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Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
Elastic Grid Talk at JavaOne 08 (San Francisco, USA)
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Elastic Grid Talk at JavaOne 08 (San Francisco, USA)

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The slides can be downloaded from Elastic Grid Blog at: …

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  • 1. Elastic Grid and EC2 How Can Amazon EC2 Benefit from the Elastic Grid Solution? Dennis Reedy Jerome Bernard
  • 2. Agenda EC2 and Amazon Web Services • Capabilities, benefits and challenges Elastic Grid introduction • Technology, approach and benefits Elastic Grid and EC2 • Deploying and scaling applications using Elastic Grid Demonstration 2008 JavaOneSM Conference | java.com.sun/javaone | 2
  • 3. Cloud Computing A way to increase capacity or add capabilities on the fly without investing in new infrastructure, training new personnel, or licensing new software Virtualized hardware available for computation • Resources “in the cloud” Low cost of entry, utility based model • Pay for what you use Embraced by startups, and medium to large corporations as a way to bypass IT Cloud Computing Providers (Utility) • Amazon, Sun, IBM, 3Tera 2008 JavaOneSM Conference | java.com.sun/javaone | 3
  • 4. Amazon EC2 Overview In a nutshell • Provides resizable compute capacity in the cloud EC2 Amazon Machine Image (AMI) • Operating System & application “stack” • Deployed using Amazon Web Services to the “cloud” EC2 Instances • Virtual machines that run AMIs 2008 JavaOneSM Conference | java.com.sun/javaone | 4
  • 5. Typical Architecture Taxonomy Applications Virtual Platform Upper Platform Lower Platform Hardware Platform 2008 JavaOneSM Conference | java.com.sun/javaone | 5
  • 6. Typical Architecture Taxonomy (more detail) Applications Middleware Support, JDBC, JMS, … Enterprise Containers, JEE, Spring, ESBs, OSGi, ... Provisioning, Management, Monitoring & Metering Hardware Platform 2008 JavaOneSM Conference | java.com.sun/javaone | 6
  • 7. EC2 AMI Stack Applications Middleware Support, JDBC, JMS, … Enterprise Containers, JEE, Spring, ESBs, OSGi, ... Provisioning, Management, Monitoring & Metering Hardware Platform 2008 JavaOneSM Conference | java.com.sun/javaone | 7
  • 8. EC2 AMI Stack Applications Middleware Support, JDBC, JMS, … AMI Enterprise Containers, JEE, Spring, ESBs, OSGi, ... Provisioning, Management, Monitoring & Metering Hardware Platform Virtualized 2008 JavaOneSM Conference | java.com.sun/javaone | 7
  • 9. EC2 AMIs: Deployment Challenges The EC2 AMI is a boot image, requires substantial system administrator knowledge As application code changes, AMIs typically need to change Not focused on developer productivity Boot base AMI Copy private key and Upload to S3 certificate (for bundling image) Install and configure requisite software 2008 JavaOneSM Conference | java.com.sun/javaone | 8
  • 10. Elastic Grid Dynamic infrastructure for the dynamic deployment, activation, management of Java applications on virtualized hardware Technology building blocks • Rio • Typica • Jets3t • Jini (River) 2008 JavaOneSM Conference | java.com.sun/javaone | 9
  • 11. Elastic Grid Architecture Administrative Application S3 Console Monitor SLA Policy Enforcement Monitor & Meter Application Agents 2008 JavaOneSM Conference | java.com.sun/javaone | 10
  • 12. Elastic Grid Architecture Administrative Application S3 Console Monitor SLA Policy Application Monitor Enforcement Deploys and manages applications (composed of services), provides failover (if service(s) fail they are re-created), and methods to scale and relocate services Monitor & Meter Application Agents 2008 JavaOneSM Conference | java.com.sun/javaone | 10
  • 13. Elastic Grid Architecture Administrative Application S3 Console Monitor SLA Policy Enforcement Application Agent EG AMI Represents the capabilities of a virtualized compute resource, acts as a dynamic agent instantiating application services Monitor & Meter Application Agents 2008 JavaOneSM Conference | java.com.sun/javaone | 10
