awslabs / visual-asset-management-system

Visual Asset Management System (VAMS) is a purpose-built, AWS native solution for the management and distribution of specialized visual assets used in spatial computing.

Visual Asset Management System(VAMS)

Introduction

Visual Asset Management System (VAMS) is a purpose-built, AWS native solution for the management and distribution of specialized visual assets used in spatial computing. VAMS offers a simplified solution for organizations to ingest, store, and manage visual assets in the cloud, which empowers any user with a web browser to upload, manage, visualize, transform, and retrieve visual assets. Existing workflows that leverage both custom code and pre-built or third-party applications can also be migrated to VAMS and ran in the AWS cloud, as opposed to being limited by the on-premise capacity available. VAMS is customizable and expandable with option of being further tailored to specific use-cases by development teams.

Customer Value: VAMS addresses challenges faced by customers embarking on Spatial Computing initiatives, such as Augmented and Virtual Reality (AR/VR). Organizations that previously had to manage these assets on local systems can now do so from a web-based application.

Leveraging Amazon Simple Storage Service (Amazon S3) as a low-cost, high availability storage layer, VAMS provides a purpose-built API for 3D asset management. This API provides a layer of abstraction, allowing custom integrations to be built. Custom integrations allow workloads and applications to be moved to the cloud, unlocking access to the entire breadth and depth of the AWS ecosystem.

Use Cases: Sample use cases that have leveraged early iterations of VAMS include:

• Distribution and management of 3D Assets using highly available S3 storage
• Modifications of 3D assets using VAMS Pipelines
• Creating workflows for 3D asset modification using VAMS Workflows

Screenshots

Architecture Overview

3D Asset Types Supported for In-Browser Viewing

VAMS currently integrates with several different asset viewers and supports the following formats for viewing assets interactively.

Name	Extension	Type	Viewer
Wavefront	obj	text	Online 3D Viewer
3D Studio	3ds	binary	Online 3D Viewer
Stereolithography	stl	text	Online 3D Viewer
Stereolithography	stl	binary	Online 3D Viewer
Polygon File Format	ply	text	Online 3D Viewer
Polygon File Format	ply	binary	Online 3D Viewer
glTF	gltf	text	Online 3D Viewer
glTF	glb	binary	Online 3D Viewer
Object File Format	off	text	Online 3D Viewer
Object File Format	off	binary	Online 3D Viewer
Dotbim	bim	text	Online 3D Viewer
Rhinoceros 3D	3dm	binary	Online 3D Viewer
Filmbox	fbx	text	Online 3D Viewer
Filmbox	fbx	binary	Online 3D Viewer
Collada	dae	text	Online 3D Viewer
Virtual Reality Modeling Language	wrl	text	Online 3D Viewer
3D Manufacturing Format	3mf	text	Online 3D Viewer
Industry Foundation Classes	ifc	text	Online 3D Viewer
Point Cloud - LiDAR Data Exchange	laz	binary	Potree Viewer
Point Cloud - LiDAR Data Exchange	las	binary	Potree Viewer
Point Cloud - LiDAR Data Exchange	e57	binary	Potree Viewer

Viewers available include:

• Online 3D Viewer
• Potree Viewer

Please take note:

• While we are limited to these formats to view assets, any file format may be uploaded to VAMS.
• There are some limitations with formats that leverage multiple files such as glTF that uses json with references to other files.
• Some viewers like Potree Viewer requires additional pipelines to be deployed to fully generate and view visualizer files.

Install

Requirements

• Python 3.8
• Poetry (for managing python dependencies in the VAMS backend)
• Docker
• Node >=16.x
• Yarn >=1.22.19
• Node Version Manager (nvm)
• AWS CDK cli
• Programatic access to AWS account at minimum access levels outlined above.

Deploy VAMS for the First Time

Build & Deploy Steps (Linux/Mac)

VAMS Codebase is changing frequently and we recommend you checkout the stable released version from github.

You can identify stable releases by their tag. Fetch the tags git fetch --all --tags and then git checkout tags/TAG or git checkout -b TAG tags/TAG where TAG is the actual desired tag. A list of tags is found by running git tag --list or on the releases page.

1. cd ./web && nvm use - make sure you're node version matches the project. Make sure Docker daemon is running.

2. yarn install - make sure you install the packages required by the web app (Take note, npm install does not result in a working build of the application - please use yarn).

3. npm run build - build the web app.

4. cd ../infra && npm install - installs dependencies defined in package.json.

5. If you haven't already bootstrapped your aws account with CDK. cdk bootstrap aws://101010101010/us-east-1 - replace with your account and region.

6. Set the CDK stack name and the region for deployment with environment variables export AWS_REGION=us-east-1 && export STACK_NAME=dev - replace with the region you would like to deploy to and the name you want to associate with the cloudformation stack that the CDK will deploy.

