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Three Critical Questions to Ask:
● What complexities will HCI introduce into the environment?
● Will HCI extend your on-premises data center to the cloud?
● Will the HCI scale to meet the organization’s performance demands?
Considering Hyperconverged for
Your Enterprise?
Webinar
For audio playback and Q&A go to: http://bit.ly/HyperConv3
Our Speakers
Clint Wyckoff is the Senior Solutions Engineer at Datrium and has over a decade of real-world enterprise
data center architecture experience. He places a large emphasis on helping IT Professionals solve the
issues they're challenged with daily. Clint is an energetic and engaging speaker, blogger and author that
has been recognized in the community for significant contributions. He is a 2x Microsoft Most Valuable
Professional (MVP) for Cloud and Data Center Management, a VMware vExpert for 2015, 2016 & 2017,
Cisco Champion and an inaugural MODE charter member. Clint is also a certified AWS Solutions
Architect.
George Crump is the founder of Storage Switzerland, the leading storage analyst focused on the
subjects of big data, solid state storage, virtualization, cloud computing and data protection. He is widely
recognized for his articles, white papers, and videos on such current approaches as all-flash arrays,
deduplication, SSDs, software-defined storage, backup appliances, and storage networking. He has over
25 years of experience designing storage solutions for data centers across the US.
Level Set: The
What and Why of
Hyperconverged
Infrastructure
● Single Node with
Compute, Storage
● Focus in on simplifying a
dynamic, sprawling data
center
● Auto-scales as nodes are
added to HCI cluster
The Challenges
of HCI in the
Enterprise
● As nodes are added complexity increases
and efficiency declines
● Problem is that each node includes compute,
storage and network
● Specifically Storage
○ Each node has to deliver high performance
○ AND long term data retention
● Expansion is inefficient
○ Most data centers scale one of the three vectors
■ Storage performance
■ Storage capacity
■ Application compute performance
Understanding the Typical HCI Storage Architectures
● Each node is self-contained storage asset then replicated to another node for
availability and data protection
○ Networking less of an issue
○ Limited to storage performance of single node
○ VM mobility limited to other nodes with replica
● Data is striped across nodes
○ Networking is major issue
○ Metadata/Cluster management is more complex
○ Performance is impacted because data must be accessed across the network
The Performance
Problems of HCI in the
Enterprise
● Compute is overworked
○ Drives applications performance
○ Drives storage software
○ Drives cluster management (which is often complex)
● Leads to
○ Inconsistent performance
○ Concerns about noisy neighbors
○ Concerns about network performance
HCI Performance Workarounds
● All-Flash NDI
○ Expensive
■ HCI storage also has retention
responsibilities
■ HCI storage also has protection
responsibilities
● 3X increase in consumption
with replication
○ Overkill
■ Most applications don’t need it
■ 80% of data is inactive
■ Node level protection may be
misplaced
The Complexity
Problems of HCI in the
Enterprise
● Complexity comes with scale and
enterprises need scale
● As Node count increases networking
becomes more complex
○ 75% of HCI network traffic is cluster related
■ Replication/erasure coding traffic
■ Cluster synchronization
● Networking becomes complex
The Integration of HCI into the
Enterprise Cloud Strategy
● Most HCI Vendors don’t support Cloud
○ Data can’t replicate to cloud via
HCI Software
■ Customer has to use third party
tool
○ VM in the Cloud
■ Customer has to manually move
VM to Cloud
■ Manually perform transformation
■ Manually start cloud instance
Solving the Cloud
Integration Problem
● For HCI Cloud Integration
○ Storage component of HCI
needs to run in the cloud
○ On cloud supported hypervisor
○ The value of cloud integration
○ Cloud storage for DR copy
○ Cloud storage for compute for
DRaaS
○ Cloud storage and compute for
cloud bursting
Solving the HCI Enterprise Performance /
Complexity / Integration Problem
● Split Architecture
○ Flash in node
○ Shared Flash / Hybrid / HDD
Centralized Storage
● Solves
○ Networking Issue
○ Performance Issue
○ Efficiency Issue
© 2017 Datrium, Inc.
© 2017 Datrium, Inc.
How
Works
© 2017 Datrium, Inc.
X86 Compute w/
SSD o NVMe
Flash
© 2017 Datrium, Inc.
Clustered Compute Power
© 2017 Datrium, Inc.
Durable Data Persisted
To Global Storage Pool
• Compressed
• Deduplicated
• Encrypted
© 2017 Datrium, Inc.
Independently Scale
Compute + Capacity
© 2017 Datrium, Inc.
What if Drives
Fails?
© 2017 Datrium, Inc.
What if a Node Fails or
Maintenance is
Required?
© 2017 Datrium, Inc.
RF3 / FTT2 w/ Erasure Coding
Ensures ALL Data remains online!
© 2017 Datrium, Inc.
Work with VMs and
Applications
Not LUNs or Volumes
© 2017 Datrium, Inc.
