The Modern Data Center Topology

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The Modern Data Center
Topology:
The High Availability Mantra

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GreenField Software
• Company
– GreenField Software is a privately held, early stage Indian (Kolkata-based)
software company looking to be a globally recognized player in Cloud-based
Intelligent Infrastructure Management
• Mission
– GFS delivers pioneering Cloud-based Intelligent Infrastructure Management
solutions to improve operational and energy efficiencies, safety and
environmental conditions of facilities with critical infrastructure.
• Vision
– Our Cloud-based Intelligent Infrastructure Management solutions help our
customers to
• Optimize capex, reduce operating costs and mitigate risks of critical infrastructure
failures
• Improve Sustainability through improved energy management and safety of their
employees and other stakeholders using the facilities

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Partners & Customers
Oil &Gas
Media House
Telecom
Higher Education
Financial Services
Power Utility

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Today’s Topics
• The Modern Data Center Overview
• The High Availability (HA) Mantra
• Operating Challenges
• A Solution

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Modern Data Center
Overview

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Multiple Classes of Data Centers
• Internet Data Center
 used by external clients connecting from the Internet
 supports servers and devices required for B2C transaction-based applications (e-commerce).
• Extranet Data Center
 provides support and services for external B2B partner transactions.
 accessed over secure VPN connections or private WAN links between the partner
network and the enterprise extranet.
• Intranet Data Center
 hosts applications and services mostly accessed by internal employees with
connectivity to the internal enterprise network.
ness services.
• Special Purpose Data Center
 For specialized application areas like Geological & Geophysical for Oil & Gas
Industry
May or may not be inter-connected

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Common Objective: Business Continuity
• Disaster Recovery Data Center
 Each Class may have dedicated or Shared DR Center
 Usually located separately from Primary Data Center
• High Availability (HA) Data Center
 Each Data Center provided for with significant redundancies
 DR Center comes into play only when a Disaster strikes.
 Component or system failures within any DC should be either self-healing or
redundancies within the DC should take over
• Insurance Against Power & Network Outages
 Reliability through multiple service providers
 Internal Back-ups
ness services.
• Securing the Data Center
 Against malicious hacking that can bring down the Data Center impacting
business continuity
 Implementing Firewalls/ Virtual Firewalls

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Common Complexity: Multitude of Assets
Multitude of Assets
 Divided between two
worlds: IT & Facilities
 Includes Mission
Critical Applications
 Like a manufacturing
operation
 Raw Material: Power &
Networks
 Processing: Data
 Output: Information
Service
 Needs: Asset
Management, Resource
Optimization, a la
Manufacturing

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The High Availability
Mantra

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Today’s High Availability Data Center
Extreme Redundancies for 99.99% Uptime -> Higher Power Consumption
Huge Population of N+1/N+2 Equipment -> Asset Under utilization & Too complex to
manage with spreadsheets & Visio tools
Chain of inter-dependent equipment -> Multiple points of failures
KW per Rack increases as more processing capacity is added -> Trade-offs: need to
support more per rack versus extra space & heat loads.
Growing Heat Loads, Carbon Emissions & e-waste -> Sustainability Issues
High Availability is Inversely Proportional to Asset Utilization & Energy Efficiency

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When HA fails - Tale of Two Disasters
Amazon RBS
Tech fault at RBS and Natwest freezes
millions of UK bank balances
RBS and Natwest have failed to register inbound
payments for up to three days, customers have
reported, leaving people unable to pay for bills,
travel and even food. The banks - both owned
by RBS Group - have confirmed that technical
glitches have left bank accounts displaying the
wrong balances and certain services
unavailable. There is no fix date available.
Amazon cloud outage takes down
Netflix, Instagram, Pinterest, & more
With the critical Amazon outage, which is the
second this month, we wouldn’t be surprised
if these popular services started looking at
other options, including Rackspace, SoftLayer,
Microsoft’s Azure, and Google’s just-introduced
Compute Engine. Some of
Amazon’s biggest EC2 outages occurred in
April and August of last year.
Which Will Be The Next One?

