Continuous Deployment Database Metrics Open Source 
Startup Lessons Learned
SEPTEMBER 30, 2008
Massive proprietary databases? If not, whos going to insist we switch to free and open source software? For example, how are you going to explain that component drive architecture like.NET isn't going to work for cross platform open open source business models? I dont think so.
Startup Lessons Learned
SEPTEMBER 10, 2008
But if you want to practice rapid deployment, you need to be able to deploy that build in one step as well. If you want to do continuous deployment, youd better be able to certify that build too, which brings us to. For more on continuous deployment, see Just-in-time Scalability. Do you have a bug database?
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The Next Web
AUGUST 6, 2013
Zappos could have gone off and built distribution centers, a large database of footwear, and inventory systems for shipping shoes. Use a continuous delivery model to release new features quickly with the least amount of friction. Consider open-sourcing certain aspects of your platform. Contrast this to Zappos.
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
SEPTEMBER 5, 2008
Lessons Learned by Eric Ries Friday, September 5, 2008 Great open source scalability tools from Danga If you are trying to build a scalable LAMP service, its always best to start with the original and still quite relevant presentation, from Brad Fitzpatrick when he was at LiveJournal. Case Study: Continuous deployment makes releases n.
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
JANUARY 4, 2009
Data storage is becoming a specialized function, delegated most often to relational databases. If you are storing all of your data in a relational database, and the load on that database exceeds its capacity, there is no automatic solution that allows you to simply add more hardware and scale up.
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