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Image Magick in the Cloud Scalable Image Processing Service

Image Magick in the Cloud Scalable Image Processing Service. Sanketh Beerabbi University of Central Florida. Introduction. Image processing is a very compute intensive task which requires multiple compute units to provide near instantaneous results.

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Image Magick in the Cloud Scalable Image Processing Service

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  1. Image Magick in the CloudScalable Image Processing Service Sanketh Beerabbi University of Central Florida

  2. Introduction • Image processing is a very compute intensive task which requires multiple compute units to provide near instantaneous results. • It’s more challenging in online applications involving many simultaneous, “impatient” users creating varying workloads. • Cloud computing provides the scalability needed for running such applications online.

  3. Service • Allows users to upload photos and store them in the cloud. • Allows photos to be manipulated by applying Instagram style image filters. • Allows users to create profile pics by detecting faces and cropping them out of the original photo.

  4. Implementation • Amazon 64 bit Linux AMI • AWS PHP SDK with cURL and PEAR packages • GD and Image Magick for image manipulation • AWS services: • EC2 & S3 • SimpleDB (SDB) • Simple Queue Service (SQS) • Elastic Load Balancer (ELB) • Cloudfront CDN

  5. What took time • Plan and Design (~2 weeks) • LAMP, AWS PHP SDK, GD and ImageMagick (~2 weeks) • Browser based uploading to S3 and server side operations using S3 API (~2 weeks) • Database operations using Simple DB(1 week) • Message passing using SQS API (~2 weeks)

  6. Architecture Simple DB AWS CLOUD

  7. Load Balancing & Redundancy

  8. Modules • Upload – • Stores file names and task status in SDB • Creates bucket and uploads image to S3 • Sends message to SQS • Process – • Reads details from SDB and updates task status. • Receives and deletes message from SQS • Downloads from S3 and processes image . • Uploads processed image to S3.

  9. Message Queing • A single Amazon SQS queue can be shared by multiple instances simultaneously. • An instance that is processing a message can prevent other instances from processing the same message at the same time by temporarily “locking” a message. When the instance is done processing the message, it deletes the message. • If the instance fails while processing the message, another instance can get the message after the lockout period. • The number of processing servers can be changed dynamically to handle varying load.

  10. What I Learnt • PHP, hundreds of new *NIX commands, tools and Linux from the “terminal” point of view. • Virtual networking, load balancing and DNS. • Batch processing on the cloud using multiple instances • Inter-instance communication using message queuing.

  11. DEMO • Main Website: • http://imagecloud.vf1.us/ • AWS Public address: • http://ec2-54-204-45-246.compute-1.amazonaws.com/ • Cloudfront CDN: • http://d3emazpmic2hkb.cloudfront.net/

  12. Questions?

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