  • 14. Elastic Grid EC2 AMI Stack Applications Middleware Support, JDBC, JMS, … Enterprise Containers, JEE, Spring, ESBs, OSGi, ... Provisioning, Management, Monitoring & Metering Hardware Platform 2008 JavaOneSM Conference | java.com.sun/javaone | 11
  • 15. Elastic Grid EC2 AMI Stack Applications Middleware Support, JDBC, JMS, … Dynamic Application Enterprise Containers, JEE, Spring, ESBs, OSGi, ... Provisioning, Management, Monitoring & Metering EG AMI Hardware Platform Virtualized 2008 JavaOneSM Conference | java.com.sun/javaone | 11
  • 16. EC2 AMIs: Deployment with EG AMIs EG AMIs are pre-set, no need to (re-)bundle As application code changes, upload to S3 and deploy Focuses on developer productivity Boot EG AMIs Deploy ... Upload (modified) app to S3 2008 JavaOneSM Conference | java.com.sun/javaone | 12
  • 17. Elastic Grid Deployment Deploy application code S3 1 Upload S3 Command to deploy the application is made 3 As needed download All code is dynamically served application resources and instantiated Application is monitored 2 Deploy activate and managed across EC2 instances Application Monitors Application Agents 2008 JavaOneSM Conference | java.com.sun/javaone | 13
  • 18. Elastic Grid Scalability on EC2 Across existing AMIs App Agent AMI App Monitor AMI SLA App Service Policy Handler 80% allocate Memory Observer register • Allocate an Application Service • Create SLA Policy Handler that registers for Memory utilization notifications • SLA has upper limit set to 80% 2008 JavaOneSM Conference | java.com.sun/javaone | 14
  • 19. Elastic Grid Scalability on EC2 Across existing AMIs App Agent AMI App Monitor AMI SLA App Service Policy Handler increment 80% Memory Observer notify • Memory utilization exceeds 80% • SLA Policy Handler is notified • App Monitor allocates another Application Service instance to appropriate App Agent AMI 2008 JavaOneSM Conference | java.com.sun/javaone | 15
  • 20. Elastic Grid Scalability on EC2 Across existing AMIs App Agent AMI App Monitor AMI SLA App Service Policy Handler increment 80% Memory Observer notify • Memory utilization exceeds 80% • SLA Policy Handler is notified • App Monitor allocates another Application Service instance to appropriate App Agent AMI 2008 JavaOneSM Conference | java.com.sun/javaone | 15
  • 21. Elastic Grid Scalability on EC2 New EC2 Instance App Agent AMI App Monitor AMI EC2 App Service Policy Handler 80% allocate Memory Observer • Allocate an Application Service • Create EC2 Policy Handler which registers for Memory utilization notifications • SLA has upper limit set to 80% 2008 JavaOneSM Conference | java.com.sun/javaone | 16
  • 22. Elastic Grid Scalability on EC2 New EC2 Instance App Agent AMI App Monitor AMI SLA App Service Policy Handler increment 80% Memory Observer notify 2008 JavaOneSM Conference | java.com.sun/javaone | 17
  • 23. Elastic Grid Scalability on EC2 New EC2 Instance App Agent AMI App Monitor AMI SLA App Service Policy Handler increment 80% Memory Observer App Agent AMI notify App Service SLA Policy Handler Memory Observer 2008 JavaOneSM Conference | java.com.sun/javaone | 17
  • 24. Elastic Grid Benefits So what EG does for the app? • Ease development and deployment of Java applications using Amazon services • Provides automated management, fault detection and scalability for the application Why EG should be used • Ease deployment and management of your Java applications 2008 JavaOneSM Conference | java.com.sun/javaone | 18
  • 25. Elastic Grid Tools Tools Used in the Demonstration IntelliJ plugin Rio UI Web Console 2008 JavaOneSM Conference | java.com.sun/javaone | 19
  • 26. Demonstration – A real world use case The Problem French TV channel in need of video conversion for streaming of short videos on the Web • for now on.. • VOD will come really soon • ...and CatchUp TV is close too, I suppose! Video conversion and streaming • done by a 3rd party, • but there are streaming issues and some conversion glitches As of the beginning of April 08, • more than 1.1K videos... • ... for about 40GB of MPEG-4 data! 2008 JavaOneSM Conference | java.com.sun/javaone | 20
