For the past 3 years, ASOS has been on a journey of moving its monolithic architecture to Microservices - and what has been driving this change is not just the buzzword: as with any monolith, the spiraling cost of change stifles the business and innovation. And in this market, advancing your competitive edge by constant improvement is a big factor in the overall success of your business.
Probably not many know that ASOS website drives more traffic (and way more bandwidth) than the showcase Stackoverflow. Some of the services are built to serve up to 10K RPS (request/second). And the services are spread around the globe currently on more than 4 Azure DCs. And on the top, we have pretty thick data pipelines moving many GBs of data to enable traditional BI - as well as the trendy Machine Learning algorithms powering recommendations and personalisation.
This talk will be a brief intro to the overall view of what +20 2-pizza teams are doing and in specific, goes into some of the details of ML-enabled recommendations platform. Underneath the success of the transition, has been a Logging/Monitoring/Alerting system (Elasticsearch+ConverorBelt+Kibana) to empower platform teams to ensure health of the system and keeping Mean-Time-to-Recovery low.
As with any such talk, there will be a section on lessons learned...