Toronto VMUG - November 13, 2013 - CiRBA

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Toronto VMware User Group (VMUG) Meeting on November 13, 2013 at the Metro Toronto Convention Centre.

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Toronto VMUG - November 13, 2013 - CiRBA

  1. 1. 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
  2. 2. Evolving Virtual / Cloud Management Stack Capacity Issues Low Density Little or No Automation Administration & Monitoring 3 vCOPS / vCenter App App App SCOM App App RHEV-M App App App HMC App App Virtualization VMware Hyper-V KVM 2 AIX Hypervisor Specific Admin Lock-in Avoidance Compute Infrastructure Storage Network www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved 1 Resource Convergence
  3. 3. Gaining Control and Moving to Cloud Models 5 Self Service Administration & Monitoring 4 Automated Capacity Control Analytics “Where, When & How Much” 3 vCOPS / vCenter App App App SCOM App App RHEV-M App App App HMC App App Virtualization VMware Hyper-V Compute Infrastructure Network Storage www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved KVM 2 PowerVM 1 Empower End Users Gain Control of Supply & Demand Hypervisor Specific Admin Lock-in Avoidance Resource Convergence
  4. 4. Automated Capacity Control Software Intelligently places workloads and allocates resources to eliminate capacity issues and lower infrastructure costs Demand www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved Supply
  5. 5. Stakeholder Value IT Executive Architect / Engineer Reduce Hardware & Software Licensing Costs by 40-70% Provides an Automated and Safe Placement Engine Eliminate Capacity Issues & Increase Automation Operations Capacity / Demand Managers Transformation Managers Enable Enterprise-Wide Routing, Reservations & Forecasting Employ Factory-like Migrations With Speed, Consistency & Accuracy www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
  6. 6. Properly Managing Density High Cost Risk Critical Production Workloads Non-Critical Production Workloads Density is Governed by Operational Policy Batch & Dev/Test Workloads Low Low High Density (Consolidation Ratio) www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
  7. 7. Policy-Based Management Production Production Production Production Critical IT Cloud 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+1 N/A N/A N/A N/A Compliance Rigorous Rigorous Medium None None Volatility Low Med High High Med High Operational Cycles Business Business Defined Defined IT Defined Unbound Unbound Windowed Simulated None Automation Approval Approval Based Based Semi-Auto Semi Auto Fully Auto Process Defined Developer Defined www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved Multi-Tenant Low to None
  8. 8. Impact: Software License Control Optimal placements are key to savings with per host licensing models Windows VMs Linux VMs Average Savings of 55% Virtual/Cloud Infrastructure License Containment www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved Defrag License Sprawl
  9. 9. Policy-Based Visualization Risks Inefficiencies Clusters Policy-Based “Goal Posts” Hosts Guests www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
  10. 10. How It Works Rapidly move to new technologies and platforms Control Policies Route new workloads to the right capacity and reserve space ahead of time Optimal Placements & Allocations Technical Analysis Business Analysis Actively balance supply and demand and accurately forecast capacity Utilization Analysis Automation www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
  11. 11. Rethinking Self Service Definition: Giving end users the ability to request capacity through a request portal/system, and immediately provisioning that capacity for them intelligently Ad-Hoc Use Road Trip = On-Demand Use www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved Enterprise Use Business Trip = Book Ahead
  12. 12. Optimizing Cloud Operational Models Request Console Enterprise Workloads Control Console Workload Routing API Ad-Hoc Self-Service Reservation Console Placement Analytics ? Provisioning Process Internal Cloud Infrastructure Create Start/Stop Destroy Intelligent Initial Placement Operational Metrics VMM Automated Rebalancing & Resizing VMM Intelligently Place VMs & Allocate Resources www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved Optimize Density & Minimize Operational Risk Scientifically Manage Enterprise Demand
  13. 13. Hotels.com for IT Timeline of inbound demands View of “booking requests” feeding in from release management, migration projects, cloud requests, etc. Demand Automatic evaluation of hosting options www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved Most suitable environments scored by Fit for Purpose, Cost, and Available Space Supply
  14. 14. 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
  15. 15. 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 ) www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved
  16. 16. Questions? www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved (we’re hiring…)

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