Application Analytics: measure twice, code once
Microsoft recently announced the availability of Visual Studio 2015 CTP 6 – included with all of the awesome capabilities and updates was the debut of Dotfuscator Community Edition (CE) 2015. … and, in addition to updates to user functionality (protection and analytics instrumentation capabilities), this is the first version of Dotfuscator CE to include it’s own analytics (we’re using PreEmptive analytics to anonymously measure basic adoption, usage, and user preferences). Here’s some preliminary results… (and these could all be yours too of course using the very same capabilities from PreEmptive Analytics!)
Users by day comparing new and returning users shows extremely low returning users – this indicates that users are validating that the functionality is present, but not actually using the technology as part of a build process – this makes sense given that this is the first month of a preview release – users are validating the IDE – not building real products on that IDE.
Feature usage and user preferences including timing of key activities like what % of users are opting in (of course opt in policy exists and is enforced), what runtimes they care about (including things like Silverlight and ClickOnce and Windows Phone…), the split between those who care about protection and/or analytics, and timing of critical activities that can impact DevOps are all readily available.
Broad geolocation validates international interest and highlights unexpected synergies (or issues) that may be tied to localized issues (language, training, regulation, accessibility, etc.)
This is an example of the most general, aggegrated, and generic usage collection - of course the same analytics plumbing can be used to capture all flavor of exception, user behavior, etc. - but ALWAYS determined by your own design goals and the telemetry is ALWAYS under your control and governance - from "cradle to grave."
BOTTOM LINE: the faster you can iterate – the better your chances for a successful, agile, application launch – building a feedback driven, continuous ALM/DevOps organization cries out for effective, secure, and ubiquitous application analytics – how is your organization solving for this requirement?