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Dify on AWS with CDK

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Self-host Dify, an LLM app development platform, using AWS managed services with AWS CDK.

architecture

Key Features:

  • Fully managed services requiring less maintenance effort
    • Aurora servereless v2, ElastiCache, ECS Fargate, etc.
  • Cost effective architectural decisions
    • allow to use NAT instances instead of NAT Gateway, and Fargate spot capacity by default
  • Easily integrate with Bedrock models and Knowledge Bases

本リポジトリの使い方について、日本語で書かれた記事もあります:

Prerequisites

You must have the following dependencies installed to deploy this app:

Deploy

You can adjust configuration parameters such as AWS regions by modifying bin/cdk.ts. Please also check EnvironmentProps interface for all the available parameters.

Then you can run the following commands to deploy the entire stack.

# install npm dependencies
npm ci
# bootstrap the AWS account (required only once per account and region)
npx cdk bootstrap
# deploy the CDK stack
npx cdk deploy --all

The initial deployment usually takes about 20 minutes. After a successful deployment, you will get the URL for the app.

 ✅  DifyOnAwsCdkStack

✨  Deployment time: 326.43s

Outputs:
DifyOnAwsStack.DifyUrl = https://dify.example.com

You can open the URL with a browser and get started!

Deploy from CloudShell

You can use a dedicated script that works even in an environment with limited storage space such as AWS CloudShell.

In CloudShell, you can just run the following commands:

git clone https://github.com/aws-samples/dify-self-hosted-on-aws.git
cd dify-self-hosted-on-aws
./simple-deploy.sh

Then follow the prompts from the shell script. You will finally get the DifyOnAwsStack.DifyUrl output in the CLI.

Tips

Here is the information that might help when you use Dify on AWS.

Setup Dify to use Bedrock

After logged in, you can setup Dify to use Bedrock LLMs.

Important

Before setting up models in Dify, you have to enable models you want to use in Bedrock management console. Please read this document for more details.

Go to settings by clicking the right-top profile, click WORKSPACE -> Model Provider, and select AWS Bedrock model.

IAM policies are already configured properly, so you can just select a correct AWS region (where the models are enabled) to use Bedrock models, and click Save.

model-setup

Add Python packages available in code execution

You can add Python packages that is available in Dify code execution feature. Edit python-requirements.txt following the Requirements File Format.

In some libraries, you have to allow additonal system calls in Dify sandbox. This CDK project let you to allow all the system calls by allowAnySysCalls flag in bin/cdk.ts.

Warning

If you enable allowAnySysCalls flag, please make sure that code executed in your Dify tenant can be fully trusted.

Please also refer to this blog article for more details: Using any Python libraries in Dify's code block

Connect to Bedrock Knowledge Bases

You can use the External Knowledge Base feature to connect to Amazon Bedrock Knowledge Bases. Because the external knowledge API is deployed as a sidecar of Dify API, you can use the feature immediately with the following steps:

  1. Click Dify -> Knowledge -> Add an External Knowledge API button.
    • add external knowledge api
  2. Fill the form as below:
    1. Name: any name as you like (e.g. Bedrock Knowledge Bases)
    2. API Endpoint: http://localhost:8000
    3. API Key: dummy-key (you can configure it by editing BEARER_TOKEN environment variable in api.ts.)
  3. Click Dify -> Knowledge -> Create Knowledge -> Connect to an External Knowledge Base
    • Connect to an External Knowledge Base
  4. Fill the form as below
    1. External Knowledge Name / Knowledge Description: any string
    2. External Knowledge API: the external API you created in the previous step
    3. External Knowledge ID: The Bedrock Knowledge Base ID you want to use. The AWS region is us-west-2 by default, but you can override the AWS region by adding region prefix with colon, e.g. us-east-1:QWERTYASDF.
  5. Now you can use the knowledge from Dify tools.

For more information, please refer to this article: Dify can also do RAG on documents with charts and graphs!

