In this episode, Darren talks about the history of applications and how recent changes, primarily due to the onslaught of data from the Internet of Things, is affecting data-centric architectures. The infrastructure is ready, but we don’t yet have a suitable way to manage all our data. There are three elements that need to change to facilitate this process: people (organization), process (operation), and architecture (technology). Darren focuses on the architecture where data and compute are spread over thousands of edge devices and across public and private clouds.
https://www.embracingdigital.com/2020/01/episode-11-history-of-data-centric.html
2. Purpose Built Software and Hardware
Stack
Purpose Built Software and Hardware
Stack
Building Applications for Missions
Application 1 Data
Compute Storage Network
Application 2 Data
Compute Storage
• Long Development Times
• No re-use of technology
• Technology moves too fast
• Hard to integrate as Technology Drifts
• Cost increases due to lack of reuse
4. Private Clouds
Cloud Technology (Operations Abstraction)
Application 1 Data
Compute Storage Network
Application 2 Data
• Common Hardware re-use
• Decrease Cost OpEx and CapEx
• Bursting ability
• Security concerns increase
• Noisy neighbors
• Integration costs
VM VMVSAN VSANNVF NVF
Application n Data
Public Clouds
5. Private CloudsPrivate Clouds
Service and Container Technology
Application 1 Data
Compute Storage Network
Application 2 Data
• Automatic deployment across Clouds
• Optimized OpEx and CapEx
• Fault tolerance
• Easier Integration
• Security concerns increase
• Increased complexity
• Where’s my data
VM VMVSAN VSANNVF NVF
Application n Data
Public Clouds
Public Clouds
Service Management Layer
Containers
Overlay
Network
Volume Containers Volume
Overlay
Network
Containers VolumeContainers Containers Containers
6. Private CloudsPrivate Clouds
Internet of Things
Application 1 Data
Compute Storage Network
Application 2 Data
• Increase the amount of Data
• Visibility increases
• Security concerns increase
• Increased complexity
• Where’s my data
VM VMVSAN VSANNVF NVF
Application n Data
Public Clouds
Public Clouds
Service Management Layer
Containers
Overlay
Network
Volume Containers Volume
Overlay
Network
Containers VolumeContainers Containers Containers
IoT
7. Organizations are Changing
Data ScientistData Steward
IT Ops Data Engineer
CDO App Dev
Manage
Infrastructure
Manage
Data / Policies
Set Data Policy
& Strategy
Develop
Apps
Analyze Data
Derive Information
Manage
Sources,Blue Prints,
& Procedures
Distributed Information
Management Layer
8. Distributed Information Management Layer
Private CloudsPrivate Clouds
Data and Information Management
Application 1 Data
Compute Storage Network
Application 2 Data
• Automatic data management
• Data Locality
• Data Governance
• Security concerns increase
• Classification Profiles Not supported
VM VMVSAN VSANNVF NVF
Application n Data
Public Clouds
Public Clouds
Service Management Layer
Net
V
C C CV VNet
IoT
Meta-Data
Data
Orchestration
Data Mgmt
9. Security and Identity
• Common Identity (People, Devices, Software)
• Access, Authorization, Authentication
• Detect attacks throughout the ecosystem
• Establish root of trust from through the stack
• Quarantine with reliability
Distributed InformationManagement Layer
Private Clouds
Private Clouds
Application 1 Data
Compute Storage Network
Application 2 Data
VM VMVSAN VSANNVF NVF
Application n Data
Public Clouds
Public Clouds
Service Management Layer
Net
V
C C CV VNet
IoT
Meta-Data
Data
Orchestrator
Identity
Aspect
Security
Aspect
Access
Authorize
Authenticate
Key
Management
Root of
Trust
Detect
Remediate
Encrypt
Data Mgmt
10. Edgemere Architectural View
Common Physical Layer
Application Layer
Distributed Information
Management
Layer
Service
Management Layer
Software Defined Infrastructure
SecurityAspect
IdentityAspect