Algorithm Continuous Deployment Metrics 
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.
Startup Lessons Learned
SEPTEMBER 15, 2008
Focus on the output metrics of that part of the product, and you make the problem a lot more clear. To promote this metrics discipline, we would present the full funnel to our board (and advisers) at the end of every development cycle. Max Levchin of Slide and Paypal has noted that 10% of Slides headcount is devoted to metrics only.
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Startup Lessons Learned
NOVEMBER 29, 2008
For the past couple of years Ive used a question that I once was asked in an interview, in which you have the candidate produce an algorithm for drawing a circle on a pixel grid. As they optimize their solution, they eventually wind up deriving Bresenhams circle algorithm. Case Study: Continuous deployment makes releases n.
Startup Lessons Learned
APRIL 7, 2010
At least, not in the traditional sense of trying to squeeze every tenth of a point out of a conversion metric or landing page. Even if it shows improvement in some micro metric, does that invalidate the overall design? Those of us with a computer science background call it the hill-climbing algorithm. No one feature is to blame.
Startup Lessons Learned
JULY 29, 2009
The design failure meant that there was constant thrashing as the servers struggled to provision capacity according to the “elegant&# algorithm we’d designed. Case Study: Continuous deployment makes releases n. Neither assumption proved remotely accurate. One last thought.
Startup Lessons Learned
JANUARY 4, 2009
More common is to use a one-way hashing algorithm to map the data to be accessed to one of the shards that store it. Theres no complex algorithm to go wrong, just a simple lookup table. Of course, you could use URL-based sharding to "wrap" a CH algorithm (or any hashing scheme you wanted).
Startup Lessons Learned
MARCH 16, 2009
This is a fairly simple approach to creating a weighting system using an Opportunity Algorithm. The algorithm is Importance + max(Importance - Satisfaction, 0) = Opportunity. Case Study: Continuous deployment makes releases n. I wont do the explanation justice so I suggest you grab the book.
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