ETE 2014

Philly ETE #29 – Data in Motion: Latency and Throughput – David Richardson & John Granieri

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From the abstract: All distributed systems are constrained by their ability to move data between components. We will talk about the engineering discipline required to achieve low latency and high throughput. Examples will be given from low latency C++ and high throughput python components used in SIG’s trading and data analysis stack. SIG is a … Read More

Philly ETE #28 – Coaching Teams Along the Path to Agile Fluency – Diana Larsen

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From the abstract: Going “Agile” can confer a number of benefits to teams and organizations, but all too often those promised benefits aren’t fully delivered and everyone wonders why. As organizational leaders/mentors and Agile coaches, we find ourselves confronted when the promise of Agile doesn’t match the reality. How do we avoid the traps of … Read More

Philly ETE #27 – Call Me Maybe: Distributed Databases and Linearizability – Kyle Kingsbury

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From the Abstract: We rely on distributed databases and queues to store and process data reliably, but many fall short of their marketing promises. I’ve spent the last year building tools to stress and analyze popular databases during network partitions, uncovering everything from undocumented behavior to catastrophic data loss. In this installment of the Jepsen … Read More

Philly ETE # 26 – Building the “Front Half” of Your App – Ben Alman

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From the abstract: As web applications have become more complex, we’ve addressed performance, usability and scaling concerns by promoting JavaScript from second-class citizen (image rollovers, form validation) to first-class citizen (business logic, app routing, Ajax, templating). However, in doing so, most of us haven’t optimized our process to treat JavaScript and its front-end siblings, CSS … Read More

Philly ETE #24 – A Look at Polyglot Data and Event Sourcing – Greg Young

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From the abstract: We are forced to solve many problems with respect to handling data. Many concepts work in our current models, many do not. Picking the wrong model can lead to massive amounts of accidental complexity. “Polyglot data” should not be confused with “polyglot persistence.” The former refers to using multiple data representations in … Read More

Philly ETE 2014 #21 – Understanding Latency: Pitfalls, Lessons & Tools – Gil Tene

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From the abstract: Understanding application responsiveness and latency is critical not only for delivering good application behavior but also for maintaining profitability and containing risk. However, good characterization of bad data is useless. If measurements of response time present false or misleading latency information, even the best analysis can lead to wrong operational decisions and … Read More