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Image management at scale
The document discusses challenges and optimizations in image management at scale, highlighting issues like performance blockers due to increasing image demands across various devices and platforms. It emphasizes the importance of optimizing image processing through techniques such as lossless compression, AI-driven features, and serverless rules to enhance operational efficiency while minimizing costs. Additionally, it references tools and solutions like Akamai and Cloudinary for effective image management.
Image management at scale
- 1. Image Management atScale - Pramendra Gupta
- 2. Issues Images are #1performance blocker Increasing demand increase in number of devices and platforms Reduce operation cost Reduce infrastructure cost
- 3. Requirements Optimization such as losslesscompression, optimize resolution Conversion such as from single source to multiple source (jpeg, webp) Resizing, Cropping such as thumbnail, cropping from center and face detection
- 4. Features Fast thumbnail AI powered facedetection, noise detection, image optimization Machine Learning reduce batch process, meta info optimization Serverless
- 5. Rules Minimize unique filesize Minimize image types Minimize reinventing wheel Minimize processing time (TTM) Maximize stability Maximize security
- 6.
- 7. Road Map Phase I PhaseII Image Management Solution Akamai, Cloudinary CDN Akamai Image Management Solution Image Management Application, MapR CDN Akamai
- 8. References Image resizing onthe fly Insanely fast JPEG/ JPG thumbnail scaling Image Management at Ebates