cloudify your business
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CLOUDIFY YOUR BUSINESS
Wayne wallscloud evangelist
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Self-Service
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On-Demand
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Metered
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Resource Pooling
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Broad Network Access
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NIST SAys...
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NIST says...
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NIST says...
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Financial Services Data Analysis & ForecastingMapReduce Data AnalyticsDistributed, Web 2.0 Apps
REVOLUTIONARY
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SAPPeopleSoftSharePointSQLHome GrownClient-Server Based
EVOLUTIONARY
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Big Promise of Cloud
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Scale!
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High-Availability vs Service Resiliency
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What is HA?
Active/PassiveActive/Active
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:Problem:Single Point of Failure
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:Solution:MAKE TWO OF ‘EM!
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Hammer & Nail Solution
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High-Availability has Problems
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Fails In Terrible Ways &Doesn’t Really Scale
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Two Options to “HA”
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Take a non-distributed system and drop HA on top of it
Option #1
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NFS
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Mean Time Between Failures (MTBF)
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Mean Time To Recovery (MTTR)
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Expected failures of a traditional HA system are catastrophic
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Expected failures of a traditional HA system are catastrophic
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Expected failures of a traditional HA system are catastrophic
System not designed to be distributed
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Expected failures of a traditional HA system are catastrophic
System not designed to be distributed
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Expected failures of a traditional HA system are catastrophic
System not designed to be distributed
Failure forces it to be distributed
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Expected failures of a traditional HA system are catastrophic
System not designed to be distributed
Failure forces it to be distributed
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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
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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
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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
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Take a distributed system and make the right tradeoffs
Option #2
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Service Resiliency
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Examples
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Percona XtraDBCassandra
Riak
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CephGlusterFS
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Constant Health Checks
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What is in a Running Application?
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Availability vs Reliability
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Reliability is the likelihood that a given component or system will be functioning when needed as measured over a given period of time.
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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.
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Server Service
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Hardware does not get a pass...
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Think availability from the service layer(s) perspective
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Apps in a Cloudy World
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Greenfield vs Legacy
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Greenfield
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Greenfield
1. Focus on the service, not the server
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Greenfield
1. Focus on the service, not the server2. Identify & tear apart stateless and stateful parts of your application
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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
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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
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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
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Legacy
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Legacy
1. Cloud Instances != server
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Legacy
1. Cloud Instances != server2. Plan to reduce mean time to recovery (MTTR)
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Legacy
1. Cloud Instances != server2. Plan to reduce mean time to recovery (MTTR)3. "We're HA, we're all good." -> Wrong.
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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
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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)
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Thank You!
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