  • 27. Demonstration – A real world use case The Problem Pricing: • 7€/GB for streaming, • 300€/month for video conversion, that is $438 $456 per month! per month! month! $474 per This solution won’t scale: • about 30 videos per day... • ... for 1.5GB of MPEG-4 • being converted on 1 machine! 2008 JavaOneSM Conference | java.com.sun/javaone | 21
  • 28. Demonstration – A real world use case The Problem Pricing: • 7€/GB for streaming, • 300€/month for video conversion, that is $438 $456 per month! per month! month! $474 per This solution won’t scale: • about 30 videos per day... • ... for 1.5GB of MPEG-4 • being converted on 1 machine! 2008 JavaOneSM Conference | java.com.sun/javaone | 21
  • 29. Demonstration – A real world use case The Problem Pricing: • 7€/GB for streaming, • 300€/month for video conversion, that is $438 $456 per month! per month! month! $474 per This solution won’t scale: • about 30 videos per day... • ... for 1.5GB of MPEG-4 • being converted on 1 machine! 2008 JavaOneSM Conference | java.com.sun/javaone | 21
  • 30. Demonstration – A real world use case The Objectives Storage should be cheap • MPEG-4 videos and FLV videos should be stored on Amazon S3 Streaming should be fast and reliable • cheap CDN in order to increase both the bps and the QoS • being served from our FLV videos on Amazon S3 Flexibility of deployments for video conversion • should be able to both on a LAN • ... and EC2 infrastructure! Flexibility of deployments for video conversion • don’t want to wait for hours... 2008 JavaOneSM Conference | java.com.sun/javaone | 22
  • 31. Demonstration Architecture IntelliJ SQS EG CLI polls Video Tomcat Web App Converter reads writes S3 S3 (source) (dest) 2008 JavaOneSM Conference | java.com.sun/javaone | 23
  • 32. Demonstration Iterations Approach 1 • LAN based approach using single computer • Using automated SLA management • System scales based on observed thresholds Approach 2 • EC2 based deployment, using EG AMIs • Dynamic deployment of application to EC2 from S3 • Using automated SLA management • System scales application instances (as opposed EC2 instances) based on observed thresholds 2008 JavaOneSM Conference | java.com.sun/javaone | 24
  • 33. Demonstration – 1st approach Local/network file system for both the MPEG-4 videos and the converted videos (FLV). Distribution of video conversion requests: • done by our “smart proxy” sending Amazon SQS messages • .. with the name of the video to convert Video conversion done on machines on the LAN • those machines needs access to the MPEG-4 videos! Use of a dynamic service (with the help of the EG framework) • driving the mencoder OpenSource tool • each Video Converter polls the SQS queue for requests 2008 JavaOneSM Conference | java.com.sun/javaone | 25
  • 34. Demonstration – 1st approach - Results Number of Services 1 2 4 6 2008 JavaOneSM Conference | java.com.sun/javaone | 26
  • 35. Demonstration – 1st approach - Results Number of Services 1 2 4 6 2008 JavaOneSM Conference | java.com.sun/javaone | 26
  • 36. Demonstration – 2nd approach Same as before, but this time, the cluster is hosted on Amazon EC2! The videos were previously uploaded on S3! Each service running on Amazon EC2: • downloads the S3 video from a “bucket”, • convert it to the many FLV flavors, • and uploads the encoded videos to another “bucket” 2008 JavaOneSM Conference | java.com.sun/javaone | 27
  • 37. Demonstration – 2nd approach - Results Number of Amazon EC2 instances 1 2 4 6 2008 JavaOneSM Conference | java.com.sun/javaone | 28
  • 38. Demonstration – 2nd approach - Results Number of Amazon EC2 instances 1 2 4 6 2008 JavaOneSM Conference | java.com.sun/javaone | 28
  • 39. Video Conversion for Streaming of Short Videos 2008 JavaOneSM Conference | java.com.sun/javaone | 29
  • 40. Summary Elastic Grid extends EC2, enabling users to manage & dynamically scale application service instances and AMIs based on declarable SLAs Cloud decides allocation of services • QoS approach provides feedback mechanisms based on SLAs • Today: Human decides/admins each machine Provisioning/changing services is simple • Dynamic reconfigurable systems • Make it live through the network Availability • EG EC2 AMI is available (easy to find with the IntelliJ plugin :)) ami-c140a5a8 Check the Elastic Grid blog for updates and status 2008 JavaOneSM Conference | java.com.sun/javaone | 30
