Cloudify Your Business

CLOUDIFY YOUR BUSINESS

Wayne wallscloud evangelist

Wednesday, August 21, 13

Self-Service

On-Demand

Metered

Resource Pooling

Broad Network Access

NIST SAys...

NIST says...

Financial Services Data Analysis & ForecastingMapReduce Data AnalyticsDistributed, Web 2.0 Apps

REVOLUTIONARY

SAPPeopleSoftSharePointSQLHome GrownClient-Server Based

EVOLUTIONARY

Big Promise of Cloud

Scale!

High-Availability vs Service Resiliency

What is HA?

Active/PassiveActive/Active

:Problem:Single Point of Failure

:Solution:MAKE TWO OF ‘EM!

Hammer & Nail Solution

High-Availability has Problems

Fails In Terrible Ways &Doesn’t Really Scale

Two Options to “HA”

Take a non-distributed system and drop HA on top of it

Option #1

Mean Time Between Failures (MTBF)

Mean Time To Recovery (MTTR)

Expected failures of a traditional HA system are catastrophic

System not designed to be distributed

Failure forces it to be distributed

Cannot take distributed failure conditions into account

Best case scenario: complete failure

Take a distributed system and make the right tradeoffs

Option #2

Service Resiliency

Examples

Percona XtraDBCassandra

CephGlusterFS

Constant Health Checks

What is in a Running Application?

Availability vs Reliability

Reliability is the likelihood that a given component or system will be functioning when needed as measured over a given period of time.

Availability is the percentage of times that a given system will be functioning as required.

Server Service

Hardware does not get a pass...

Think availability from the service layer(s) perspective

Apps in a Cloudy World

Greenfield vs Legacy

Greenfield

1. Focus on the service, not the server

Greenfield

1. Focus on the service, not the server2. Identify & tear apart stateless and stateful parts of your application

Greenfield

1. Focus on the service, not the server2. Identify & tear apart stateless and stateful parts of your application3. Make stateful parts redundant using distributed data stores

Greenfield

1. Focus on the service, not the server2. Identify & tear apart stateless and stateful parts of your application3. Make stateful parts redundant using distributed data stores4. Know the dependencies of your system and the impact of failure

Greenfield

1. Focus on the service, not the server2. Identify & tear apart stateless and stateful parts of your application3. Make stateful parts redundant using distributed data stores4. Know the dependencies of your system and the impact of failure5. Use micro-services to make dependencies explicit

Legacy

1. Cloud Instances != server

Legacy

1. Cloud Instances != server2. Plan to reduce mean time to recovery (MTTR)

Legacy

1. Cloud Instances != server2. Plan to reduce mean time to recovery (MTTR)3. "We're HA, we're all good." -> Wrong.

Legacy

1. Cloud Instances != server2. Plan to reduce mean time to recovery (MTTR)3. "We're HA, we're all good." -> Wrong.4. Think about stateful vs stateless parts of your application and work piece by piece

Legacy

1. Cloud Instances != server2. Plan to reduce mean time to recovery (MTTR)3. "We're HA, we're all good." -> Wrong.4. Think about stateful vs stateless parts of your application and work piece by piece5. Be creative about trade-offs: many apps that run on more than one server have some type of common backend (NFS)

Thank You!

Cloudify Your Business

Technology

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