Video Transcoding Reference Architecture
This reference architecture provides a concrete example of how to create a scalable, portable, and cost-effective media processing workflow. A traditional Video On-Demand (VOD) workflow is demonstrated in which a source video is output to an online distribution format. The prescribed architecture for this workflow can be cost-effectively scaled and extended to the formats required for your video transcoding use-cases. Some use-cases addressed by this workflow include:
- Supporting content for blogs or social media
- Producing video or digital assets for streaming services
- Embedding content in business applications
Review the video transcoding architecture diagrams for a high-level depiction of a general video transcoding workflow, as well as a more granular version which prescribes specific technologies to implement the workflow.
The workflow in this document is implemented on the Akamai Connected Cloud (in particular, the Linode Kubernetes Engine), Akamai CDN, and a GitHub Actions-powered CI/CD powered pipeline. The full accounting of technologies used includes:
Akamai Connected Cloud technologies:
Technology Description Linode Kubernetes Engine (LKE) A fully-managed K8s container orchestration engine for deploying and managing containerized applications and workloads NodeBalancers Managed cloud load balancers Object Storage S3-compatible Object Storage, used to manage unstructured data like video files Block Storage Network-attached block file storage volumes API Programmatic access to Linode products and services DNS Manager Domain management, free for Akamai Connected Cloud customers
Other software and services:
Technology Description Argo Kubernetes-native workflow engine FFmpeg Encoding/decoding/transcoding multimedia framework PyTranscoder Python wrapper for FFmpeg MediaInfo Gathers metadata for audio/video files GitHub Git-based managed version control service Terraform Infrastructure-as-code provisioning tool Helm Package manager for Kubernetes DockerHub Container image library Let’s Encrypt Free, automated, open certificate authority cert-manager Cloud native certificate management NGINX Load balancer, web server, and reverse proxy Prometheus Monitoring system and time series database Grafana Observability platform
Extensibility: This reference architecture supports a myriad of media output format types and workflow step definitions. It can be configured to output to any device, platform, or audience specification.
Scalability: This solution supports horizontal scalability by adding more Linodes within the Kubernetes cluster, which enables high throughput. Scaling this solution allows you to process a large amount of content in a short period of time. Scaling can support service launch or marketing campaign requirements.
Cost-effectiveness: Traditional media workflows have to keep a deployed capacity for peak usage. This reference architecture is built on Kubernetes and uses the Argo workflow engine, which supports dynamic pod scheduling and tear-down. Because of this dynamic resource usage, your cost footprint can be minimized.
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