Adrian Cockcroft
MAY 6, 2023
A real-time user experience analytics engine for live video, that looked at all users rather than a subsample. This is a very good thing to have, in fact Netflix built in monitoring for all users at the start of it’s streaming launch in 2007, and it was the very first workload that moved to AWS in 2009.
Dynatrace
JULY 24, 2023
The evolution of DevOps automation Since the concept of DevOps emerged around 2007 and 2008 in response to pain points with Agile development, DevOps automation has been continuously evolving. Business process automation Business process automation is the foundation for improving operational efficiency.
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John McCalpin
APRIL 2, 2020
This data is from the 2007 presentation. It is not surprising that there is a lot of scatter, but the factor of four range in Peak MFLOPS at fixed SPECfp_rate2000/core and the factor of four range in SPECfp_rate2000/core at fixed Peak MFLOPS was higher than I expected… (Also from the 2007 presentation.)
Percona
JANUARY 14, 2019
What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Analytical databases are optimized for a low number of slow queries.
Speed Curve
DECEMBER 19, 2018
Understanding the importance of loading scripts asynchronously might help increase adoption of this critical performance improvement, so we're going to walk through the evolution of async script loading starting way back in 2007. This is likely when some dominant third party snippets (Google Analytics, Facebook, etc.)
Rigor
SEPTEMBER 17, 2019
When working on a project for the Man Booker Prize in 2007 (now known as the Booker Prize), Howard saw first-hand how a heavy-load day could impact a website. Retrospectives. Lessons learned. Q: What in your background helped you gain a stronger understanding of peak-load readiness? From there, he will calculate a load model.
Highly Scalable
MARCH 10, 2015
most of them are structured as data scientist manuals focusing on algorithms and methodologies and assume that human decisions play a central role in transforming analytical findings into business actions. This framework will later be used to describe analytical problems in a more uniform way. Fisher, 2007. Billsus, 2007.
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