A Morning with MongoDB Barcelona: MongoDB and Tapp


Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

A Morning with MongoDB Barcelona: MongoDB and Tapp

  1. 1. How does uses A Morning with MongoDB - Barcelona
  2. 2. what we Solve‣ It is high risk to have all infrastructure in one single cloud provider‣ Single points of failure in infrastructure.‣ Different providers with different SLAs.‣ Different cloud offerings changing everyday (vendors and pricing)‣ Vendor Lock-in‣ Complex software deployment in IaaS offerings‣ No automated migration between public IaaS vendors
  3. 3. our Solution‣ Tapp is compatible with 9 different IaaS providers.‣ Services are managed with Configuration Management Systems.‣ Full compatibility with Linux, Windows and SmartOS‣ Automatic DNS administration to diverge traffic instantly to newly deployed infrastructure‣ Integration with New Relic (APM) coming in following weeks.‣ Tapps extremely easy-to-use UI allows practically anyone with minimal system administration background to commission machines, deploy software and migrate between IaaS providers.‣ We think in multi cloud and treat computer as a commodity.
  4. 4. mayor Challenges for Tapp‣ Highly Scalable‣ Fast to Scale‣ Highly Distributed System‣ Multiple Location Solution‣ Concentrated in Events more than Transactions‣ Needed a Low Learning Curve‣ Limited Resources ($$$)‣ Agile Development
  5. 5. learning Curve‣ SQL is old and does not scale and its not easy to use‣ Programmers work with Objects and Events not Statements‣ ORM(object relational mapping) is the present‣ Mongo has multiple ORM connectors for: ‣ Ruby: Mongoid ‣ Node.js: Mongoose ‣ Php: pymongo ‣ Groovy: gmongo
  6. 6. Mongo in Tapp‣ Multiple Sets replicated across multiple cloud providers and operating systems‣ When we need to scale up we will begin to use sharding options‣ Learning Curve small with use Mongoid‣ Dynamic definition of Data‣ Gridfs allow us to store all the information in the Set‣ Single Logical point of concurrency of data
  7. 7. Mongo in Tapp‣ Monitor data using: ‣ We use Capped collections ‣ MapReduce to calculate summary into other Collections‣ We use readslaves to gather information to Async Server‣ Easy to change requirements with out involving other parties.‣ We only have programers, and our dbas have converted to SysAdmin.‣ Performance, Performance, Performance.
  8. 8. Architecture in Tappsync sync async sync sync async sync async async sync sync inst mongo mongo mongo job job job
  9. 9. DEMO
  10. 10. Scientific and Technological Park Cartuja 93 Technology incubator Marie Curie Leonardo Da Vinci, 18 41092 Seville, Spain + 34 954 460 290 www.besol.es