The future of scaling forrester research - GigaSpaces Road Show 2011

© 2011 Forrester Research, Inc. Reproduction Prohibited2 © 2009 Forrester Research, Inc. Reproduction Prohibited

The Future Of Scalability, Performance, And Reliability

Mike Gualtieri, Senior Analyst, Architecture & Design

February, 2011

An explosion of activity and information.


Agenda

Massive scale

The seven qualities of wildly desirable applications

Massive scale solutions

Cloud ROI hinges on elasticity

Recommendations


Volume equates to transactions, services, and data

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Average daily volume of share (million)

Source: NYSE Technologies: Market Data Facts & Figures (http://www.nyxdata.com/Data-Products/Facts-and-Figures)

Average daily volume of shares (in millions) by year on the

New York Stock Exchange (NYSE)


More eCommerce means more of everything: users, transactions, and data

Yikes! This guy can persuade a million

people that my product is rubbish


They’re not just kids. Social networking use among Internet users 50 and older has nearly doubled.

Placeholder – social media influence


Your business must scale to new heights

• Corporate data warehouses• Historical market data• Structured and unstructured Web data

Huge historical data stores

• Real-time market data• Radio frequency identification (RFID), global position system (GPS)

Exponential increase in business events (data in motion)

• More channels such as eReaders & smart phones (20% of US mobile subscribers now use smart phones)

• Increased expectations for content and transactions

More users

• Business must respond faster• IT must enable continuous business change

Faster pace of change


Massive scale examples

• 145M customer• 20k transactions per second• 1B events daily.

Financial services has an enormous need for scalability, performance, and reliability.


Agenda

Massive scale

The seven qualities of wildly desirable software



Recommendations


Wildly desirable business applications must strike the right balance among these seven qualities

Quality What it means

1 ExperienceUsers’ perceptions of the usefulness, usability, and desirability of the application.

2 AvailabilityThe readiness of an application to perform its functions when needed.

3 PerformanceThe speed with which an application performs a function to meet business and user expectations.

4 ScalabilityHandle increasing or decreasing volumes of transactions, services, and data.

5 AdaptabilityThe ease with which an application can be changed or extended.

6 SecuritySupports the security properties of confidentiality, integrity, authentication, authorization, and nonrepudiation.

7 EconomyMinimize the cost to build, operate, and change and application without comprising its business value.

•Monitor application and infrastructure for expected and unexpected events that can detect or foretell an outage.

Monitored

•Mitigate the effect of known vulnerabilities by implementing redundant components and the ability to operate in a crippled mode.

Fault tolerant

•Identify and rehearse failure scenarios and put in place a support regime to quickly investigate, escalate, and resolve problems.

Fixable

Availability


What does high availability mean?

Uptime %* Downtime per year

99.999% (5 nines) 5.26 minutes

99.99% (4 nines) 52.6 minutes

99.5% 1.83 days

99% (2 nines) 3.65 days

98% 7.30 days

95% 18.25 days

*Uptime calculations assume no scheduled downtime.


Can “dial tone” reliability be achieved?

•Application response time meets or beats user expectations and business requirements.

Fast

•Application response time is consistent under normal and load conditions of increasing users, workload, and data.

Consistent

Performance


Achieving top performance is a moving target

Source: Gomez.com

20Entire contents © 2009 Forrester Research, Inc. All rights reserved.

•Application can handle an increasing volume of transactions.

•Example: mouse click to search, button on ATM machine

•Bounding: users, connections, bandwidth

Transactions

•Application can handle an increasing volume of services needed to process transactions.

•Example: business logic, calculations, integration

•Bounding: compute workload

Services

•Applications can handle an increasing volume of transient and persistent data.

•Example: customer profile, transaction history, content, and documents

•Bounding: Size and amount of data

Information

Scalability


Agenda

Massive scale




Recommendations

Legacy means you can’t just “rip and replace”.


Elastic platforms are a great answer.


Elastic application platforms are the future of scalability, performance, and reliability.

Local Cache

Distributed Cache Platform

Elastic Cache Platform

Elastic Application Platform

Memory speeds

Clustered resources

Automatic scaling

Code execution

Fault tolerance


Forrester evaluated 8 platforms using 124 criteria


Definition: Elastic caching platforms (ECP)

– Platform software that provides data caching

services distributed across two or more server

nodes that:

– consistently perform as volumes grow,

– can be scaled without downtime,

– provide a range of fault-tolerance.


Top 6 scenarios for ECPs

Web user session data

Staging of static or transient Web page fragments

Shared application state

Frequently accessed reference data

Result sets from database queries

Compute-intensive jobs on huge data sets

•Data can be replicated to 2 or more nodes

•Read-through and write-behind can save data to persistent data stores

•Cache can be configured to distribute locks to maintain data integrity during CRUD operations

Availability

•Data stored in-memory for fast access

•Data distributed across 2 or more nodes to avoid bottleneck

•Local cache can store data on same node as code for fastest access

Performance

•Additional nodes can be added in run-time

•Data is re-balanced to take advantage of additional nodes

•Nodes can be removed in real-time to scale down

Scale

Elastic platforms are distributed


Typical IT Web architecture statically scales app server tier – but not the data tier at all

Database

Load balancer

Application server

Application server

Application server

Application server

Or, multiple data stores


Elastic caching adds a layer to overcome data bottlenecks

Database

Load balancer

Cache node

Cache node

Cache node

Application server

Application server

Application server

Application server



Elastic application adds a layer to overcome both data and application bottlenecks – elastically!

Database

Load balancer

Code & Cache node

Code & Cache node

Code & Cache node

Application server

Application server

Application server

Application server


Elastic caching can eliminate bottlenecks.


Programming to an elastic cache is straightforward

Scale, performance, & reliability just works


Elasticity requires more than just caching


Agenda

Massive scale




Recommendations

Cloud computing


Steady state of ~40 instances

Launch of Facebook modification

Peak of 5000 instances

The power of cloud economics is elasticity


The basics of cloud economics are clear

• As demand rises, resources are added• Requires apps to scale out• Load balancing governs

Elastic scale delivers just-in-time capacity

• No upfront payment• No commitment whether you use it or not• Costs aligned to use

Pay per use keeps costs low

• If you can build it, you can deploy it – fast• API access drives use of automation

Self-service fuels productivity


Agenda

Massive scale




Recommendations

Use EAP to achieve high availability.

Replicated, distributed data

Use EAP to achieve breakneck performance.

In-memory, optimized access

Which of your competitors are doing this now?

© 2009 Forrester Research, Inc. Reproduction Prohibited

Thank you

Mike [email protected]

Twitter: mgualtieri

www.forrester.com

The future of scaling forrester research - GigaSpaces Road Show 2011

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Transcript of The future of scaling forrester research - GigaSpaces Road Show 2011