  • 41. Elastic Grid and EC2 How Can Amazon EC2 Benefit from the Elastic Grid Solution? Dennis Reedy dennis.reedy@elastic-grid.com Jerome Bernard jerome.bernard@elastic-grid.com BOF-5105
  • 42. Backups 2008 JavaOneSM Conference | java.com.sun/javaone | 32
  • 43. Demonstration – 2nd approach Same as before, but this time, EG drives scalability with watches on both CPU usage and SQS queue size [Insert here the opstring addition] Still running outside of Amazon EC2 world! 2008 JavaOneSM Conference | java.com.sun/javaone | 33
  • 44. Demonstration – 2nd approach - Results No performance hit • Running on QuadCore – Win. increases total time by 47s, • Running on 2xQuadCore – Mac. increases total time by 47s, • Due to the lowerDampener and upperDampener set to 60s No more instances running than what’s needed! EG scales the number of SQS “workers” according to the SQS queue length and how much CPU is used. EG can quickly provision/unprovision “workers” based on those metrics! 2008 JavaOneSM Conference | java.com.sun/javaone | 34
  • 45. Demonstration – 3rd approach Same as before, but this time, both the MPEG-4 and FLV videos are put on Amazon S3. This means uploading the local MPEG-4 videos to S3: this work is done by our JSB smart proxy! • No change on the client! Each SQS “worker”: • downloads the MPEG-4 video from an Amazon S3 “bucket”, • convert it to many FLV formats, • and uploads the results to another “bucket” Still running out of Amazon EC2 world! 2008 JavaOneSM Conference | java.com.sun/javaone | 35
  • 46. Demonstration – 3rd approach - Results This solution trades CPU for bandwidth • Something not optimal for a LAN cluster! Upload bandwidth is the limiting factor: • On ADSL-2+, max at 60KBps, total processing time becomes an issue! • This means a bit more than 9 days for 45GB! Solution: copy the MPEG-4 videos on a disk, go to your datacenter facility, connect the drive, copy the content and upload from there! Billing is not optimal: billed for uploading of MPEG-4, downloading of MPEG-4 and uploading of FLV files! 2008 JavaOneSM Conference | java.com.sun/javaone | 36
  • 47. Challenges AMI creation & management • Application changes result in changes to AMI • Re-“push” & deploy Application Management • Fault Detection & Recovery • Application reliability Scalability • Making your application meet service level objectives Accounting • Fine-grained accounting • Pay for what you use 2008 JavaOneSM Conference | java.com.sun/javaone | 37
  • 48. Rio Policy-Based infrastructure automating the deployment and execution of distributed applications • Measure Responses against Service Level Agreements • Dynamic execution fabric • Platform and application aware Providing … • Deployment & management capabilities • POJO-based development approach • Fault detection and recovery • SLA Management • Declarative service model Built on • Java and Jini technologies 2008 JavaOneSM Conference | java.com.sun/javaone | 38
  • 49. Demonstration – A real world use case The Problem French TV channel in need of video conversion for streaming of short videos on the Web • for now on.. • VOD will come really soon • ...and CatchUp TV is close too, I suppose! Video conversion and streaming • done by a 3rd party, • but there are streaming issues and some conversion glitches As of the beginning of April 08, • more than 1.1K videos... • ... for about 45GB of MPEG-4 data! 2008 JavaOneSM Conference | java.com.sun/javaone | 39
  • 50. Demonstration – A real world use case The Problem Pricing: • 7€/GB for streaming, • 300€/month for video conversion, that is $438 $456 per month! per month! month! $474 per This solution won’t scale: • about 30 videos per day... • ... for 1.5GB of MPEG-4 • being converted on 1 machine! 2008 JavaOneSM Conference | java.com.sun/javaone | 40
  • 51. Demonstration – A real world use case The Problem Pricing: • 7€/GB for streaming, • 300€/month for video conversion, that is $438 $456 per month! per month! month! $474 per This solution won’t scale: • about 30 videos per day... • ... for 1.5GB of MPEG-4 • being converted on 1 machine! 2008 JavaOneSM Conference | java.com.sun/javaone | 40
