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Distribute Workload for Efficiency, Budget & Perception

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Helgi Þormar Þorbjörnsson
Helgi Þormar Þorbjörnsson

The document discusses distributing workloads across multiple servers for efficiency, budget, and user perception reasons. It describes characteristics of distributed systems like decoupling, elasticity, high availability and concurrency. Specific techniques discussed include load balancing, monitoring, queue systems, avoiding local dependencies, and using tools like Gearman for asynchronous processing. The talk emphasizes architecting for distribution from the start through techniques like decoupling components, elastic scaling, and avoiding single points of failure.

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Distribute the workload Helgi Þormar Þorbjörnsson PHP Tek, Chicago, 26th May 2011 Sunday, 29 May 2011
Who am I? Sunday, 29 May 2011
Helgi Sunday, 29 May 2011
Helgi VP of Engineering at Orchestra.io Sunday, 29 May 2011
Helgi VP of Engineering at Orchestra.io Developer at PEAR Sunday, 29 May 2011
Helgi VP of Engineering at Orchestra.io Developer at PEAR From Iceland Sunday, 29 May 2011
Helgi VP of Engineering at Orchestra.io Developer at PEAR From Iceland @h on Twitter Sunday, 29 May 2011
Why Distribute? Sunday, 29 May 2011
Why Distribute? Efficiency Sunday, 29 May 2011
Why Distribute? Efficiency Budget Sunday, 29 May 2011
Why Distribute? Efficiency Budget Perception Sunday, 29 May 2011
Efficiency 10 small servers > 1 big Sunday, 29 May 2011
Budget Sunday, 29 May 2011
Budget Spend wisely Sunday, 29 May 2011
Budget Spend wisely Commodity servers Sunday, 29 May 2011
Budget Spend wisely Commodity servers Cloud Computing (EC2) Sunday, 29 May 2011
Perception Sunday, 29 May 2011
Perception Defer intensive processes Sunday, 29 May 2011
Perception Defer intensive processes Give instant feedback Sunday, 29 May 2011
Perception Defer intensive processes Give instant feedback Users keep on browsing Sunday, 29 May 2011
Perception Defer intensive processes Give instant feedback Users keep on browsing Sunday, 29 May 2011
Sunday, 29 May 2011
Ant Colonies Sunday, 29 May 2011
Teamwork When faced with a problem they will solve the problem as one. Sunday, 29 May 2011
Sunday, 29 May 2011
Sunday, 29 May 2011
Architect for Distribution Sunday, 29 May 2011
Characteristics Sunday, 29 May 2011
Characteristics Decoupling Sunday, 29 May 2011
Characteristics Decoupling Elasticity Sunday, 29 May 2011
Characteristics Decoupling Elasticity High Availability Sunday, 29 May 2011
Characteristics Decoupling Elasticity High Availability Concurrency Sunday, 29 May 2011
Decoupling Sunday, 29 May 2011
Application DB API Cache FE Sunday, 29 May 2011
Application DB API Cache FE Sunday, 29 May 2011
DB Application API Cache FE Sunday, 29 May 2011
DB Application API Cache FE Cache Sunday, 29 May 2011
API DB Application API Cache FE Cache Sunday, 29 May 2011
API DB Application API API Cache FE Cache Sunday, 29 May 2011
Elasticity Sunday, 29 May 2011
Cloud Computing Sunday, 29 May 2011
Load Balancing Sunday, 29 May 2011
My Favourite HA Proxy Nginx Sunday, 29 May 2011
Monitoring Sunday, 29 May 2011
When do I need more servers? Sunday, 29 May 2011
Needs to be around from the start! Sunday, 29 May 2011
Keep records Sunday, 29 May 2011
Spot trends Sunday, 29 May 2011
Different types Sunday, 29 May 2011
Different types Hardware Performance Sunday, 29 May 2011
Different types Hardware Performance Software Performance Sunday, 29 May 2011
Different types Hardware Performance Software Performance Availability Sunday, 29 May 2011
Different types Hardware Performance Software Performance Availability Resourcing Sunday, 29 May 2011
Different types Hardware Performance Software Performance Availability Resourcing Sunday, 29 May 2011
Applications Sunday, 29 May 2011
Applications New Relic Sunday, 29 May 2011
Applications New Relic CloudKick Sunday, 29 May 2011
