The Modern Data Center Topology

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The Modern Data Center TopologyThe 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

Higher Education
Oil Gas
Media House
Financial Services
Telecom
Power Utility
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Todays 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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Todays High Availability Data Center
Extreme Redundancies for 99.99 Uptime -gt Higher
Power Consumption
Huge Population of N1/N2 Equipment -gt Asset
Under utilization Too complex to manage
with spreadsheets Visio tools
Chain of inter-dependent equipment -gt Multiple
points of failures
KW per Rack increases as more processing
capacity is added -gt Trade-offs need to support
more per rack versus extra space heat loads.
Growing Heat Loads, Carbon Emissions e-waste -gt
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
wouldnt be surprised if these popular services
started looking at other options, including
Rackspace, SoftLayer, Microsofts Azure, and
Googles just-introduced Compute Engine. Some of
Amazons biggest EC2 outages occurred in April
and August of last year.
Which Will Be The Next One?
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Whats 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 N1)
• 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 -gt Rack -gt 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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Operating Challenges
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The High Availability Challenge

• Asset Over Provisioning

• Lack of HA Management Tool

• 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

• 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 theres fatal human error
• Health and history of equipment, or previous MAC
  impact, not tracked

Need to Predict Failures
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Beyond HA Infrastructure Operational Challenges

• Energy Problems

• Operational Problems

• 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

• 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

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A Solution
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Solution That Bridges the Gap Between IT
Facilities
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 theres 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

DCIM Helps to Predict Failures
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Solution That Addresses Infra Operational
Challenges

• Energy Problems

• Operational Problems

• 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

• 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

DCIM Improves Energy Operational Efficiencies
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Anatomy of a DCIM Software GFS Crane
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Thank Youhttp//www.greenfieldsoft.comEmail
sales_at_greenfieldsoft.com
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See alsoData Center Infrastructure Management
ERP for the Data Center Manager