No Noisy Neighbors!
All Compute Nodes are
Independent and
stateless
© 2017 Datrium, Inc.
© 2017 Datrium, Inc.
Datrium End-to-End Monitoring with Analytics
Da
Capacity and Flash Resources
Headroom Available, Data Reduction
Available and Projected Stats
Completely Integrated vSphere Presence
No other UI to Learn or Access
Manage at DVX, Host, and VM levels
Summary, Real-time & Historical Views
Per Host, VM, and DVX
At a Glance Situational Knowledge
Real-time Key Performance Metrics
Event and Task Oriented
Monitor and Manage
© 2017 Datrium, Inc.
1-128 Compute
Nodes
• Up to 200 GB/s Reads
• Up to 18M IOPS
1-10 Data Nodes
• Up to 1+ PB Capacity
• Up to 16 GB/s Writes
• Up to 1.2M Snapshots
Inspired by post-2010 Hyperscalers:
AWS, Google, Facebook.
Datrium Open ConvergedDa
© 2017 Datrium, Inc.
© 2017 Datrium, Inc.
Blanket EncryptionDa
Host
In-Use
Network
In-Flight
Data
At-Rest
Industry Unique End-to-end
protection
• Encrypted across host-network-storage
• AES-XTS-256 algorithm, 512-bit keys
With full data reduction capabilities
• Compressed, deduped before encryption
Simple, quick deployment
• No hardware dependencies
• Built-in key manager
High Performance
• Scales with compute nodes
• Leverages x86 AES-NI acceleration
buffer
Economics AND Security Built-In
It’s Easy As
Black and White
The Final Product
You Have:
ESX Hosts
Any x86 Server
Blades / Rack
You Add:
Flash at
Commodity
Pricing
We Bring:
Durable Capacity
2U Data Backup
We Load:
Datrium DVX
Controllers on each
ESX Host to drive
performance
Thank you!
Storage Switzerland
http://www.storageswiss.com
georgeacrump@storageswiss.com
StorageSwiss on Twitter:
http://twitter.com/storageswiss
StorageSwiss on YouTube:
http://www.youtube.com/user/storageswiss
Datrium
https://www.datrium.com
Datrium on Twitter:
https://twitter.com/datrium
Datrium on LinkedIN:
https://www.linkedin.com/company/datrium
Considering Hyperconverged for Your Enterprise?
For complete Audio and Q&A please register for the On Demand Version at:
http://bit.ly/HyperConv3

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Webinar: Considering Hyperconverged for Your Enterprise? 3 Key Questions to Ask

  • 1. Three Critical Questions to Ask: ● What complexities will HCI introduce into the environment? ● Will HCI extend your on-premises data center to the cloud? ● Will the HCI scale to meet the organization’s performance demands? Considering Hyperconverged for Your Enterprise? Webinar For audio playback and Q&A go to: http://bit.ly/HyperConv3
  • 2. Our Speakers Clint Wyckoff is the Senior Solutions Engineer at Datrium and has over a decade of real-world enterprise data center architecture experience. He places a large emphasis on helping IT Professionals solve the issues they're challenged with daily. Clint is an energetic and engaging speaker, blogger and author that has been recognized in the community for significant contributions. He is a 2x Microsoft Most Valuable Professional (MVP) for Cloud and Data Center Management, a VMware vExpert for 2015, 2016 & 2017, Cisco Champion and an inaugural MODE charter member. Clint is also a certified AWS Solutions Architect. George Crump is the founder of Storage Switzerland, the leading storage analyst focused on the subjects of big data, solid state storage, virtualization, cloud computing and data protection. He is widely recognized for his articles, white papers, and videos on such current approaches as all-flash arrays, deduplication, SSDs, software-defined storage, backup appliances, and storage networking. He has over 25 years of experience designing storage solutions for data centers across the US.