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What’s the High Availability Mantra?
Availability % Downtime per year Downtime per month* Downtime per week
99% ("two nines") 3.65 days 7.20 hours 1.68 hours
99.5% 1.83 days 3.60 hours 50.4 minutes
99.8% 17.52 hours 86.23 minutes 20.16 minutes
99.9% ("three nines") 8.76 hours 43.8 minutes 10.1 minutes
99.95% 4.38 hours 21.56 minutes 5.04 minutes
99.99% ("four nines") 52.56 minutes 4.32 minutes 1.01 minutes
99.999% ("five nines") 5.26 minutes 25.9 seconds 6.05 seconds
99.9999% ("six nines") 31.5 seconds 2.59 seconds 0.605 seconds
99.99999% ("seven nines") 3.15 seconds 0.259 seconds 0.0605 seconds
Amazon Data Centers (built to Tier 4 standards and with an expected availability of 99.995%) has had
two outages already in 2012 – each over 3 hours!
• Tier 3/Tier 4 just defined by hardware redundancies
• Glaring gaps in operating procedures to prevent fatal human errors
• Lack of purpose-built BCP software to predict failures
• Lack of chain of custody to detect root cause

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Delivering the High Availability Promise
Adequate Redundancies
• Are there any points of failure – besides power and external networks - that can impact
uptime? (Not everything is N+1)
• What are my redundancy paths?
• Are the relationships & dependencies among critical assets clearly defined?
• Can I do an impact analysis on the outage/downtime of any equipment? Can I predict
the cascading effect of such an outage on other assets/applications in the data center?
Preventing Failures
• Can any failure be predicted to take proactive measures? Do I get alerts on threshold
breaches so that I can take preventive actions before a failure happens?
• Is there a history of a Move-Add-Change (MAC) that I should be aware of?
• What is the impact of a MAC on space, power, cooling?
• Where can new devices/servers be best placed? Floor -> Rack -> Cage. How this can be
determined based on current infrastructure and other dependencies to avoid a failure?
• How do I prevent a fatal human error?

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The High Availability Challenge
Asset Over Provisioning Lack of HA Management Tool
 IT assets tracked by Systems
Management Tool
 Facilities assets tracked by BMS
 Two not inter-operable: Unable to
determine missing link for HA
 Unable to track redundancy paths
 HA fails if any equipment or
software in critical path fails
 HA fails if there’s fatal human error
 Health and history of equipment, or
previous MAC impact, not tracked
 Too many assets; two classes of assets
 Absence of Software Portfolio (even if
hardware assets are tracked)
 Move-Add-Change: Decisions not
based on simulations, analysis
 Absence of change management
 Absence of workflow approvals
 Unable to predict failures
 No chain of custody
Need to Predict Failures

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Beyond HA: Infrastructure & Operational Challenges
Energy Problems Operational Problems
 Low level asset tracking
 Under utilization of many computing
resources
 Running of old inefficient equipment
 Decisions not based on analysis
 Cooling not optimized
 Floor & Rack Space: Non-optimal
placements of equipment
 Increasing demand for rack space
 Absence of capacity planning
 Higher power consumption & growing
power bills
 Not monitoring power use at device
levels
 Dissemination of enormous heat
 Creation of hot spots
 Drastic reduction in expected life of
computing equipment
 Failing of a data center
 Increase in CO2 emission

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Solution That Bridges the Gap Between IT & Facilities
IT System
Performance
Management
Building
Management
System
Data Center
Infrastructure
Management
Data Center Infrastructure Management (DCIM) Software

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Solution That Addresses The High Availability Challenge
Asset Over Provisioning Lack of HA Management Tool
 IT assets tracked by Systems
Management Tool
 Facilities assets tracked by BMS
 Two not inter-operable: Unable to
determine missing link for HA
 Unable to track redundancy paths
 HA fails if any equipment or software
in critical path fails
 HA fails if there’s fatal human error
 Health and history of equipment, or
previous MAC impact, not tracked
 Too many assets; two classes of assets
 Absence of Software Portfolio (even if
hardware assets are tracked)
 Move-Add-Change: Decisions not
based on simulations, analysis
 Absence of change management
 Absence of workflow approvals
 Unable to predict failures
DCIM Helps to Predict Failures
 No chain of custody

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Solution That Addresses Infra & Operational Challenges
Energy Problems Operational Problems
 Low level asset tracking
 Under utilization of many computing
resources
 Running of old inefficient equipment
 Decisions not based on analysis
 Cooling not optimized
 Floor & Rack Space: Non-optimal
placements of equipment
 Increasing demand for rack space
 Absence of capacity planning
 Higher power consumption & growing
DCIM Improves Energy & Operational Efficiencies
power bills
 Not monitoring power use at device
levels
 Dissemination of enormous heat
 Creation of hot spots
 Drastic reduction in expected life of
computing equipment
 Failing of a data center
 Increase in CO2 emission

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Anatomy of a DCIM Software: GFS Crane

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Thank You
http://www.greenfieldsoft.com
Email: sales@greenfieldsoft.com

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See also:
Data Center Infrastructure
Management: ERP for the Data
Center Manager

The Modern Data Center Topology

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