Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Condé Nast Italy: Serverless Cost Optimization

387 views

Published on

How Condé Nast went form $$$ to $$$/4

Published in: Engineering
  • Be the first to comment

  • Be the first to like this

Condé Nast Italy: Serverless Cost Optimization

  1. 1. Serverless Hamburg – 12 March 2018 Serverless Cost Optimization: how Condé Nast went from $$$ to $$$/4 Marco Viganò Digital CTO Serverless On Stage #10 20 March 2018
  2. 2. Serverless Hamburg – 12 March 2018
  3. 3. Serverless Hamburg – 12 March 2018
  4. 4. Serverless Hamburg – 12 March 2018 CN.numbers // by month 30M Unique Visitors 250M Page Views 20% Desktop 80% Mobile 46% SEO 29% Social
  5. 5. Serverless Hamburg – 12 March 2018 CN.technologies
  6. 6. Serverless Hamburg – 12 March 2018 • Infrastructure scaling problems due to traffic boost • Non optimal delivery and uptime • Aggressive time to market • No automation • Costs onPremise(CN) = Error 500 Internal Server Error 2013 / 2014
  7. 7. Serverless Hamburg – 12 March 2018 Wave 1: the pilot
  8. 8. Serverless Hamburg – 12 March 2018 CN.pilot === “Wired.it” MigrationPreparationEvaluation Tuning Pilot Cloud migrationEngagement of team
  9. 9. Serverless Hamburg – 12 March 2018 • Infrastructure migrated AS IS -> no optimization for the cloud • 150 Server + 30 DB + more than 50 LB • Application redundancy • Costs explosion: CN #epicfail on premise + cloud + people + external providers = _______________ a lot of money!!!
  10. 10. Serverless Hamburg – 12 March 2018 Wave 2: consolidation (start Q3 2014)
  11. 11. Serverless Hamburg – 12 March 2018 • Application !cloud optimized • Destroy monoliths • Make refactoring • Automation • CN Blueprint
  12. 12. Serverless Hamburg – 12 March 2018 CN.blueprint
  13. 13. Serverless Hamburg – 12 March 2018 end of wave 2 (2015): ROI
  14. 14. Serverless Hamburg – 12 March 2018 Wave 3: thinking Serverless (start Q3 2014)
  15. 15. Serverless Hamburg – 12 March 2018 CN.Vogue().photovogue • > 300,000 photographers more than 800,000 photos image size up to 50 Mb The Challenge • PV was launched in 2011: needs new UI/UX and to be re-engineered • Photos and users growing by the day: old legacy IT infrastructure wasn’t able to manage the website traffic • We need to provision resources quickly: problems in scaling • We wanted to give both photographers and editorial staff a better, faster experience • Problems with large file upload
  16. 16. Serverless Hamburg – 12 March 2018 serverless(CN.Vogue().photovogue) • Quicker provisioning of resources: from days to hours • No scaling problem due to traffic boost • Cost saving: cut 30% in comparison to the old infrastructure • Enabling innovation: Devs / DevOps, are now focused on innovation not on manage old infrastructure survival • UX 90% faster: photographer and editorial team now have an excellent experience old_windows_cluster(CN.Vogue().photovogue)
  17. 17. Serverless Hamburg – 12 March 2018 end of wave 3 (2016)
  18. 18. Serverless Hamburg – 12 March 2018 Wave 4: reserve capacity (start in Q2 2016 – running in 2017/2018)
  19. 19. Serverless Hamburg – 12 March 2018 Predictable Workloads
  20. 20. Serverless Hamburg – 12 March 2018 • Reserved Instances / Committed use discounts • 1 year / 3 years • CN.Italy.saving[‘2016’] = 35% • CN.Italy.saving[‘2017’] = 60% • CN.Italy.saving[‘2018’] = VMs + DB + DWHPay as yo go Reserved Capacity
  21. 21. Serverless Hamburg – 12 March 2018 2017 costs = On Premise / 4
  22. 22. Serverless Hamburg – 12 March 2018 Wave 5: container (start Q4 2017 - runninng)
  23. 23. Serverless Hamburg – 12 March 2018 • Build, Ship, and Run any App, Anywhere • Running containers across many different machines • Scaling up or down by adding or removing containers when demand changes • Keeping storage consistent with multiple instances of an application • Distributing load between the containers • Launching new containers on different machines if something fails
  24. 24. Serverless Hamburg – 12 March 2018
  25. 25. Serverless Hamburg – 12 March 2018 Tips & Tricks
  26. 26. Serverless Hamburg – 12 March 2018 • VMs Autoscaling • Caching: Varnish, Redis, memcache… • Offload of static resources: CDN • Infrastucture self healing • Serverless Tip&Tricks(CN); // costs optimization
  27. 27. Serverless Hamburg – 12 March 2018 Turn off the lights
  28. 28. Serverless Hamburg – 12 March 2018
  29. 29. Serverless Hamburg – 12 March 2018 Turn off the lights 25% 25% 25% 25% • CPU from 8pm to 8am • 0.2$/h 0.2$/h x 4VMs x 24h x 365day = 7008 $ • Turn of from 8pm to 8am 12h x 365day = 4380h saving = 876$ • 7008$ - 876$ = 6132$ • 12.5% Saving 33% 33% 33%
  30. 30. Serverless Hamburg – 12 March 2018
  31. 31. Serverless Hamburg – 12 March 2018 Last but not least • Make investments on your team: training, summit, Meetup, certifications, R&D… • Your team must be at the center of your Cloud Transformation • No Team -> No Party -> No Saving!!!
  32. 32. Serverless Hamburg – 12 March 2018 summary
  33. 33. Serverless Hamburg – 12 March 2018 CN.costs.onCloud() = CN.costs.onPremise() / 4 CN.time_to_market.onCloud() = CN.time_to_market.onPremise() / 5
  34. 34. Serverless Hamburg – 12 March 2018 2013/2014 >150 servers! 30 Databases 2015: ROI!!!! 2016 Change Mindset: Thinking Serverless - Photovogue - Starting reducing costs From an angry CFO… to a happy CFO :) 2017 Infrastucture improvements 50 servers - 8 Databases Costs = on premise / 4 On premise 2018 Continuos improvements: Serverless *.* Docker / K8
  35. 35. Serverless Hamburg – 12 March 2018 Thank You Marco Viganò @Sasha0423

×