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Self-Healing Amazon AWS-Based Open
Source Distributed Rendering System
Presentation to Internet Tech Forum
George Nassef
Chief Technology Officer
June 2, 2014
Our Environment
 LAMPR (Linux Apache MySQL PHP And Redis)
 Millions of IOS and Android Client Mobile Devices
 RESTFul API MVC
 Ad-hoc video rendering jobs submitted with real-time expectations.
 Need for job queue, dispatch, processing and most-importantly: self-healing
recovery.
The Problem
 I wanted to deploy only Amazon SPOT instances to save money.
 However, Spot instances can come and go and be terminated mid-job at
any time due to price/availability changes.
 Also, wanted full horizontal scaling with queue-based communications.
 Any render job which did not finish must be rapidly identified and
requeued.
 However, geo-distribution makes traditional requeue software moot.
Solution
 Use REDIS for queue by creating work queue keys.
 Place to-be-done work in “Messages” key.
 Have each render server pick-up work, move the jobid to the “In Work” queue.
 Created an outboard Mongodb system to capture all system and application
logs.
 Separate process intelligently watches Mongodb system and interprets program
alerts, system messages, warnings, errors.
 “Watching” processor requeues render jobs before they fail.
Progress
 After hundreds of thousands of submitted render jobs, only 2 failures.
 Failures were unrelated to “chaos” of environment or spot instances.
 Realtime analysis of mongodb logs closes/catches security holes, system
errors and provides data and user response time information.
 Huge savings in AWS costs by being able to use ANY availability zone,
worldwide and spin-up or down instances at will without regard to
workload.
 System “self heals” as it scales.
Challenges / Choices
 Hosted REDIS by AWS is ElasticCache.
 Accessible seamlessly across Availability Zones, but not Regions.
 Autoscale groups for spot instances take time to “spin up.”
 CloudWatch metrics may not fit your workload for rapid spinup.
Challenges / Choices
 Hosted REDIS by AWS is ElasticCache.
 Accessible seamlessly across Availability Zones, but not Regions.
 Autoscale groups for spot instances take time to “spin up.”
 CloudWatch metrics may not fit your workload for rapid spinup.

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Self-Healing AWS-Based Open Source Distributed Rendering System By George Nassef

  • 1. Self-Healing Amazon AWS-Based Open Source Distributed Rendering System Presentation to Internet Tech Forum George Nassef Chief Technology Officer June 2, 2014
  • 2. Our Environment  LAMPR (Linux Apache MySQL PHP And Redis)  Millions of IOS and Android Client Mobile Devices  RESTFul API MVC  Ad-hoc video rendering jobs submitted with real-time expectations.  Need for job queue, dispatch, processing and most-importantly: self-healing recovery.
  • 3. The Problem  I wanted to deploy only Amazon SPOT instances to save money.  However, Spot instances can come and go and be terminated mid-job at any time due to price/availability changes.  Also, wanted full horizontal scaling with queue-based communications.  Any render job which did not finish must be rapidly identified and requeued.  However, geo-distribution makes traditional requeue software moot.
  • 4. Solution  Use REDIS for queue by creating work queue keys.  Place to-be-done work in “Messages” key.  Have each render server pick-up work, move the jobid to the “In Work” queue.  Created an outboard Mongodb system to capture all system and application logs.  Separate process intelligently watches Mongodb system and interprets program alerts, system messages, warnings, errors.  “Watching” processor requeues render jobs before they fail.
  • 5. Progress  After hundreds of thousands of submitted render jobs, only 2 failures.  Failures were unrelated to “chaos” of environment or spot instances.  Realtime analysis of mongodb logs closes/catches security holes, system errors and provides data and user response time information.  Huge savings in AWS costs by being able to use ANY availability zone, worldwide and spin-up or down instances at will without regard to workload.  System “self heals” as it scales.
  • 6. Challenges / Choices  Hosted REDIS by AWS is ElasticCache.  Accessible seamlessly across Availability Zones, but not Regions.  Autoscale groups for spot instances take time to “spin up.”  CloudWatch metrics may not fit your workload for rapid spinup.
  • 7. Challenges / Choices  Hosted REDIS by AWS is ElasticCache.  Accessible seamlessly across Availability Zones, but not Regions.  Autoscale groups for spot instances take time to “spin up.”  CloudWatch metrics may not fit your workload for rapid spinup.