  • 3. Level Set: The What and Why of Hyperconverged Infrastructure ● Single Node with Compute, Storage ● Focus in on simplifying a dynamic, sprawling data center ● Auto-scales as nodes are added to HCI cluster
  • 4. The Challenges of HCI in the Enterprise ● As nodes are added complexity increases and efficiency declines ● Problem is that each node includes compute, storage and network ● Specifically Storage ○ Each node has to deliver high performance ○ AND long term data retention ● Expansion is inefficient ○ Most data centers scale one of the three vectors ■ Storage performance ■ Storage capacity ■ Application compute performance
  • 5. Understanding the Typical HCI Storage Architectures ● Each node is self-contained storage asset then replicated to another node for availability and data protection ○ Networking less of an issue ○ Limited to storage performance of single node ○ VM mobility limited to other nodes with replica ● Data is striped across nodes ○ Networking is major issue ○ Metadata/Cluster management is more complex ○ Performance is impacted because data must be accessed across the network
  • 6. The Performance Problems of HCI in the Enterprise ● Compute is overworked ○ Drives applications performance ○ Drives storage software ○ Drives cluster management (which is often complex) ● Leads to ○ Inconsistent performance ○ Concerns about noisy neighbors ○ Concerns about network performance
  • 7. HCI Performance Workarounds ● All-Flash NDI ○ Expensive ■ HCI storage also has retention responsibilities ■ HCI storage also has protection responsibilities ● 3X increase in consumption with replication ○ Overkill ■ Most applications don’t need it ■ 80% of data is inactive ■ Node level protection may be misplaced
  • 8. The Complexity Problems of HCI in the Enterprise ● Complexity comes with scale and enterprises need scale ● As Node count increases networking becomes more complex ○ 75% of HCI network traffic is cluster related ■ Replication/erasure coding traffic ■ Cluster synchronization ● Networking becomes complex
  • 9. The Integration of HCI into the Enterprise Cloud Strategy ● Most HCI Vendors don’t support Cloud ○ Data can’t replicate to cloud via HCI Software ■ Customer has to use third party tool ○ VM in the Cloud ■ Customer has to manually move VM to Cloud ■ Manually perform transformation ■ Manually start cloud instance
  • 10. Solving the Cloud Integration Problem ● For HCI Cloud Integration ○ Storage component of HCI needs to run in the cloud ○ On cloud supported hypervisor ○ The value of cloud integration ○ Cloud storage for DR copy ○ Cloud storage for compute for DRaaS ○ Cloud storage and compute for cloud bursting
  • 11. Solving the HCI Enterprise Performance / Complexity / Integration Problem ● Split Architecture ○ Flash in node ○ Shared Flash / Hybrid / HDD Centralized Storage ● Solves ○ Networking Issue ○ Performance Issue ○ Efficiency Issue
  • 13. © 2017 Datrium, Inc. How Works
  • 14. © 2017 Datrium, Inc. X86 Compute w/ SSD o NVMe Flash
  • 15. © 2017 Datrium, Inc. Clustered Compute Power
  • 16. © 2017 Datrium, Inc. Durable Data Persisted To Global Storage Pool • Compressed • Deduplicated • Encrypted
  • 17. © 2017 Datrium, Inc. Independently Scale Compute + Capacity
  • 18. © 2017 Datrium, Inc. What if Drives Fails?
  • 19. © 2017 Datrium, Inc. What if a Node Fails or Maintenance is Required?
  • 20. © 2017 Datrium, Inc. RF3 / FTT2 w/ Erasure Coding Ensures ALL Data remains online!
  • 21. © 2017 Datrium, Inc. Work with VMs and Applications Not LUNs or Volumes
  • 22. © 2017 Datrium, Inc. No Noisy Neighbors! All Compute Nodes are Independent and stateless
  • 24. © 2017 Datrium, Inc. Datrium End-to-End Monitoring with Analytics Da Capacity and Flash Resources Headroom Available, Data Reduction Available and Projected Stats Completely Integrated vSphere Presence No other UI to Learn or Access Manage at DVX, Host, and VM levels Summary, Real-time & Historical Views Per Host, VM, and DVX At a Glance Situational Knowledge Real-time Key Performance Metrics Event and Task Oriented Monitor and Manage
  • 25. © 2017 Datrium, Inc. 1-128 Compute Nodes • Up to 200 GB/s Reads • Up to 18M IOPS 1-10 Data Nodes • Up to 1+ PB Capacity • Up to 16 GB/s Writes • Up to 1.2M Snapshots Inspired by post-2010 Hyperscalers: AWS, Google, Facebook. Datrium Open ConvergedDa
  • 27. © 2017 Datrium, Inc. Blanket EncryptionDa Host In-Use Network In-Flight Data At-Rest Industry Unique End-to-end protection • Encrypted across host-network-storage • AES-XTS-256 algorithm, 512-bit keys With full data reduction capabilities • Compressed, deduped before encryption Simple, quick deployment • No hardware dependencies • Built-in key manager High Performance • Scales with compute nodes • Leverages x86 AES-NI acceleration buffer Economics AND Security Built-In
  • 28. It’s Easy As Black and White The Final Product You Have: ESX Hosts Any x86 Server Blades / Rack You Add: Flash at Commodity Pricing We Bring: Durable Capacity 2U Data Backup We Load: Datrium DVX Controllers on each ESX Host to drive performance
  • 29. Thank you! Storage Switzerland http://www.storageswiss.com georgeacrump@storageswiss.com StorageSwiss on Twitter: http://twitter.com/storageswiss StorageSwiss on YouTube: http://www.youtube.com/user/storageswiss Datrium https://www.datrium.com Datrium on Twitter: https://twitter.com/datrium Datrium on LinkedIN: https://www.linkedin.com/company/datrium
  • 30. Considering Hyperconverged for Your Enterprise? For complete Audio and Q&A please register for the On Demand Version at: http://bit.ly/HyperConv3