Serverless Overview

Posted by Hardwork đẹp trai on February 05, 2024 · 14 mins read

Serverless Overview

  • Serverless is a new paradigm in which the developers don’t have to manage servers anymore…
  • They just deploy code
  • They just deploy… functions !
  • Initially… Serverless == FaaS (Function as a Service)
  • Serverless was pioneered by AWS Lambda but now also includes anything that’s managed: “databases, messaging, storage, etc.”
  • Serverless does not mean there are no servers… it means you just don’t manage / provision / see them

    Serverless in AWS

    AWS Lambda, DynamoDB, AWS Cognito, AWS API Gateway, Amazon S3, AWS SNS & SQS, AWS Kinesis Data Firehose, Aurora Serverless, Step Functions, Fargate

    Why AWS Lambda

  • EC2
    • Virtual Servers in the Cloud
    • Limited by RAM and CPU
    • Continuously running
    • Scaling means intervention to add / remove servers
  • Amazon Lambda
    • Virtual functions – no servers to manage!
    • Limited by time - short executions
    • Run on-demand
    • Scaling is automated!

      Benefits of AWS Lambda

  • Easy Pricing
    • Pay per request and compute time
    • Free tier of 1,000,000 AWS Lambda requests and 400,000 GBs of compute time
  • Integrated with the whole AWS suite of services
  • Integrated with many programming languages
  • Easy monitoring through AWS CloudWatch
  • Easy to get more resources per functions (up to 10GB of RAM!)
  • Increasing RAM will also improve CPU and network!

    AWS Lambda language support

  • Node.js, python, java, C#, Golang, C# Powershell, Ruby, Custom Runtim API (community supported, example Rust)
  • Lambda Container Image
    • The container image must implement the Lambda Runtime API
    • ECS / Fargate is preferred for running arbitrary Docker images

      AWS Lambda Integrations Main ones

      AWS Lambda Pricing: example

  • You can find overall pricing information here:
  • Pay per calls:
    • First 1,000,000 requests are free
    • $0.20 per 1 million requests thereafter ($0.0000002 per request)
  • Pay per duration: (in increment of 1 ms)
    • 400,000 GB-seconds of compute time per month for FREE
    • == 400,000 seconds if function is 1GB RAM
    • == 3,200,000 seconds if function is 128 MB RAM
    • After that $1.00 for 600,000 GB-seconds
  • It is usually very cheap to run AWS Lambda so it’s very popular

    AWS Lambda Limits to Know - per region

  • Execution:
    • Memory allocation: 128 MB – 10GB (1 MB increments)
    • Maximum execution time: 900 seconds (15 minutes)
    • Environment variables (4 KB)
    • Disk capacity in the “function container” (in /tmp): 512 MB
    • Concurrency executions: 1000 (can be increased)
  • Deployment:
    • Lambda function deployment size (compressed .zip): 50 MB
    • Size of uncompressed deployment (code + dependencies): 250 MB
    • Can use the /tmp directory to load other files at startup
    • Size of environment variables: 4 KB

      Lambda@Edge

  • You have deployed a CDN using CloudFront
  • What if you wanted to run a global AWS Lambda alongside?
  • Or how to implement request filtering before reaching your application?
  • For this, you can use Lambda@Edge:
    • deploy Lambda functions alongside your CloudFront CDN
    • Build more responsive applications
    • You don’t manage servers, Lambda is deployed globally
    • Customize the CDN content
    • Pay only for what you use

      Lambda@Edge

  • You can use Lambda to change CloudFront requests and responses:
    • After CloudFront receives a request from a viewer (viewer request)
    • Before CloudFront forwards the request to the origin (origin request)
    • After CloudFront receives the response from the origin (origin response)
    • Before CloudFront forwards the response to the viewer (viewer response)
    • You can also generate responses to viewers without ever sending the request to the origin

      Lambda@Edge: Global application

      Lambda@Edge: Use Cases

  • Web security and privacy
  • Dynamic Web application at the edge
  • Search Engine Optimization (SEO)
  • Intelligently Route Across Origin and Data Centers
  • Bot Mitigation at the Edge
  • Realtime image transformation
  • A/B Testing
  • User Authentication and Authorization
  • User Prioritization
  • User Tracking andAnalytics

