toronto vmug - november 13, 2013 - cirba

www.cirba.com Copyright ©2012 CiRBA Inc. All Rights Reserved

Automated Capacity Control Actively Balancing Infrastructure Supply & Demand

Andy Walton

Director, Technical Sales

www.cirba.com

@ajwCiRBA

http://www.cirba.com/


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


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

http://www.google.ca/url?sa=i&rct=j&q=openstack+logo&source=images&cd=&cad=rja&docid=MNsOqARY4afajM&tbnid=s7KAugSB1vvgcM:&ved=0CAUQjRw&url=http://www.yoyoclouds.com/p/blog-page_11.html&ei=YTqBUf3AM-nR2wWXhIGIDA&bvm=bv.45921128,d.aWc&psig=AFQjCNGdfWsnmAyZxM6b7uVvQ5W_4qVN4g&ust=1367509969785420


Automated Capacity Control Software

Intelligently places workloads and allocates

resources to eliminate capacity issues and

lower infrastructure costs

Demand Supply


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


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


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


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%


Policy-Based Visualization

Clusters

Hosts

Guests

Policy-Based

“Goal Posts”

Risks Inefficiencies


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


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


?

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


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


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


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 )


Questions? (we’re hiring…)

toronto vmug - november 13, 2013 - cirba

Technology