Upgrade to Pro — share decks privately, control downloads, hide ads and more …

FutureStack 15: New Relic at Scale

Nic Benders
November 11, 2015

FutureStack 15: New Relic at Scale

In a typical day, New Relic receives half a trillion data points from our customers. All of these need to be processed, stored and made available for charts, queries and alerts as soon as possible. Getting from humble roots to querying more than a billion events a second has meant radically reinventing and re-architecting the whole platform multiple times.

In this session, Matthew Flaming and Nic Benders from New Relic will take you on a deep dive into some of the lessons we've learned along the way and where we go from here. They'll touch on designing scalable services, optimizing for predictability, creating software architecture through team structure, and what it takes to (continuously) rebuild a system that can never stop.

Nic Benders

November 11, 2015
Tweet

More Decks by Nic Benders

Other Decks in Programming

Transcript

  1. Confidential ©2008-15 New Relic, Inc. All rights reserved. Building a

    System that Never Stops: New Relic at Scale 1 Matthew Flaming Nic Benders
  2. EVERY MINUTE requests accepts
 over 16M stores
 over analytic
 events

    2M aggregates
 over 600M metrics 3B queries
 over data
 points ▪
  3. 1. NOTHING Lasts Forever 2. Run EXPERIMENTS 3. SYNCHRONOUS CALLS

    are going to be a problem 4. Master the ROLLOUT 5. NEW TECH = NEW CHALLENGES 6. Use the right WORKLOAD DISTRIBUTION 7. Technology enables CULTURE 8. Software architecture: THE BIG PICTURE The New Relic lesson plan
  4. Collector New Relic App Agents Browser R.U.M.
 Beacon New Relic

    Browser Agents Mobile Proxy New Relic Mobile Agents
  5. New Relic App Agents New Relic Browser Agents New Relic

    Mobile Agents Zzz Collector Browser R.U.M.
 Beacon Mobile Proxy
  6. ▪ Kafka Kafka Browser Data Consumer Browser Data Router New

    Relic App Agents New Relic Browser Agents Collector
  7. ▪ Kafka Kafka Browser Data Consumer New Relic App Agents

    Collector Zzz Browser Data Router New Relic Browser Agents
  8. Rollout
 Techniques Kafka Load Balancer Cluster Kafka Browser Data Consumer

    Browser Data Router Browser Data
 Consumer V2 Browser R.U.M.
 Beacon %- %+ New Relic Browser Agents Collector Old New
  9. ©2008-15 New Relic, Inc. All rights reserved. ▪ Workload Distribution

    A C B D D D D D B C B B B B D D A A A A A D D Active Management Random C B B B D D A A D C B B D B C A A D D C C A B
  10. Software Architecture: The Big Picture ▪ ▪ ▪ ▪ ▪

    Organic growth Paradigm shift Breaking point
  11. Organic Growth Collector New Relic App Agents Browser R.U.M.
 Beacon

    New Relic Browser Agents Mobile Proxy New Relic Mobile Agents
  12. Breaking Point Collector Browser R.U.M.
 Beacon Mobile Proxy Zzz New

    Relic App Agents New Relic Browser Agents New Relic Mobile Agents
  13. ▪ Kafka Kafka Browser Data Consumer Browser Data Router New

    Relic App Agents New Relic Browser Agents Collector