James Governor's Monkchips

Logging and machine data at Scale – a talk at AWS re:Invent 2017

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Earlier this week at AWS re:Invent 2017 I gave a talk to customers about why and how they should tap into the unrealised value of log and machine data in order to create new products and services and improved customer experiences. A common trait of the world’s most valuable companies today is that they all make extensive use of machine data. Apple is notable because it it creates value by claiming, unlike Google and Facebook, that it won’t make use of customer generated data other than to improve user experience.

Use Cases include Security, Compliance, DevOps, IT Service management/root cause analysis ecommerce, digital marketing optimisation, fraud detection, IoT and integration with data from physical assets, and healthcare

Splunk really created the market for tools to leverage machine data for business process integration and remains a dominant player in leveraging machine data. But we’re seeing the rise of the ELK stack for logging and monitoring.

I also discussed Observability as the new hotness, with thanks to Charity Majors and Cindy Sridharan.

Bosch has some amazing use cases in leveraging machine data –¬†Imagine a world where every time an engineer tightens a screw Bosch stores it in MongoDB and correlates it with CADCAM models of the machine part.

 

 

AWS paid T&E to re:Invent. This talk was a paid engagement.

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