IT Architecture – How to capture video streams from IP cameras, store in the cloud with a 7-year retention period, and provide live streaming and playback functions

Scenario: ACME PTY LTD wants to achieve requirements of capturing video streams from IP cameras, storing them in the cloud with a 7-year retention period, and providing live streaming and playback functions, you can leverage various AWS services along with some additional components. By leveraging these AWS services and components, you can build a scalable, cost-effective, and secure video streaming and storage solution with long-term retention, live streaming, and playback functions.

AWS Azure solution:

Here’s a high-level overview of how you can set up such a system:

1. IP Camera Setup:

• Ensure your IP cameras are compatible with RTSP (Real-Time Streaming Protocol) or other streaming protocols supported by AWS services.
• Configure your IP cameras to stream video to your AWS infrastructure.

2. AWS Services and Components:

a. Amazon Kinesis Video Streams:

• Use Amazon Kinesis Video Streams to ingest, process, and store video streams from your IP cameras.
• Kinesis Video Streams can handle real-time streaming of video data from millions of devices, making it suitable for your live streaming requirement.

b. Amazon S3 (Simple Storage Service):

• Store the video streams for long-term retention in Amazon S3.
• Set up lifecycle policies to automatically transition older video data to Amazon Glacier for cost optimization, as Glacier provides lower-cost storage suitable for long-term retention.

c. AWS Elemental MediaLive:

• Use AWS Elemental MediaLive for live video encoding and streaming.
• Configure MediaLive to ingest video streams from Kinesis Video Streams and encode them for live streaming.

d. Amazon CloudFront:

• Utilize Amazon CloudFront as a content delivery network (CDN) to deliver your live streams with low latency and high transfer speeds.
• Configure CloudFront to distribute your live streams to viewers globally.

e. Amazon DynamoDB:

• Use Amazon DynamoDB to store metadata related to your video streams, such as timestamps, camera IDs, and playback URLs.
• DynamoDB can be used to manage and query metadata for playback functions.

f. AWS Lambda:

• Implement AWS Lambda functions for various tasks such as:
  • Periodic cleanup of old video data based on retention policies.
  • Generating signed URLs for secure access to video playback.
  • Triggering alerts or notifications based on events such as camera disconnects or unusual activity.

3. Architecture Overview:

Additional Considerations:

• Security: Ensure proper security measures are in place to protect your video streams and data. Use AWS IAM (Identity and Access Management) for access control, encryption in transit and at rest, and other security best practices.
• Cost Optimization: Regularly monitor and optimize costs by leveraging features like S3 lifecycle policies, CloudFront caching, and selecting appropriate instance types for MediaLive.
• Scalability: Design your architecture to scale horizontally to handle increasing numbers of cameras and viewers over time.
• Compliance: Consider any regulatory requirements or compliance standards applicable to your use case, especially regarding data privacy and retention.

Microsoft Azure solution:

ACME PTY LTD can implement a similar solution using Microsoft Azure services. By leveraging these Azure services and components, you can build a scalable, secure, and cost-effective video streaming and storage solution with long-term retention, live streaming, and playback functions.

Here’s how you can set up video stream capture from IP cameras, storing them in the cloud with a 7-year retention period, and providing live streaming and playback functions using Azure services:

1. IP Camera Setup:

• Ensure your IP cameras support streaming protocols such as RTSP or others compatible with Azure services.
• Configure your IP cameras to stream video to your Azure infrastructure.

2. Azure Services and Components:

a. Azure IoT Hub:

• Use Azure IoT Hub for ingesting and managing data from your IP cameras.
• IoT Hub can handle large-scale telemetry ingestion from millions of devices, making it suitable for streaming video data.

b. Azure Blob Storage:

• Store the video streams for long-term retention in Azure Blob Storage.
• Set up lifecycle management policies to automatically move older video data to Azure Archive Storage for cost optimization.

c. Azure Media Services:

• Utilize Azure Media Services for live video encoding, streaming, and video-on-demand (VOD) playback.
• Configure Media Services to ingest video streams from IoT Hub and encode them for live streaming.

d. Azure Content Delivery Network (CDN):

• Use Azure CDN to deliver your live streams with low latency and high transfer speeds.
• Configure CDN endpoints to distribute your live streams to viewers globally.

e. Azure Cosmos DB:

• Use Azure Cosmos DB to store metadata related to your video streams, such as timestamps, camera IDs, and playback URLs.
• Cosmos DB can provide low-latency, globally distributed database capabilities for managing metadata.

f. Azure Functions:

• Implement Azure Functions for various tasks such as:
  • Periodic cleanup of old video data based on retention policies.
  • Generating signed URLs for secure access to video playback.
  • Triggering alerts or notifications based on events such as camera disconnects or unusual activity.

