Note_Tech
All technological notes.
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AWS - Containers
Docker
Docker- a set of Platform as Service (PaaS) products that use OS-level virtualization to deliver software in packages called containers.
- a software development platform to deploy apps
- Apps are packaged in containers that can be run on any OS
- Apps run the same, regardless of where they’re run
- Any machine
- No compatibility issues
- Predictable behavior
- Less work
- Easier to maintain and deploy
- Works with any language, any OS, any technology
- Scale containers up and down very quickly (seconds)
Podman
VMs vs Containers
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VMs- VMs do not make best use of space.
- Apps are not isolated which could cause config conflicts, security problems or resource hogging.
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Containers- containers allow to run multiple apps which are virtually isolated from each other.
- Launch new containers and configures OS Dependencies per container.
Docker images
Docker imagesare stored in Docker Repositories- Private:
Amazon ECR (Elastic Container Registry)
Container Services On AWS
Elastic Container Service (ECS) - Docker + Instances
Elastic Container Service (ECS)- Launch Docker containers on AWS
- Has integrations with the
Application Load Balancer - You must provision & maintain the infrastructure (the EC2 instances)
- AWS takes care of starting / stopping containers
Fargate - Docker, Serverless
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Fargate- Launch Docker containers on AWS
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Serverless offering
- You do not provision the infrastructure (no EC2 instances to manage) – simpler!
- AWS just runs containers for you based on the CPU / RAM you need
Elastic Container Registry (ECR) - Docker images
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Elastic Container Registry
- Private Docker Registry on AWS
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This is where you store your Docker images so they can be run by ECS or Fargate
Batch - dynamically instance
- Fully managed batch processing at any scale
- Efficiently run 100,000s of computing batch jobs on AWS
- A “batch” job is a job with a start and an end (opposed to continuous)
- Batch will dynamically launch EC2 instances or Spot Instances
- AWS Batch provisions the right amount of compute / memory
- You submit or schedule batch jobs and AWS Batch does the rest!
- Batch jobs are defined as Docker images and run on ECS
- Helpful for cost optimizations and focusing less on the infrastructure
- AWS Batch dynamically provisions the optimal quantity and type of compute resources. 用户无需管理硬件
Batch vs Lambda
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Lambda:
- Time limit
- Limited runtimes
- Limited temporary disk space
- Serverless
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Batch:
- No time limit
- Any runtime as long as it’s packaged as a Docker image
- Rely on EBS / instance store for disk space
- Relies on EC2 (can be managed by AWS)
Kuberenetes
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Kuberenetes- an open-source container orchestration system for automating deployment, scaling, and management of containers.
- commonly called
K8
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The advantage of Kubernetes over Docker is the ability to run containers distributed across multiple VMs.
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A unique component of Kubernetes are Pods.
- A pod is a group of one more containers with shared storage, network resources, and other shared settings.
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Kuberenetes is ideally for micro-service architectures where a company has tems to hundreds of services they need to manage.
Elastic Kubernetes Service (EKS) - Kubernetes
Elastic Kubernetes Service (EKS)- a managed Kubernetes service to run Kubernetes in the AWS cloud and on-premises data centers.
Serverless
- 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.”
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Serverless does not mean there are no servers… it means you just don’t manage / provision / see them
- Serverless
- Amazon S3
- DynamoDB
- Fargate
- Lambda
Lambda - Serverless
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Amazon EC2
- Virtual Servers in the Cloud
- Limited by RAM and CPU
- Continuously running
- Scaling means intervention to add / remove servers
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Amazon Lambda
- Virtual functions – no servers to manage!
- Limited by time - short executions
- Run on-demand
- Scaling is automated!
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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
- Event-Driven: functions get invoked by AWS when needed
- 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!
- Easy Pricing:
-
Lambda Container Image
- The container image must implement the Lambda Runtime API
- ECS / Fargate is preferred for running arbitrary Docker images
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Example: Serverless CRON Job
CloudWatch EventsEventBridge ->AWS Lambda FunctionPerform a task
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Pricing
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Pay per calls:
- First 1,000,000 requests are free
- $0.20 per 1 million requests thereafter ($0.0000002 per request)
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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
-
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It is usually very cheap to run AWS Lambda so it’s very popular
API Gateway - serverless API, with Lambda
- Example:
- building a serverless API
- Fully managed service for developers to easily create, publish, maintain, monitor, and secure APIs
- Serverless and scalable
- Supports RESTful APIs and WebSocket APIs
- Support for security, user authentication, API throttling, API keys, monitoring…
Microservices
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Monolithic Architecture- One app which is resonsible for everyting functionality is tightly coupled.
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Microservices Architecture- Multiple apps which are each resonsible for one thing functionality is isolate and stateless.
Summary
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Docker: container technology to run applications
ECS: run Docker containers on EC2 instancesFargate:- Run Docker containers without provisioning the infrastructure
- Serverless offering (no EC2 instances)
ECR: Private Docker Images RepositoryBatch: run batch jobs on AWS across managed EC2 instances
-
Lambdais Serverless, Function as a Service, seamless scaling, reactive- Lambda Billing:
- By the time run x by the RAM provisioned
- By the number of invocations
- Language Support: many programming languages except (arbitrary) Docker
- Invocation time: up to 15 minutes
- Use cases:
- Create Thumbnails for images uploaded onto S3
- Run a Serverless cron job
API Gateway: expose Lambda functions as HTTP API
- Lambda Billing: