Lecture Two - System Availability

Question 1

Information Technology (IT):

Answer 1

Encompasses technologies related to storage, retrieval, manipulation, and communication of information.
Includes computers, networks, phones, and fax machines.

Question 2

Infrastructure Definition:

Answer 2

The underlying framework or features of a system or organization.
Fundamental facilities and systems serving a country, city, or area, such as transportation and communication systems.

Question 3

Benefits of IT Infrastructure

Answer 3

Commonly Accepted Benefits:
Automates manual activities.
Handles increased volumes of data efficiently.
Extends the range of tasks that can be performed.
Enhances customer service quality.
Increases the quality of finished products.
Improves information sharing and manipulation capabilities.

Question 4

Components of IT Infrastructure - Elements of IT Infrastructure

Answer 4

Business Process: Operations that support business goals.
Information and Data: Key resources for decision-making.
Applications and Servers: Software and hardware systems.
Buildings and Electricity Providers: Physical and power resources.
Hardware and Software: Essential computing equipment and programs.
Data & Storage: Systems for data management and retention.
Network Services: Connectivity and communication services.

Question 5

IT System Model - System Layers

Answer 5

Process/Information: Core business processes and data handling.
Applications: Software tools and systems.
Application Integration: Ensures seamless operation and data flow.
Infrastructure: Physical and virtual resources.

Question 6

IT System Model - Considerations

Answer 6

Availability: System uptime and reliability.
Performance: Efficiency and speed of operations.
Security: Protection against threats and vulnerabilities.
End User Devices: Interfaces for user interaction.
Operating Systems, Servers, Networks, Virtualisation, Data Centres: Core components for IT operation.

Question 7

System Availability -

Answer 7

Availability%=( MeasuredTimePeriod/Uptime
)×100

Question 8

System Availability and SLAs - Common Availability Levels

Answer 8

99.0%, 99.9%, 99.95% typically specified in SLAs.
99.999% known as carrier-grade availability.

Question 9

System Availability and SLAs - Downtime Estimates

Answer 9

99.8%: 17.5 hours/year, 86.2 minutes/month, 20.2 minutes/week.
99.9%: 8.8 hours/year, 43.2 minutes/month, 10.1 minutes/week.
99.99%: 52.6 minutes/year, 4.3 minutes/month, 1.0 minute/week.
99.999%: 5.3 minutes/year, 25.9 seconds/month, 6.1 seconds/week.

Question 10

Unavailability Intervals - Definition

Answer 10

Used in conjunction with availability percentage to define acceptable downtime.
Example for 99.9% Availability:
525 minutes of downtime/year should not occur as a single event.
Downtime can be spread across many short events.

Question 11

Unavailability Intervals - Interval Specifications

Answer 11

0 - 5 minutes: ≤ 35 times/year
5 - 10 minutes: ≤ 10 times/year
10 - 20 minutes: ≤ 5 times/year
20 - 30 minutes: ≤ 2 times/year
> 30 minutes: ≤ 1 time/year

Question 12

Estimating System Availability - SLAs

Answer 12

Provide upfront availability guarantees; actual availability is computed afterward.

Question 13

Estimating System Availability - Estimation Factors

Answer 13

Mean Time to Repair (MTTR): Average time to repair/recover failed components.
Mean Time Between Failures (MTBF): Average time between failures.

Question 14

Estimating System Availability - Timeline

Answer 14

Failure: Time when a system component fails.
Recovery: Time taken to repair the system.
MTTR and MTBF: Key metrics for assessing system reliability.

Question 15

Estimating Availability with MTBF and MTTR

Answer 15

EstimatedAvailability%=(
MTBF/(MTBF+MTTR))×100

Question 16

Observed Availability and Failures

Answer 16

Failure Probability: Changes over time, typically following a bathtub curve.
Failure Phases:
Early Failures: Initial phase with higher failure rates.
Random Failures: Stable phase with constant failure rate.
Wear-Out Failures: Increased failures as components age.
Observed Availability: Influenced by component reliability and failure rates.

Question 17

Multi-Component Availability

Answer 17

Comprise multiple components, each with its availability.
A (system) = A1 x A2 x A3… where A1, A2, A3… are the availabilities of the individual components.

Question 18

System Availability and Components - Graphical Representation

Answer 18

System availability decreases as the number of components increases.
Visualizes availability for different component reliability (99%, 95%, 90%).