3. Architecture Overview:

Additional Considerations:

• Security: Implement Azure Active Directory (Azure AD) for identity and access management, encryption, and other security measures to protect your video streams and data.
• Cost Optimization: Use Azure Cost Management to monitor and optimize costs by leveraging features like Blob Storage lifecycle management, Azure CDN caching, and selecting appropriate instance types for Media Services.
• Scalability: Design your architecture to scale horizontally to handle increasing numbers of cameras and viewers over time.
• Compliance: Consider any regulatory requirements or compliance standards applicable to your use case, especially regarding data privacy and retention.

Learn about AWS IoT Greengrass for your reference.

AWS IoT Greengrass is a service that extends AWS cloud capabilities to local devices, enabling them to collect and analyse data closer to the source, while also allowing them to interact securely with cloud services for management, storage, and analytics. Greengrass is particularly useful in scenarios where low latency, intermittent connectivity, or data privacy concerns make local processing preferable. By leveraging AWS IoT Greengrass along with other AWS services, you can create a robust and scalable solution for capturing, processing, storing, and streaming video data from IP cameras, meeting both real-time and long-term retention requirements.

Using AWS IoT Greengrass for Video Stream Capture, Storage, and Playback

To use AWS IoT Greengrass for capturing video streams from IP cameras and integrating with AWS cloud services for long-term storage, live streaming, and playback, you can follow this approach:

1. IP Camera Setup

• Ensure your IP cameras support protocols compatible with Greengrass (e.g., RTSP).
• Configure the cameras to stream video to a local device running Greengrass Core software.

2. AWS IoT Greengrass Setup

a. Install Greengrass Core

• Set up a local device (like a Raspberry Pi or an industrial gateway) and install AWS IoT Greengrass Core software on it.
• Follow the Greengrass Core installation guide to install and configure the core.

b. Deploy Lambda Functions Locally

• Use Greengrass to deploy Lambda functions that process video streams locally. These functions can handle tasks like transcoding, filtering, and buffering video data.

3. Cloud Integration

a. Kinesis Video Streams

• Use AWS IoT Greengrass to stream video data to Amazon Kinesis Video Streams. This can be done using a Lambda function deployed on Greengrass that captures video data and sends it to Kinesis Video Streams.

b. Long-Term Storage in S3

• From Kinesis Video Streams, configure the video data to be stored in Amazon S3 for long-term retention. Use S3 lifecycle policies to transition data to Amazon S3 Glacier for cost-effective long-term storage.

c. Live Streaming with AWS Elemental MediaLive

• Use AWS Elemental MediaLive to process the video streams from Kinesis Video Streams for live broadcasting.
• Configure AWS Elemental MediaPackage to package the video streams for delivery and use Amazon CloudFront for CDN to distribute the live streams globally.

d. Metadata Management with DynamoDB

• Store video metadata (timestamps, camera IDs, playback URLs) in Amazon DynamoDB. This database can be used to query and manage video playback requests.

e. Playback Functionality

• Implement an application that uses AWS SDKs to interact with DynamoDB for metadata retrieval, S3 for fetching stored videos, and CloudFront for live stream playback.
• Utilize AWS Lambda for backend processing tasks like generating signed URLs for secure access to video content.

Architecture Overview

Additional Considerations

• Security: Use AWS IoT Greengrass security features to manage device authentication and authorization, and ensure data encryption in transit and at rest.
• Scalability: Design your solution to add new IP cameras and local Greengrass devices as needed, and configure cloud services to handle increased data loads.
• Cost Management: Monitor and optimize costs by using S3 lifecycle policies, selecting appropriate instance types, and using cost management tools provided by AWS.
• Compliance: Ensure your solution complies with relevant regulations and standards for data privacy and retention, especially given the long-term storage requirement.

Also, referenced the following Restreamer.

Referenced diagram, live streaming architecture.