
Followers
18.8K
Votes
0
Votes
432
Pros & Cons
No community feedback yet
Pros
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
Cons
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort

What are some alternatives to Kestrel, AWS Lambda?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

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.

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