    Amazon DynamoDB

  • Fully managed, highly available with replication across multiple AZs
  • NoSQL database - not a relational database
  • Scales to massive workloads, distributed database
  • Millions of requests per seconds, trillions of row, 100s of TB storage
  • Fast an consistent in performance (low latency on retriieval)
  • Integrated with IAM for security, authorization and administration
  • Enables event driven programming with DynamoDB Streams
  • Low cost and auto-scaling capabilities
  • Standard & Infrequent Access (IA) Table Class

    DynamoDB - Basics

  • DynamoDB is made of Tables
  • Each table has a Primary Key (must be decided at creation time)
  • Each table can have an infinite number of items (= rows)
  • Each item has attributes (can be added over time – can be null)
  • Maximum size of an item is 400KB
  • Data types supported are:
    • Scalar Types – String, Number, Binary, Boolean, Null
    • Document Types – List, Map
    • Set Types – String Set, Number Set, Binary Set

      DynamoDB – Table example

      DynamoDB – Read/Write Capacity Modes

  • Control how you manage your table’s capacity (read/write throughput)
  • Provisioned Mode (default)
    • you specify the number of reads/writes per second
    • You need to plan capacity beforehand
    • Pay for provisioned Read Capacity Units (RCU) & Write Capacity Units (WCU)
    • Possibility to add auto-scaling mode for RCU & WCU
  • On-Demand Mode
    • Read/writes automatically scale up/down with your workloads
    • No capacity planning needed
    • Pay for what you use, more expensive ($$$)
    • Great for unpredictable workloads

      DynamoDB Accelerator (DAX)

  • Fully-managed, highly available, seamless in-memory cache for DynamoDB
  • Help solve read congestion by caching
  • Microseconds latency for cached data
  • Doesn’t require application logic modification (compatible with existing DynamoDB APIs)
  • 5 minutes TTL for cache (default)

    DynamoDB Accelerator (DAX) vs. ElastiCache

    DynamoDB Streams

  • Ordered stream of item-level modifications (create/update/delete) in a table
  • Stream records can be:
    • Sent to Kinesis Data Streams
    • Read by AWS Lambda
    • Read by Kinesis Client Library applications
  • Data Retention for up to 24 hours
  • Use cases:
    • react to changes in real-time (welcome email to users)
    • Analytics
    • Insert into derivative tables
    • Insert into ElasticSearch
    • Implement cross-region replication

      DynamoDB Streams

      DynamoDB Global Tables

  • Make a DynamoDB table accessible with low latency in multiple-regions
  • Active-Active replication
  • Applications can READ and WRITE to the table in any region
  • Must enable DynamoDB Streams as a pre-requisite

    DynamoDB – Time To Live (TTL)

  • Automatically delete items after an expiry timestamp
  • Use cases: reduce stored data by keeping only current items, adhere to regulatory obligations, …

    DynamoDB - Indexes

  • Global Secondary Indexes (GSI) & Local Secondary Indexes (LSI)
  • High level: allow to query on attributes other than the Primary Key
  • With Indexes, we can query by Game ID, Game_TS, Score, Result, etc…

    DynamoDB - Transactions

    Example: Building a Serverless API

    AWS API Gateway

  • AWS Lambda + API Gateway: No infrastructure to manage
  • Support for the WebSocket Protocol
  • Handle API versioning (v1, v2…)
  • Handle different environments (dev, test, prod…)
  • Handle security (Authentication and Authorization)
  • Create API keys, handle request throttling
  • Swagger / Open API import to quickly define APIs
  • Transform and validate requests and responses
  • Generate SDK and API specifications
  • Cache API responses