7. (Optional) Set the optional feature to deploy the Point Cloud (PC) visualizer pipeline with environment variables export PIPELINEACTIVATE_PCVISUALIZER=true - the point cloud (PC) visualizer pipeline stack is for viewing Point Cloud files in the VAMS visualizer preview. You can optionally set this via CDK deploy context parameter. Note: This does deploy additional AWS components such as a VPC and EPV endpoints that may have additional static infrastructure costs.

8. npm run deploy.dev adminEmailAddress=[e-mail] - replace with your email address to deploy. An account is created in an AWS Cognito User Pool using this email address. Expect an email from [e-mail] with a temporary password.

Deployment Success

1. Navigate to URL provided in {stackName].WebAppCloudFrontDistributionDomainName{uuid} from cdk deploy output.

2. Check email for temporary account password to log in with the email address you provided.

Multiple Deployments With Different or Same Region in Single Account

You can change the region and deploy a new instance of VAMS my setting the environment variables to new values (export AWS_REGION=us-east-1 && export STACK_NAME=dev) and then running npm run deploy.dev adminEmailAddress=[e-mail] again.

Deploy VAMS Updates

To deploy customzations or updates to VAMS, you can update the stack by running cdk deploy --all. A changeset is created and deployed to your stack.

Please note, depending on what changes are in flight, VAMS may not be available to users in part or in whole during the deployment. Please read the change log carefully and test changes before exposing your users to new versions.

Already have Assets in S3 that you want to register in VAMS?

VAMS can be deployed with a staging-bucket parameter to enable copying from an existing asset bucket.

to deploy with staging bucket, just pass the staging-bucket paramter to your cdk deployment and VAMS will register your existing bucket as a staging bucket.

Once the deployment is complete, you can invoke the /assets/uploadAssetWorkflow API to start copying the assets into the VAMS S3 bucket.

Please refer to the uploadAssetWorkflow in the API docs to find out about the API request body.

Architecture components

Backend

VAMS Backend is composed of AWS Lambda functions that are accessed through an AWS API Gateway.

Architecture diagrams for Individual components

Asset Management

Pipelines Creation

Pipelines are a feature in VAMS that allow you to edit

Workflows Execution

Frontend

VAMS Frontend is a ReactJS application.

Security

VAMS API and frontend are authorized through AWS Cognito user accounts by default.

Federated authentication with SAML is available with additional configuration. See SAML Authentication in the developer guide for instructions.

Code Layout

component	folder
web application	web
cdk deployment	infra
api and backend	backend

Demo and Workshop

Checkout the VAMS workshop for detailed walkthrough

Developers

To know more about how VAMS works and for instructions on configuring pipeline & workflow, refer to the Developer Guide developer guide.

Writing your own VAMS pipelines

Refer to the Writing your own pipelines section in the Developer Guide.

Security

VAMS is provided under a shared responsibility model. Any customization for customer use must go through an AppSec review to confirm the modifications don't introduce new vulnerabilities. Any team implementing takes on the responsibility of ensuring their implementation has gone through a proper security review.

1. Run yarn audit in the web directory prior to deploying front-end to ensure all packages are up-to-date. Run yarn audit fix to mitigate critical security vulnerabilities.
2. When deploying to a customer account, create an IAM Role for deployment that limits access to the least privilege necessary based on the customers internal security policies.

Uninstalling

1. Run cdk destroy --all from infra folder.
2. Some resources may not be deleted by CDK (e.g S3 buckets and DynamoDB tables, pipeline stacks). You may delete them using the AWS CLI or the AWS Console.

Contributing

See the CONTRIBUTING file for how to contribute.

Costs

The costs of this solution can be understood as fixed storage costs and variable costs of the pipelines that you configure. Storage cost is proportional to the amount of data you upload to VAMS including new data you create using VAMS pipelines.

You are responsible for the cost of the AWS services used while running this solution. Ensure that you have billing alarms set within the constraints of your budget.

An approximate cost breakdown is below (excluding free tiers):

Service	Quantity	Cost
Amazon API Gateway	150000 requests	$0.16
Amazon DynamoDB	750000 writes, 146250 reads, 0.30 GB storage	$1.18
AWS Lambda	12000 invocations, 2-minute avg. duration, 256 MB memory	$6
AWS Step Functions	92400 state transitions	$2.21
Amazon S3	10 GB storage, 4000 PUT requests, 4000 GET requests	$0.26
Amazon Rekognition	9000 Image analysis, 3 Custom Label inference units	$22.32
Amazon SageMaker	2 inference endpoints	$5.13
Amazon Elastic Container Registry	ECR (In region)40GB	$4

Below are the additional costs for including visualizer pipeline and their outputs in your deployment:

Service	Quantity	Cost
VPC	7 VPC endpoints per AZ (1 AZ configuration){Static Cost}	$51.11
Batch Fargate	10 hours of processing	$3.56
Amazon S3	300 GB storage, 30GB transfer out	$9.60
Amazon Cloudwatch	1GB logs - VPC Flowlogs/API Gateway/Pipeline	$3.28

License

See the LICENSE file for our project's licensing.

Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.