These are my notes on Roy T. Fielding's famous Ph.D. dissertation "Architectural Styles and the Design of Network-based Software Architecture"

What follows are excerpts from the dissertation, with my notes usually in parentheses.

Roy Thomas Fielding is: chief Scientist in some tech company; Chairman, Apache Software Foundation; Visiting Scholar, W3C @ MIT CS Lab; etc; Publications, Honors, Awards, Fellowships etc. Involved in the authoring of the Internet standards for the Hypertext Transfer Protocol (HTTP) and Uniform Resource Identifiers (URI).

Abstract:

"The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia system."

(He makes it sound as if it was designed this way on purpose.)

"In order to identify {...} aspects of the Web that needed improvement and avoid undesirable modifications, a model for the modern Web architecture was needed to guide its design, definition, and deployment."

(So, he admits the need to build a model after the fact.)

"An architectural style is a named, coordinated set of architectural constraints."

A YouTube videoclip titled "Roy T. Fielding: Understanding the REST Style"

Quote: "It's really an accessible piece of work. It is not full of equations. There is one equation. The equation is there just to have an equation, by the way."

For my notes on REST, see other post: My notes on the Fielding Dissertation (REST)

Foreword

Historically, the difference between scripting languages and real programming languages has been understood as the presence or absence of a compilation step. However, in recent decades the distinction has blurred; from time to time we have seen:

• Interpreters for languages that were originally meant to be compiled.
• Compilers for languages that were originally meant to be interpreted.
• Scripting engines internally compiling source code to bytecode before interpreting it.
• Real languages compiling to bytecode which is then mostly interpreted and rarely converted to machine code.

So, compiled vs. interpreted does not seem to be the real differentiating factor; nonetheless, we can usually tell a scripting language when we see one. So, what is it that we see?

My notes on Devoxx 2016 Belgium - Microservices Evolution: How to break your monolithic database by Edson Yanaga (I attended this conference)

Reduce maintenance window

Achieve zero downtime deployments

"Code is easy, state is hard"

Changes in a database schema from one version to another are called database migrations

Tools: Flyweight Liquibase

Migrations require back and forward compatibility

Baby steps = Smallest Possible Batch Size

Too many rows = Long Locks

My notes on Devoxx US 2017, Knowledge is Power: Getting out of trouble by understanding Git by Steve Smith

"If that doesn't fix it, git.txt contains the phone number of a friend of mine who understands git. Just wait through a few minutes of 'It's really pretty simple, just think of branches as...' and eventually you'll learn the commands that will fix everything."

My notes on GOTO 2016 - Microservices at Netflix Scale: Principles, Tradeoffs & Lessons Learned - R. Meshenberg

They have a division making a layer of tools for other teams to build their stuff on top of it.

Exceptions for statelessness are persistence (of course) but also caching.

Destructive testing - Chaos monkey -> simian army - in production, all the time. (During office hours)

Their separation of concerns looks like a grid, not like a vertical or horizontal table.