Applications New Relic CloudKick ScoutApp Sunday, 29 May 2011
Applications New Relic CloudKick ScoutApp Nagios Sunday, 29 May 2011
Applications New Relic CloudKick ScoutApp Nagios Cacti Sunday, 29 May 2011
Applications New Relic CloudKick ScoutApp Nagios Cacti Circonus Sunday, 29 May 2011
Automation Sunday, 29 May 2011
Plug into your monitoring Sunday, 29 May 2011
Bringing together Monitoring and Elastic behaviour into one beautiful whole! Sunday, 29 May 2011
Add some intelligence to add / remove servers as needed based on current information. Sunday, 29 May 2011
Just make sure it doesn’t turn into... Sunday, 29 May 2011
Skynet!! Sunday, 29 May 2011
High Availability Sunday, 29 May 2011
Get a highly available and resilient setup by following a few of those recommendations Sunday, 29 May 2011
Remember, even Google has outages Sunday, 29 May 2011
What to avoid Sunday, 29 May 2011
Local Sessions Sunday, 29 May 2011
Solution Store sessions in DB / Memcache Sunday, 29 May 2011
Local Memory Sunday, 29 May 2011
Solution Networked Memcache Sunday, 29 May 2011
Local Files Sunday, 29 May 2011
Local Uploads Sunday, 29 May 2011
Writing to /tmp Sunday, 29 May 2011
Solution Store on S3 or a networked FS Sunday, 29 May 2011
Solution Serve up static files from CDNs Sunday, 29 May 2011
Servers can vanish at any given time Sunday, 29 May 2011
Internal APIs Sunday, 29 May 2011
Application Internal Storage API GFS S3 FS Sunday, 29 May 2011
Application Internal DB API Mongo MySQL Cache Sunday, 29 May 2011
Eventually Consistent Sunday, 29 May 2011
CAP Therom Sunday, 29 May 2011
Consistency Availability Partition Tolerance Sunday, 29 May 2011
Consistency All nodes see the same data at the same time Sunday, 29 May 2011
Availability Node failures do not prevent survivors from continuing to operate Sunday, 29 May 2011
Partition Tolerance The system continues to operate despite arbitrary message loss Sunday, 29 May 2011
Consistency Availability Partition Tolerance Sunday, 29 May 2011
Queue Systems Sunday, 29 May 2011
Good for Sunday, 29 May 2011
Good for Image Processing Sunday, 29 May 2011
Good for Image Processing Distributed Logs Sunday, 29 May 2011
Good for Image Processing Distributed Logs Data Mining Sunday, 29 May 2011
Good for Image Processing Distributed Logs Data Mining Mass Emails Sunday, 29 May 2011
Good for Image Processing Distributed Logs Data Mining Mass Emails Intensive transformation Sunday, 29 May 2011
Good for Image Processing Distributed Logs Data Mining Mass Emails Intensive transformation Search Sunday, 29 May 2011
Common Tools Sunday, 29 May 2011
Common Tools Gearman Sunday, 29 May 2011
Common Tools Gearman Hadoop Sunday, 29 May 2011
Common Tools Gearman Hadoop ZeroMQ Sunday, 29 May 2011
Common Tools Gearman Hadoop ZeroMQ RabbitMQ Sunday, 29 May 2011
Common Tools Gearman Hadoop ZeroMQ RabbitMQ And many others! Sunday, 29 May 2011
Gearman Sunday, 29 May 2011
Your Client Code Gearman Client API (C, PHP, Perl, MySQL UDF, ...) Your App Gearman Job Server Gearman gearmand Gearman Worker API (C, PHP, Perl, Python, ...) Your Worker Code Sunday, 29 May 2011
pear.php.net/ net_gearman Sunday, 29 May 2011
A Story! Sunday, 29 May 2011
Financial Software Sunday, 29 May 2011
3000+ Clients Sunday, 29 May 2011
Each one has 5 external data sources Sunday, 29 May 2011
Each data source is a web service Sunday, 29 May 2011
Ran every 6 hours every day Sunday, 29 May 2011
Cron Sunday, 29 May 2011
Cron Gearman Sunday, 29 May 2011
Cron Gearman Job 1 Sunday, 29 May 2011
Cron Gearman Web Services 1 Job 1 4 2 5 3 Sunday, 29 May 2011
Cron Gearman Web Services Processing 1 Job 1 1 4 5 2 2 5 4 3 3 Sunday, 29 May 2011
But! That wasn’t enough Sunday, 29 May 2011
Job kicked off on login Sunday, 29 May 2011
Supervisord Sunday, 29 May 2011
phpadvent.org/2009/daemonize- your-php-by-sean-coates Sunday, 29 May 2011
Questions? @h helgi@orchestra.io Joind.in: http://joind.in/3433 Sunday, 29 May 2011

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