  • 52. Demonstration – A real world use case The Problem Pricing: • 7€/GB for streaming, • 300€/month for video conversion, that is $438 $456 per month! per month! month! $474 per This solution won’t scale: • about 30 videos per day... • ... for 1.5GB of MPEG-4 • being converted on 1 machine! 2008 JavaOneSM Conference | java.com.sun/javaone | 40
  • 53. Demonstration – A real world use case The Objectives Storage should be cheap • MPEG-4 videos and FLV videos should be stored on Amazon S3 Streaming should be fast and reliable • cheap CDN in order to increase both the bps and the QoS • being served from our FLV videos on Amazon S3 Flexibility of deployments for video conversion • should be able to both on a LAN • ... and EC2 infrastructure! Flexibility of deployments for video conversion • don’t want to wait for hours... 2008 JavaOneSM Conference | java.com.sun/javaone | 41
  • 54. Demonstration Iterations Approach 1 • LAN based approach using single computer • Using automated SLA management • System scales based on observed thresholds Approach 2 • EC2 based deployment, using EG AMIs • Dynamic deployment of application to EC2 from S3 • Using automated SLA management • System scales application instances (as opposed EC2 instances*) based on observed thresholds 2008 JavaOneSM Conference | java.com.sun/javaone | 42
  • 55. Demonstration – 1st approach Local/network file system for both the MPEG-4 videos and the converted videos (FLV). Distribution of video conversion requests: • done by our “smart proxy” sending Amazon SQS messages • .. with the name of the video to convert Video conversion done on machines on the LAN • those machines needs access to the MPEG-4 videos! Use of a Rio JSB (with the help of the EG framework) • driving the mencoder OpenSource tool • each JSB polls the SQS queue for requests 2008 JavaOneSM Conference | java.com.sun/javaone | 43
  • 56. Demonstration – 1st approach - Results Number of Services 1 2 4 6 2008 JavaOneSM Conference | java.com.sun/javaone | 44
  • 57. Demonstration – 1st approach - Results Number of Services 1 2 4 6 2008 JavaOneSM Conference | java.com.sun/javaone | 44
  • 58. Demonstration – 4th approach Same as before, but this time, the cluster is hosted on Amazon EC2! This means a LAN client uploading the local videos to S3: • just as before this work is done by our JSB “smart proxy”. Each SQS “worker” on Amazon EC2: • downloads the S3 video from a “bucket”, • convert it to the many FLV flavors, • and uploads the encoded videos to another “bucket” 2008 JavaOneSM Conference | java.com.sun/javaone | 45
  • 59. Demonstration – 4th approach EG starts new Amazon EC2 instances based on CPU usage and the length of the SQS queue! Accordingly to how the SLAs are configured • [Insert here the OpString extract] 2008 JavaOneSM Conference | java.com.sun/javaone | 46
  • 60. Demonstration – 4th approach - Results Slower on a per instance basis, but can scale to tens, or hundreds of instances in order to run this in a timely fashion! Upload bandwidth still is the limiting factor! • Investment needed on LAN to S3 bandwidth • Prefer a symmetric connection, like SDSL or Fiber or Cable. The billing problem of the 3rd approach is gone • because the bandwidth between EC2 and S3 is free • $8.55/month for MPEG-4 • $5.7 for upload • $5.82/month for FLV • + EC2 fees depending on the number of videos to convert. 2008 JavaOneSM Conference | java.com.sun/javaone | 47
  • 61. Demonstration – 4th approach - Results EC2 advantages: • Converting 1.1K videos on 1 instances cost as much as converting 1.1K videos on 100 instances • Unless you need each instance less than an hour => Amazon, you should really per minute/CPU or second/CPU! EG advantages: • You don’t need much work in order to do this: simply declare the appropriate Scaling Policy Handler in your OpString! • You can develop/test on your LAN and deploy on Amazon EC2. 2008 JavaOneSM Conference | java.com.sun/javaone | 48

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