    API Gateway – Integrations High Level

  • Lambda Function
    • Invoke lambda function
    • Easy way to expose REST API backed by AWS Lambda
  • HTTP
    • Expose HTTP endpoints in the backend
    • Example: internal HTTP API on premise, Application Load Balancer…
    • Why? Add rate limiting, caching, user authentications, API keys, etc…
  • AWS Service
    • Expose any AWS API through the API Gateway?
    • Example: start an AWS Step Function workflow, post a message to SQS
    • Why? Add authentication, deploy publicly, rate control…

      API Gateway - Endpoint Types

  • Edge-Optimized (default): For global clients
    • Requests are routed through the CloudFront Edge locations (improves latency)
    • The API Gateway still lives in only one region
  • Regional:
    • For clients within the same region
    • Could manually combine with CloudFront (more control over the caching strategies and the distribution)
  • Private:
    • Can only be accessed from your VPC using an interface VPC endpoint (ENI)
    • Use a resource policy to define access

      API Gateway – Security

  • IAM Permissions
    • Create an IAM policy authorization and attach to User / Role
    • API Gateway verifies IAM permissions passed by the calling application
    • Good to provide access within your own infrastructure
    • Leverages “Sig v4” capability where IAM credential are in headers
  • Lambda Authorizer (formerly Custom Authorizers)
    • Uses AWS Lambda to validate the token in header being passed
    • Option to cache result of authentication
    • Helps to use OAuth / SAML / 3 rd party type of authentication
    • Lambda must return an IAM policy for the user

  • Cognito User Pools

    • Cognito fully manages user lifecycle
    • API gateway verifes identity automatically from AWS Cognito
    • No custom inplementation required
    • Cognito only helps with authentication, not authorization

      API Gateway – Security – Summary

  • IAM:
    • Great for users / roles already within your AWS account
    • Handle authentication + authorization
    • Leverages Sig v4
  • Custom Authorizer
    • Great for 3 rd party tokens
    • Very flexible in terms of what IAM policy is returned
    • Handle Authentication + Authorization
    • Pay per Lambda invocation
  • Pay per Lambda invocation
    • You manage your own user pool (can be backed by Facebook, Google login etc…)
    • No need to write any custom code
    • Must implement authorization in the backend

      AWS Cognito

  • We want to give our users an identity so that they can interact with our application.
  • Cognito User Pools:
    • Sign in functionality for app users
    • Integrate with API Gateway
  • Cognito Identity Pools(Federate Identity)
    • Provide AWS credentials to users so they can access AWS resources directly
    • Integrate with Cognito User Pools as an identity provider
  • Cognito Sync
    • Synchronize data from device to Cognito.
    • May be deprecated and replaced by AppSync

      AWS Cognito User Pools (CUP)

  • Create a serverless database of user for your mobile apps
  • Simple login: Username (or email) / password combination
  • Possibility to verify emails / phone numbers and add MFA
  • Can enable Federated Identities (Facebook, Google, SAML…)
  • Sends back a JSON Web Tokens (JWT)
  • Can be integrated with API Gateway for authentication

    AWS Cognito – Federated Identity Pools

  • Goal
    • Provide direct access to AWS Resources from the Client Side
  • How:
    • Log in to federated identity provider – or remain anonymous
    • Get temporary AWS credentials back from the Federated Identity Pool
    • These credentials come with a pre-defined IAM policy stating their permissions
  • Example:
    • provide (temporary) access to write to S3 bucket using Facebook Login

      AWS Cognito Sync

  • Deprecate - use AWS AppSync now
    • Store preferences, configuration, state of app
    • Cross device synchronization (any platform – iOS, Android, etc…)
    • Offline capability (synchronization when back online)
  • Requires Federated Identity Pool in Cognito (not User Pool)
    • Store data in datasets (up to 1MB)
    • Up to 20 datasets to synchronise

      AWS SAM - Serverless Application Model

  • SAM = Serverless Application Model
  • Framework for developing and deploying serverless applications
  • All the configuration is YAML code:
    • Lambda Functions
    • DynamoDB tables
    • API Gateway
    • Cognito User Pools
  • SAM can help you to run Lambda, API Gateway, DynamoDB locally
  • SAM can use CodeDeploy to deploy Lambda functions
← Previous Post Next Post →