Question 19

System Availability with Multiple Components - Insight

Answer 19

Increasing the number of components increases the likelihood of system failures.

Question 20

Redundancy in IT Systems - Purpose

Answer 20

Improves system availability and robustness by duplicating components/functions.
Acts as a backup to mitigate failures.

Question 21

Redundancy in IT Systems - Cost Implications

Answer 21

Pros: Enhances reliability and reduces downtime.
Cons: Increases overall system cost.

Question 22

Parallel System Availability

Answer 22

Availability improves as the number of systems/components in parallel increases.
Formula -
A (Parrallel) = 1 - (1-A)^m
A is the availability of a single system/component, m is the number in parallel.

Question 23

Business Continuity

Answer 23

Disaster Events: Potential incidents like fires, natural disasters, or social unrest.
Preparedness: Businesses must prepare for contingencies to ensure continuity.
Disaster Recovery Plan (DRP):
Outlines procedures to protect and recover IT infrastructure.
Ensures minimal disruption and swift recovery from incidents.

Question 24

Business Continuity Concepts

Answer 24

Downtime and Data Loss Metrics:
Recovery Time Objective (RTO):
Time needed to restore a business process.
Indicates the maximum allowable downtime.
Recovery Point Objective (RPO):
Data freshness required for recovery.
Commonly set at 24 hours, dictating data lost between last backup and incident.

Question 25

Trends in IT Infrastructure

Answer 25

Emerging Trends:
Cloud Computing
Bring Your Own Device (BYOD)
Green IT
Big Data Analytics

Question 26

Cloud Computing

Answer 26

Paradigm Shift: Enabled by virtualization technologies.
Shared Resources: Applications utilize resources from a virtualized pool.
On-Demand: Resources scale up/down based on demand.
Deployment Models:
Public Cloud: Available to the general public.
Private Cloud: Dedicated to a single organization, managed internally or by a third party.
Hybrid Cloud: Combines public and private models.

Question 27

Cloud Computing Service Models

Answer 27

Service Models:
Software-as-a-Service (SaaS): Provides software applications over the internet.
Platform-as-a-Service (PaaS): Offers hardware and software tools over the internet.
Infrastructure-as-a-Service (IaaS): Delivers computing infrastructure over the internet.
Future Lecture Topic: Further details on Cloud Computing to be covered later.

Question 28

Bring Your Own Device (BYOD) - Trend Description

Answer 28

Employees using personal devices (smartphones, tablets, laptops) for work.
Access organizational applications and data for information processing and communication.

Question 29

Benefits of Bring Your Own Device (BYOD)

Answer 29

No commitment to maintaining devices.
Low capital expenditure.
Agile decision-making and minimal operational expenditure.
Familiarity increases efficiency and productivity.
Potential cost savings from using employee contracts.

Question 30

Risks of Bring Your Own Device (BYOD)

Answer 30

Security and Management Risks:
Multiple devices not fully controlled by system managers.
Data privacy and confidentiality concerns.
Potential malware carriers from external networks.
Ownership Concerns:
Employee-owned phone numbers might be dialled by business contacts.

Question 31

Green IT

Answer 31

Environmental Goal: Reduce the environmental impact of IT infrastructures.
Strategies:
Reduce electricity usage and CO2 emissions.
Use greener equipment and increase efficiency.
Examples:
Flash disks instead of rotating disks.
Blade servers sharing power supplies to reduce consumption.

Question 32

Power Usage Effectiveness (PUE)

Answer 32

Efficiency Metric:
Measures the energy efficiency of a data centre.
PUE= ITEquipmentEnergy/TotalFacility Energy

Question 33

Power Usage Effectiveness (PUE) - Interpretation

Answer 33

PUE of 2.0 indicates that for every watt of IT power, an additional watt is used for cooling and distribution.
PUE closer to 1.0 indicates higher efficiency, with more energy used for computing.

Question 34

Big Data Analytics - Data Generation

Answer 34

Generated by ubiquitous sensors, mobile telephony, surveillance cameras, RFID tags, and social networks.

Question 35

Big Data Analytics - Data Characteristics

Answer 35

Raw data is often unstructured.
Investments focus on managing and maintaining large datasets.

Question 36

Big Data Analytics

Answer 36

Analyzing large datasets to discover meaningful patterns, trends, and associations.
Enhances decision-making and strategic planning.