Architecture Continuous Deployment Metrics 
Startup Lessons Learned
NOVEMBER 14, 2013
Alistair Croll will lead a session on Lean analytics for intrapreneurs —from introducing never-before-seen case studies to tracking a product through its entire development and demonstrating which data and metrics are useful in what kinds of situations. Thus we reduce the risk of deployments. How do you address that?
Startup Lessons Learned
JUNE 15, 2009
Lessons Learned by Eric Ries Monday, June 15, 2009 Why Continuous Deployment? Of all the tactics I have advocated as part of the lean startup , none has provoked as many extreme reactions as continuous deployment , a process that allows companies to release software in minutes instead of days, weeks, or months.
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www.subelsky.com
FEBRUARY 25, 2010
Because it has an RSS feed, one could also use "Unresolved Hoptoad Errors" as a metric influencing the continuous deployment system. This isnt Rails-specific, but we use SimpleDB for dumping a lot of important metrics data, like performance measurements, which we then turn into metrics.
Startup Lessons Learned
DECEMBER 28, 2009
Lessons Learned by Eric Ries Monday, December 28, 2009 Continuous deployment for mission-critical applications Having evangelized the concept of continuous deployment for the past few years, Ive come into contact with almost every conceivable question, objection, or concern that people have about it.
Startup Lessons Learned
FEBRUARY 16, 2009
Lessons Learned by Eric Ries Monday, February 16, 2009 Continuous deployment with downloads One of my goals in writing posts about topics like continuous deployment is the hope that people will take those ideas and apply them to new situations - and then share what they learn with the rest of us. Thanks for the comments.
Startup Lessons Learned
JULY 29, 2009
Outside the world of hypothetical examples, its more important to make continual progress than to build the ultimate design. For example, at a previous virtual world company , we spent years developing an architecture to cope with millions of simultaneous users. That’s what Just-in-time Scalability is all about. One last thought.
Startup Lessons Learned
NOVEMBER 13, 2008
Because five whys kept turning up a few key metrics that were hard to set static thresholds for, we even had a dynamic prediction algorithm that would make forecasts based on past data, and fire alerts if the metric ever went out of its normal bounds. Case Study: Continuous deployment makes releases n.
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