On one hand media enterprises using workflows involving thick apps and traditional server based workflows have business opportunities of lifting and shifting from on-prem infrastructure to off-prem cloud or centralized data centers. On the other hand, cloud native micro-services architectures and web apps provide options to implement new services and apps rapidly and dynamically. This talk provides insights into the different hosting patterns observed from these media enterprises, and discusses a common framework provided by Avid’s Media Central Platform to realize the business opportunities under the different hosting models. Speaker : Shailendra Mathur, VP Architecture, AVID

1. 1
Cloud Transition Patterns for Media
Enterprises
Shailendra Mathur
Vice President of Architecture, Avid

2. 2 Confidential and Proprietary Information. Please do not copy, forward, redistribute, or publish. Avid ©2017.
Topics
 Understanding current media production infrastructure
 Different “Cloud” definitions evolving in the media Industry
 Lift & Shift methods vs Micro-services based implementations
 Avid Media Central Platform based communication fabric across
hosting models

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Source: http://ngcodec.com/fpga-encoder-markets/
Narrowing the problem domain

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Existing production workflows and infrastructure
Asset Management & Storage

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Machine Rooms/Datacenter
• VM/Bare Metal
• Single Customer Instance
• Network Storage
• Edge servers (SDI/IP)
Interpretation of “Cloud” in the media industry
On-prem Cloud
• VMs & Containers
• Single customer Instance
• Private
• Network/Cloud Storage
Private Cloud
• VMs & Containers
• Single customer
Instance
Public Cloud
• VM & Containers
• Public Cloud Provider
• Multiple customers
“Local” Cloud
• VMs & Containers
• Managed Service
provider
• Multiple customer
CoLo Datacenter
• Storage
• Edge Servers (IP)
Cloud “On-Prem”
WAN
High
Bandwidth
Network Link
Hybrid Cloud
Ali, AWS, MSFT, IBM, Google…
HP, Dell, VMWare, IBM, MSFT, Huawei…

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Media services hosting patterns
Host OS
Any
App
Any
App
Any
App
Bare Metal
Hypervisor Layer
Guest
OS
App1
Compute, Network, Storage,
VDI,, A/V IP interfaces
Bins/
Libs
Guest
OS
App2
Bins/
Libs
Guest
OS
App3
Bins/
Libs
CloudProvider
(IaaS)
AppProvider
(VirtualMachines)
Virtualized
Cloud or On Prem
Operating System
App1
Compute, Network, Storage
Bins/
Libs
CloudProvider
(PaaS)
AppProvider
(Containers)
Bins/Libs
App2 App3
Micro-Services Containers
Cloud Native
Docker Engine
AppProvider
(Machines)
Compute, Network, Storage,
Display, A/V IP/SDI
interfaces, Controllers
Web Client
Web
Client
Thick
Client
Web
Client
Thick
Client

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Why Micro-Services?
Multi-function software appliance

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Multi-function software appliance

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…vs multiple functional micro-services
1 2 3 4

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Service hosting and communication
App Provider
Communication Fabric
App Provider
Communication Fabric
Cloud Provider
Communication Fabric
Bare Metal Virtualized
Cloud or On Prem
Micro-services Containers
Cloud Native

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Service hosting and communication
Common communication event and message bus
(App Provider)
Bare Metal Virtualized
Cloud or On Prem
Micro-services Containers
Cloud Native

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Why a message bus?
1
3
4 2
5
6
7
8
9
10
Point to Point Traditional communication fabric

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Traditional communication fabric

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…vs pub-sub service interactions
5
Event Enabled Microservices
(Publish/Subscribe)
1 2 3 4

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Common service communication framework
Cloud Native
Federated Message BusFederated Message Bus Federated Message| Bus
Bare Metal Virtualized Data Center Cloud

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Media ingest & processing example
Federated Message BusFederated Message Bus Federated Message| Bus
Cloud Upload
Bare Metal Virtualized Data Center Cloud

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Avid Media Central framework
Service
Management
Service
Execution
User Admin
& Config
Connectivity
Toolkit
Cloud Native
API Upstreams
Federated Message BusFederated Message Bus Federated Message| Bus

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Summary
 “Cloud” has different hosting interpretations
 The Media Industry looking to implement both Lift and Shift and
Cloud native models
 Avid Media Central Framework bridges the different hosting models

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Multiple message & data model formats
…
…

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Common message data model interpreters
…
…