Talk about the tapping into the unrealised value of log and machine data in order to create new products and services and improved customer experiences. The value of Splunk and rise of ELK for logging and monitoring. Scale at Facebook. Observability as the new hotness, with thanks to Charity Majors. Use cases and customer examples (bosch etc)

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Logging and machine data at Scale
James Governor @monkchips co-founder.

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“The lumber industry sells what used to be waste —
sawdust, chips, and shredded wood — for a pretty profit.
Today you’ll find these by-products in synthetic fireplace
logs, concrete, ice strengtheners, mulch, particle board,
fuel, livestock and pet bedding, winter road traction,
weed killing and more”
– Jason Fried, CEO Basecamp

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Zero Users Care What The System Health
is
All Users Care What Their Experience Is
Nines Don’t Matter if Users Aren’t Happy
Charity Majors, Honeycomb.io

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Observability bridges tracing, logging, and monitoring
Logs are no longer about history
Real time, streams, and adhoc queries

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https://simplicable.com/new/machine-data

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Use Cases
Compliance
DevOps, IT Service management/root cause analysis
ecommerce, digital marketing optimisation
Fraud detection
IoT and integration with data from physical assets
Healthcare
Real time security

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Always Compliance
Anti-money laundering
PCI
GDPR is coming – fines potentially 4% of global turnover

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Splunk
Dubai Airport instruments literally everything
– Even hand washing in the bathroom from electronic taps and soap
Rackspace ingests 3TB of data every day
– Security monitoring and management
Tactical Assault Light Operator Suit (TALOS)
– Monitoring including vital signs

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ELK as a disruptive entrant
Started as text search, now as a default for many orgs
Sprint – 3bn events per day
– Digital Transformation 4.0 Project
– real-time data from Retail Management and Store Ops
– 200 dashboards represent events from logs, databases, emails,
syslogs, test messages, and internal and vendor application APIs.
Uber, Facebook, Netflix

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Edge Filtering
IoT
Sampling and polling

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Tracing at Facebook
2014 Mystery Machine took 2 hours to compute a model from 1.3M traces
2017 Canopy generates and processes 1.3 billion traces per day
(spanning end-user devices, web servers, and backend services, backs 129
performance datasets from high-level end-to-end metrics to specific custom use cases)
Source https://blog.acolyer.org/2017/11/22/canopy-an-end-to-end-performance-tracing-and-analysis-system/

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Roll your own kind of sucks

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Using machine data for business process optimization
Data isn’t on the balance sheet
But data as product is
Data optimized services and customer experiences
Data culture
Observability is the new hotness

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Cloud Native Tools
Grafana – visualization graph and dashboards,
Prometheus – monitoring and alerting, time series
Fluentd – data collector and log aggregation
Graphite – time series and graphs