Scaling out / Scaling up

Although this system is designed with infrastructure scalability in mind, there are several tuning knobs that you might want to explicitly set as you prepare for larger numbers of users.

The below are the list of configurable parameters and their default values:

  1. ECS Task (api.ts, web.ts)
    1. Size
      1. api/worker: 1024vCPU / 2048MB
      2. web: 256vCPU / 512MB
    2. Desired Count
      1. 1 task for each service
  2. ElastiCache (redis.ts)
    1. Node Type: cache.t4g.micro
    2. Node Count: 1
  3. Aurora Postgres (postgres.ts)
    1. Serverless v2 maximum capacity: 2 ACU

Deploying to a closed network (a.k.a 閉域要件)

You can deploy the system on a closed network (i.e. a VPC without internet gateway or NAT gateway) with a few simple additional steps.

To deploy on a closed network, please follow the steps below:

  1. Set configuration parameters in bin/cdk.ts as below:

    export const props: EnvironmentProps = {
        // set region and account explicitly.
        awsRegion: 'ap-northeast-1',
        awsAccount: '123456789012',
    
        // Set your internal IP address ranges here.
        allowedIPv4Cidrs: ['10.0.0.0/16'],
    
        // The below two flags must be set for closed network deployment.
        useCloudFront: false,
        internalAlb: true,
    
        // If Docker Hub is not accessible from your vpc subnets, set this property and run copy-to-ecr script (see step#2)
        customEcrRepositoryName: 'dify-images',
    
        // To let the CDK create a VPC with closed network, set this property.
        vpcIsolated: true,
        // Or, optionally you can import an existing VPC.
        vpcId: 'vpc-12345678',
    
        // Other properties can be configured as you like.
    };
  2. Open python-requirements.txt and remove all the dependencies from it

    • This is only required if PyPI is not accessible from your vpc subnets.
  3. Copy all the dify container images in Docker Hub to an ECR repository by executing npx ts-node scripts/copy-to-ecr.ts.

    • The script handles all the tasks required to copy images. You will also need to run npm ci before this.
      • You can create an ECR repository with the name of customEcrRepositoryName by yourself, or the script creates one if it does not exist yet.
      • This script must be executed in an environment that has access to the Internet.
      • Please run the script every time you change difyImageTag or difySandboxImageTag property.
    • This is only required if Docker Hub is not accessible from your vpc subnets.
  4. If you are using an existing VPC (vpcId property), make sure the required VPC endpoints are provisioned before deployment.

    • See vpc-endpoints.ts for the list of required VPC endpoints.
    • If you let CDK create a VPC (by setting vpcIsolated: true), all the endpoints are created automatically.
  5. Deploy the CDK project following the Deploy section.

  6. After the deployment, please configure Bedrock in Dify with the same AWS region as your VPC (see setup section)

    • This is only required if Bedrock API in other regions are not accessible from your vpc subnets.

Clean up

To avoid incurring future charges, clean up the resources you created.

npx cdk destroy --force
# If you encountered an error during the deletion, please retry. It happens sometimes.

If you set customEcrRepositoryName and have run the copy-to-ecr.ts script, please remove the container repository and images in it manually.

Cost

The following table provides a sample cost breakdown for deploying this system in the us-east-1 (N. Virginia) region for one month (when deployed using cheap configuration).

AWS service Dimensions Cost [USD]
RDS Aurora Postgres Serverless v2 (0 ACU) $0
ElastiCache Valkey t4g.micro $9.2
ECS (Fargate) Dify-web 1 task running 24/7 (256CPU) $2.7
ECS (Fargate) Dify-api/worker 1 task running 24/7 (1024CPU) $10.7
Application Load Balancer ALB-hour per month $17.5
VPC NAT Instances t4g.nano x1 $3.0
TOTAL estimate per month $43.1

Note that you have to pay LLM cost (e.g. Amazon Bedrock ) in addition to the above, which totally depends on your specific use case.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file. You should also check Dify's license.

Acknowledgement

This CDK code is heavily inspired by dify-aws-terraform.

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