4.21 Lambda Concepts

History

At the beginning, AWS provide data center and IaaS. The problem of IaaS is that the code is still running on virtual machines or physical machines, so you still need to worry about the operating systems and the hardware.

Then, Amazon come up with PaaS, i.e. Elastic Beanstalk. You can just upload your code and AWS will take a look at the code and provision the underlying resources, for example, creating a web server for you. However, as a developer, you still need to manage operating systems.

Then, we have Containers, for example, Docker. Containers are isolated and they are lightweight. We still have to deploy them to a server and you still have to worry about keeping your containers running and scaling them into responds to load.

Then, Lambda was released in re-invent 2015. You don't worry about managing data centers, IaaS, PaaS, and Containers, AWS take care of all that for you, and all you have to worry about is your code. Take your code and upload them to Lambda and then you configure an event trigger, and this event will trigger your Lambda function.

What is Lambda?

All these things such as data center, hardware, assembly code/protocols, high level languages, operating systems, application layer/AWS APIs are encapsulated by AWS Lambda.

AWS Lambda is a compute service where you can upload your code and create a Lambda function. AWS Lambda takes care of provisioning and managing the servers that you use to run the code. You don't have to worry about operating systems, patching, scaling, etc. You can use Lambda in the following ways:

• As an event-driven compute service where AWS Lambda runs your code in response to events. These events could be changes to data in an Amazon S3 bucket or an Amazon DynamoDB table.

• As a compute service to run your code in response to HTTP requests using Amazon API Gateway or API calls made using AWS SDKs. This is what we use at ACloudGuru.

Lambda function can trigger another Lambda function and it can also use other AWS services. Lambda can scale out automatically. If multiple users send to HTTP requests concurrently, there will be multiple Lambda functions are invoked (scaled out automatically) and give responses to users, but the code of the Lambda functions are identical, so one set of code but it will respond to multiple requests. This is very different with EC2 instances behind the ELB. The specific number of EC2 instances will always take charge of responding to the requests, no matter how many requests are there, and the code are copied across the EC2 instances. For the automatic scaling out of Lambda function, there is a good news that you get a million free invocations per month. The main thing you need to know in the exam is the different types of Lambda triggers, and what languages and runtime the Lambda supports.

Lambda

• In your AWS console, go to Compute and go to Lambda.

• Create a new Lambda function:

  • Configure Triggers, such as SNS, S3, Kinesis, DynamoDB, Alexa, AWS IOT, CloudFront, CloudWatch, CodeCommit, API Gateway, etc.

  • Configure Function. Lambda support languages/runtime including: Node.js, Java, Python and C#.

  • Review.

• Pricing based on:

  • Number of requests

    • First 1 million requests are free, and $0.2 per 1 million requests thereafter.

  • Duration

    • Duration is calculated from the time your code begins executing until it returns or otherwise terminates, rounded up to the nearest 100ms. The price depends on the amount of memory you allocate to your function. You are charged $ 0.00001667 for every GB-second used. Duration has a threshold, it is 5 minutes. The function cannot get executed over 5 minutes, so you have to break your function into multiple functions, and let one function trigger next one.

• Why Lambda is cool?

  • No servers. No database admin, no network admin, no system admin. You only need to focus on your code.

  • Continuous scaling. Unlike auto scaling of EC2 instances or something others, you don't need to set any Rule, you don't need to wait a couple of minutes, and Lambda will auto scaling instantly.

  • Super cheap.

  • Alexa is using Lambda. When you talk to it, you trigger a lambda function, and this lambda function will respond to you.

Exam Tips

• Lambda scale out, not up, automatically.

• Lambda functions are independent, 1 event = 1 function.

• Lambda is serverless.

• Know what services are serverless, such as S3, API Gateway, Lambda, DynamoDB, etc. EC2 is not, it will need to maintain instances.

• Lambda functions can trigger other lambda functions, 1 event can = x functions if functions trigger other functions.

• Architectures can get extremely complicated, AWS X-ray allows you to debug what is happening.

• Lambda can do things globally, you can use it to back up S3 buckets to other S3 buckets, etc.

• Know your triggers. (i.e. SNS, S3, Kinesis, DynamoDB, Alexa, AWS IOT, CloudFront, CloudWatch, CodeCommit, API Gateway, etc).

• Lambda is duration time, maximum is 5 minutes.

• The available languages/runtime for Lambda.

• Lambda automatically monitors functions on your behalf, reporting metrics through CloudWatch. These metrics are including:

  • total requests

  • latency

  • error rates