PLANNING FOR
CONVERGED
INFRASTRUCTURE
Performance, Capacity and Management
Peter Dyer – Product Manager
www.uptimesoftware.com
Why am I here?
• Alex couldn’t be here
• Building software for the datacenter for more than 15
years
• Focused on virtualization for the past 8 years
• Worked on a tool called PlateSpin Recon – one of the first
virtualization consolidation/capacity planning tools
• Working with up.time customers to define the future of
our product, including addressing management and
capacity planning challenges in the modern datacenter
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Definition –
Converged Infrastructure
Grouping of multiple components: server (compute), storage,
networking and management software in a single, optimized
computing package
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Two approaches
Integrated Systems
Fabic Based (Hyperconverged)
(older, scale up)
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(newer, scale out)
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Subcategories (Gartner) –
Integrated Systems (Converged Infrastructure)
• Integrated stack systems (ISS) – server, storage and
network with application software
– Simplified: really big server (one application)
• Integrated infrastructure systems (IIS) – server, storage
and network to provide compute infrastructure
– Simplified: private cloud
• Fabric-based computing (FBC) – server, storage and
network together in an integrated system designed to be
building blocks
– Simplified: private cloud building blocks
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Integrated stack systems (ISS)
Examples: Oracle Exadata, IBM PureApplication, Teradata
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Integrated infrastructure systems (IIS)
Examples: VCE Vblock (VMware, Cisco, EMC), HP
ConvergedSystem, IBM PureFlex, Cisco-NetApp FlexPod
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Fabric-based computing (FBC) /
Hyperconverged Infrastructure
Examples: SimpliVity, Nutanix, HP Moonshot
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Demand and Supply
Integrated Systems
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Fabric-based
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Under the covers
• Integrated systems
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Existing technology
Reference architecture
Pre-configured
Tested
• Fabric-based
– New technology
– Existing parts
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The History of Fabric-based
Converged Infrastructure
Google
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Key use cases
• Private cloud
• Virtual desktops
• Applications
– Traditional data driven: Oracle, SAP, etc
– Big data: Hadoop, etc
• Greenfield
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Business Drivers
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Improved performance
Lower operating costs
Simplified support
Faster deployment
Simplified sourcing
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Market
• Gartner estimates
– Converged infrastructure (Integrated systems)
• 2014: $6B
• 2014: 50% growth rate
– Total hardware market: $80B
• MarketsandMarkets
– Converged Infrastructure
• $33.89B by 2019
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Systems Management
• Good news
– Workloads are not changing
• Operating systems and applications just see (virtual) hardware
– Hypervisor is not changing
• But there are more (new) parts
• Bad news
– Hardware is changing, and access to physical hardware is changing
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Not isolated
Converged infrastructure
Private cloud
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Software-defined
data center
Not isolated
Converged infrastructure
Private cloud
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Software-defined
data center
Software-Defined Data Center
Storage
• VMware
– vSANs
– vVols
• Microsoft
– Storage spaces
• EMC
– ScaleIO
Networking
• VMware
– NSX
• Microsoft
– Hyper-V Network
Virtualization (HNV)
• Cisco
– Extensible Network
Controller (XNC)
• VMware
– EVO (Rail & Rack)
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Software-Defined Storage (SDS)
• Pool of disks treated as one disk resource
– Local disk
• VMware vSAN
• Microsoft Storage Spaces
• Fabric-based (Hyperconverged) solutions
– External disk (NAS, JBOD, etc)
• VMware vVols
• Goals
– Lower costs
– Easier to scale
– Easy management (eliminates hardware RAID and proprietary SAN
operating systems)
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Storage is evolving (sort of)
• Capacity is ever increasing, IOPS sort of
• IOPS is king (or at least very important)
– Mixing of different types of storage – fast tier
– Dynamic tiering
– Caching
• Replication
– Data protection
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Software-Defined Networking (SDN)
• Moving switch management from the physical port to
software that follows the VM (workload)
• Goals
– Lower costs
– Easy management
– Better security (egg)
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The Software-Defined Challenge
• Who knows the truth
– It used to be the operating system – it isn’t any more
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The Old Days
Application
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The Old Days (monitored)
Application
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…along comes SAN
Application
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…then comes virtualization
Application
VM
VM
VM
Hypervisor
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VM
VM
…software-defined data center
SDN
Application
VM
VM
VM
Hypervisor
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VM
VM
SDS
…Public Cloud
SDN
Application
VM
VM
VM
Hypervisor
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VM
VM
VM
SDS
…monitoring
SDN
Application
VM
VM
VM
Hypervisor
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VM
VM
VM
SDS
The New Way Tradeoff
• Good
– Time to provision new systems (agility) – decreased dramatically
– Cost per system – decreased dramatically
• Bad
– Cost to manage new systems – increased dramatically
– Number of systems – increased dramatically
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Not isolated
Converged infrastructure
Private cloud
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Software-defined
data center
Private Cloud Defined
• Shared pool of computing resources inside a corporate
firewall
• Characteristics
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Easy, fast provisioning / access to resources
Used by many departments / groups
Used for a wide variety of use cases
Buzz words: agile, automated
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Cloud Capacity Challenge
• Are people using the resources they have requested?
– Generally, no they are not
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Strategies to address challenge
• Show costs upfront at time of provisioned
• Chargeback
– Show-back
• Shame-back
• Lease only (must be renewed)
• Overprovision
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Not isolated
Converged infrastructure
Private cloud
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Software-defined
data center
Capacity Planning Challenge
• Limited ability to isolate capacity and performance to
discrete elements
– CPU, memory, disk (fast and slow) purchased together
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vBlock example
(small and simple)
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Related challenge
• Fast and slow disk
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vBlock example
(small and simple)
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Nutanix
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Simplivity Omnicube
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WRAP UP
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Questions
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What type of converged infrastructure is being deployed?
What is it being used for?
How easy is it to add capacity?
How much capacity must be purchased?
– How much lead time is required?
• Can capacity be optimized across compute and storage?
• What is the maximum workload size that needs to be
supported?
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Takeaways
• Converged Infrastructure doesn’t exist in isolation –
– Software-defined data center
– Use case (ie Private Cloud, VDI, etc)
• Software-defined data center introduces “source of truth”
management challenge
• Private Cloud introduces capacity challenges
• Converged Infrastructure introduces capacity challenges
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Map Dashboard
Capacity Dashboard
Topology Dashboard
Thank you.
peter.dyer@uptimesoftware.com
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