AWS at Mendeley (London, September 27th 2011)

2,091 views
1,992 views

Published on

How Mendeley uses Amazon web services achieve our vision of improving the world of research. This talk was giving at an AWS event in London.

Published in: Technology, Education
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
2,091
On SlideShare
0
From Embeds
0
Number of Embeds
354
Actions
Shares
0
Downloads
12
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide
  • Introduce myself\nAsk who knows about Mendeley\nMendeley are a start-up aiming to improve the world of research\n
  • One of our two core products, Mendeley Desktop\nResearch can put research papers they read, annotate their thoughts and ideas\nUse them as citations inside Word, Openoffice, Latex\n
  • Sync to Mendeley Web, where you can share notes and collaborate with other\nAlso allows us to produce statistics and trends on research speeding up the usual delay researchers get with feed back to their publications.\n
  • A few numbers... we’ve got over 1 million research using the platform. They’ve uploaded over 130 million documents, which we’ve found around 40 million are unique. Of these 40 million we’ve got 17 million pdf articles users have uploaded, giving around 16TH of documents in total.\n\nSo quite a scaling and growth challenge!\n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • Hello how’s this looking...\n
  • \n
  • \n
  • AWS at Mendeley (London, September 27th 2011)

    1. 1. Revolutionising the world of researchwith Amazon Web ServicesDan HarveySystems Architect
    2. 2. Mendeley helps researchers work smarter
    3. 3. Mendeley makes science more collaborative and transparent Sync between computers and peers around the world
    4. 4. 1 million researchers... Uploaded130 million citations 40 million unique 17 million papers 16 TB of data
    5. 5. Document Storage• Backed on to S3• Previews for 16TB of PDFs?
    6. 6. PDF Previews Process Queue Load PDFs Elastic Beanstalk S3Render to PDF Store PNG Serve via Cloud Front
    7. 7. System Overview S3 RD EM S R EC 2 EB S VPC
    8. 8. Article Search• Based on Solr (open source search)• 40GB index• Variable usage H-p Requests Day  of  the  month
    9. 9. Solr Layout Solr Master EB S Inside VPC Outside VPC Solr Solr SolrSlave Slave Slave Elastic Search Load Balancer Queries
    10. 10. • Machine learning on Hadoop• Personalised article recommendations• Collaborative filtering based• Running on Elastic Map Reduce
    11. 11. Summary• Not all or nothing• Focus on your problem not “Undifferentiated heavy lifting” - Werner Vogels• Learn the building blocks AWS provide
    12. 12. Enjoy what you’ve seen? We’re hiring! Senior Java Engineers chat to me after or e-mail/tweet
    13. 13. Questions? @DanHarveydan.harvey@mendeley.com

    ×