toronto vmug - november 13, 2013 - cirba
DESCRIPTION
Toronto VMware User Group (VMUG) Meeting on November 13, 2013 at the Metro Toronto Convention Centre.TRANSCRIPT
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Automated Capacity Control Actively Balancing Infrastructure Supply & Demand
Andy Walton
Director, Technical Sales
www.cirba.com
@ajwCiRBA
www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
Evolving Virtual / Cloud Management Stack
Compute
Storage
Network
Infrastructure Resource
Convergence
1
vCOPS / vCenter Administration
& Monitoring RHEV-M SCOM HMC
Hypervisor
Specific Admin
3
Virtualization
KVM
App App
AIX
App App App
VMware
App App App
Hyper-V
App App Lock-in
Avoidance
2
Capacity Issues
Low Density
Little or No Automation
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Gaining Control and Moving to Cloud Models
Compute
Storage
Network Infrastructure
vCOPS / vCenter Administration
& Monitoring RHEV-M
Virtualization
KVM
App App
PowerVM
App App App
VMware
App App App
Hyper-V
App App
SCOM HMC
Resource
Convergence
1
Hypervisor
Specific Admin
3
Lock-in
Avoidance
2
Analytics Automated Capacity Control “Where, When & How Much”
Gain Control of
Supply & Demand
4
Self Service Empower
End Users
5
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Automated Capacity Control Software
Intelligently places workloads and allocates
resources to eliminate capacity issues and
lower infrastructure costs
Demand Supply
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Stakeholder Value
Provides an Automated and Safe Placement Engine
Architect / Engineer
Reduce Hardware & Software Licensing
Costs by 40-70% IT Executive
Eliminate Capacity Issues & Increase Automation
Operations
Enable Enterprise-Wide Routing, Reservations & Forecasting Capacity / Demand
Managers
Employ Factory-like Migrations With Speed, Consistency & Accuracy Transformation
Managers
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Density (Consolidation Ratio)
Low High
Low
High
Critical
Production
Workloads Non-Critical
Production
Workloads Batch &
Dev/Test
Workloads
Cost Risk
Properly Managing Density
Density is
Governed by
Operational
Policy
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Policy-Based Management
Production
Critical
Production
IT
Production
Cloud
Production
Batch/HPC Pre-Prod Dev/Test
Density
Performance
Availability
Compliance
Volatility
Operational
Cycles
Automation
N+1 N/A
Rigorous Low to None
Low High
Business
Defined Unbound
Approval
Based Fully Auto
Production
Critical
Production
IT
Production
Cloud
Production
Batch/HPC Pre-Prod Dev/Test
Density Low Med Med Low Med High
Performance High Med Med Very High Med Low
Availability N+2 N+1 N+1 N/A N/A N/A
Compliance Rigorous Medium Multi-Tenant Low to None None None
Volatility Low Med High High Med High
Operational
Cycles
Business
Defined IT Defined Unbound Windowed Simulated None
Automation Approval
Based Semi-Auto Semi Auto Fully Auto
Process
Defined
Developer
Defined
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Optimal placements are key to savings with
per host licensing models
Virtual/Cloud Infrastructure
Impact: Software License Control
License
Containment
Windows VMs Linux VMs
License
Sprawl Defrag
Average Savings of 55%
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Policy-Based Visualization
Clusters
Hosts
Guests
Policy-Based
“Goal Posts”
Risks Inefficiencies
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Optimal
Placements &
Allocations
How It Works
Rapidly move to new technologies
and platforms
Route new workloads to the
right capacity and reserve space ahead
of time
Actively balance supply and demand
and accurately forecast capacity
Automation
Control
Policies
Technical
Analysis
Business
Analysis
Utilization
Analysis
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Rethinking Self Service
Definition: Giving end users the ability to request
capacity through a request portal/system, and
immediately provisioning that capacity for them
immediately
Road Trip = On-Demand Use
Ad-Hoc Use Enterprise Use
Business Trip = Book Ahead
intelligently
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?
VMM
VMM
Provisioning
Process
Optimizing Cloud Operational Models
Control
Console
Workload
Routing API
Placement
Analytics
Request
Console
Internal Cloud
Infrastructure
Optimize Density &
Minimize Operational Risk Intelligently Place VMs
& Allocate Resources
Operational
Metrics
Create
Start/Stop
Destroy
Automated
Rebalancing
& Resizing
Intelligent
Initial
Placement
Reservation
Console Ad-Hoc
Self-Service
Enterprise
Workloads
Scientifically Manage
Enterprise Demand
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Demand Supply
Timeline of
inbound
demands
View of “booking requests” feeding in
from release management, migration
projects, cloud requests, etc.
Automatic evaluation of hosting options
Most suitable environments
scored by Fit for Purpose,
Cost, and Available Space
Hotels.com for IT
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What This All Means…
One model of all global hosting capacity
– Virtual or cloud (or even external)
Scientific means to align Supply and Demand
– Environment-level routing of inbound demands
– Host-level placement, rebalancing, resizing
– Cloud stack integration (Ad-Hoc Self-Service)
– Capacity Reservations (Enterprise Self-Service)
Opportunity for significant financial savings
– Increased VM density = H/W purchase avoidance
– Software density = license savings
– Reduced capacity risk = cloud success
www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
CiRBA & VMware
1. All CiRBA customers have VMware ELA’s
2. Complementary Solutions:
– API Integrations
– Data comes directly from VMware
– Actions sent directly to VMware
– Designed to work with:
• vCOPS
• DRS
• vCAC
(Also true of HyperV, RHEV & POWERvm )
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Questions? (we’re hiring…)