AWS - 06 Lambda & API Gateway & Step Functions

In the sixth post of the AWS series, we’re going to talk about 3 serverless-related services:

Lambda

Stage variables are name-value pairs that you can define as configuration attributes associated with a deployment stage of an API.

They act like environment variables and can be used in your API setup and mapping templates.

Active tracing with X-Ray is only available in Lambda

Components

Event source publishes events, triggers Lambda function. And the Lambda Function is the custom code to process events
Event source mapping
- Maps an event source to a Lambda function
- It enables automatic invocation of your Lambda function when events occur
Runtimes
- Lambda runtimes allow functions in different languages to run in the same base execution environment.
- The runtime sits in-between the Lambda service and your function code, relaying invocation events, context information, and responses between the two
Layer
- Lambda layers are a distribution mechanism for libraries, custom runtimes, and other function dependencies
- Use layers to manage your function’s dependencies independently and keep your deployment package small
Downstream resource
- AWS service that your Lambda function calls once it is triggered
Log stream
- While Lambda automatically monitors your function invocations and reports metrics to CloudWatch, you can annotate your function code with custom logging statements that allow you to analyze the execution flow and performance of your Lambda function

Difference

Environment vars: always encrypt at rest, can be encrypted in transit
Versions & aliases: Secondary resources, manage function deployment & invocation

Lambda@Edge

Run Lambda functions to customize content that CloudFront delivers, executing the functions in AWS locations closer to the viewer
The functions run in response to CloudFront events, without provisioning or managing servers
Automate with CodeDeploy & CodePipeline
Lambda will automatically track the behavior of your Lambda function invocations, and provide feedback that you can monitor. In addition, it provides metrics that allows you to analyze the full function invocation spectrum, including event source integration and whether downstream resources perform as expected

Metrics that Lambda monitor (then reports through CW)

Lambda Layers

DynamoDB Streams

Capture data modification events in DynamoDB tables
Each event is represented by a stream record, captures when new item is CUDed
- Stream records (24h) are organized into groups (shards). Each shard acts as a container for multiple stream records
DynamoDB Stream & Lambda:

Trigger: Code that executes automatically when an event of interest appears in a stream
Use:
- Data replication across regions
- Materialized view of tables
- Data analysis with Kinesis

With triggers, we can build applications that react to data modifications in DynamoDB tables

DynamoDB Stream + Lambda

After you enable DynamoDB Streams on a table, associate the DynamoDB table with a Lambda function. AWS Lambda polls the stream and invokes your Lambda function synchronously when it detects new stream records
Configure the StreamSpecification you want for your DynamoDB Streams
- StreamEnabled
- StreamViewType (what info is written to the stream for this table)

Concepts

API endpoints: Host name API in GW, deployed to a specific region
- Edge optimized
- Regional
- Private
API key: (similar to github blog deploy key)
API stage: a stage in the API lifecycle
Proxy integration
- HTTP proxy: GW passes the entire request and response between the frontend and an HTTP backend
- Lambda proxy: GW sends the entire request as an input to a backend Lambda function

Features

GW can execute Lambda code in your account, start Step Functions state machines, or make calls to Elastic Beanstalk, EC2, or web services outside of AWS with publicly accessible HTTP endpoints
GW helps you manage traffic to your backend by setting throttling rules based on the number of requests per second for each HTTP method in your APIs
Set up a cache with customizable keys and TTL for your API data to avoid hitting your backend services for each request
Run multiple versions of the same API simultaneously with API Lifecycle
All APIs expose HTTPS endpoints only (all encrypted, does not support unencrypted HTTP)

Monitoring

Security

Serverless orchestration: Coordinate multiple AWS services into serverless workflows, so you can build & update apps quickly
SF has built-in fault tolerance and maintains service capacity across multiple AZs in each region
SF scales automatically

Concepts

Step Functions is based on tasks & state machines
- Task: Performs work by using an activity / Lambda function, or by passing parameters to the API actions of other services
- Finite state machine: Express an algorithm as a number of states, their relationships, and their input and output
Define state machines with JSON-based Amazon States Language

Features

State machine execution occurs when a state machine runs and performs its tasks. Each Step Functions state machine can have multiple simultaneous executions
State machine updates in SF are eventually consistent
By default, when a state reports an error, AWS Step Functions causes the execution to fail entirely
Define workflows as state machines: transform complex code into easy to understand statements and diagrams

Common use cases

Ensure that long-running, multiple ETL jobs execute in order and complete successfully, instead of manually orchestrating those jobs or maintaining a separate application
By using SF to handle a few tasks in your codebase, you can approach the transformation of monolithic applications into microservices as a series of small steps
Use SF to easily automate recurring tasks such as patch management, infrastructure selection, and data synchronization; SF will automatically scale, respond to timeouts, and retry failed tasks
Combine multiple Lambda functions into responsive serverless applications and microservices, without having to write code for workflow logic, parallel processes, error handling, timeouts or retries
Orchestrate data and services that run on Amazon EC2 instances, containers, or on-premises servers