What is AWS Lambda?
Who uses AWS Lambda?
AWS Lambda Integrations
Here are some stack decisions, common use cases and reviews by companies and developers who chose AWS Lambda in their tech stack.
We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.
To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS , AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas
To build #Webapps we decided to use Angular 2 with RxJS
#Devops - GitHub , Travis CI , Terraform , Docker , Serverless
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.
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
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
For our Compute services, we decided to use AWS Lambda as it is perfect for quick executions (perfect for a bot), is serverless, and is required by Amazon Lex , which we will use as the framework for our bot. We chose Amazon Lex as it integrates well with other #AWS services and uses the same technology as Alexa . This will give customers the ability to purchase licenses through their Alexa device. We chose Amazon DynamoDB to store customer information as it is a noSQL database, has high performance, and highly available. If we decide to train our own models for license recommendation we will either use Amazon SageMaker or Amazon EC2 with AWS Elastic Load Balancing (ELB) and AWS ASG as they are ideal for model training and inference.
I only know Java and so thinking of building a web application in the following order. I need some help on what alternatives I can choose. Open to replace components, services, or infrastructure.
- Frontend: AngularJS , Bootstrap
- Web Framework: Spring Boot
- Database: Amazon DynamoDB
- Authentication: Auth0
- Deployment: Amazon EC2 Container Service
- Local Testing: Docker
- Marketing: Mailchimp (Separately Export from Auth0)
- Website Domain: GoDaddy
- Routing: Amazon Route 53
PS: Open to exploring options of going completely native ( AWS Lambda , AWS Security but have to learn all)
I am building an API that can be achieved from either.
It's a simple CRUD API.
Is there a well-known public API in production by a known company powered by AWS Lambda ?
I see that everybody uses containers instead.
I planned to do a project in Cloud Firestore , which will store about 100GB of data. Shall I go for Cloud Firestore or traditional AWS RDS MS-SQL SERVER with AWS Lambda ? Please I need your suggestion.
AWS Lambda 's Features
- 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