feedback, and then adjust what they have produced. As a result, the code can be developed in a user-centric way and match the enterprise’s needs precisely. Risk is low, because the team is constantly adjusting

RequestHandler): def get(self): self.write("Hello, world") def make_app(): return tornado.web.Application([ (r"/", MainHandler), ]) async def main(): app = make_app() app.listen(8888) await asyncio.Event() generally causes some work to happen in the background before triggering some future action in the application (as opposed to normal synchronous functions, which do every- thing they are going to do before run(main()) 6.1.5 Structure of a Tornado web application A Tornado web application generally consists of one or more RequestHandler subclasses, an Application object which routes incoming requests to handlers

def get(self): self.write("Hello, world") def make_app(): return tornado.web.Application([ (r"/", MainHandler), ]) async def main(): app = make_app() app.listen(8888) spider Structure of a Tornado web application Templates and UI Authentication and security Running and deploying Web framework tornado.web — RequestHandler and Application classes tornado.template — Flexible background Queue example - a concurrent web spider Structure of a Tornado web application The main coroutine The Application object Subclassing RequestHandler Handling request input Overriding RequestHandler

Major contributing cause of issues stems from releases representing the first time we see how an application behaves in a production-like environment ii. Don’t just document the environment specifications the value stream iii. Everything, everything, everything is checked into version control 1. Application code & dependencies 2. Environment scripts & creation tools 3. DB scripts and reference data 4. Containers 5. Automated tests 6. Project artifacts – documentation, procedures, etc. 7. Application configuration files 8. This also includes pre-production and build processes 9. Tools iv. 2014

and are subsequently transmitted to receiving equipment for monitoring 1. Create telemetry in application & environments (to include production, pre-production, and CD pipeline) iii. Ian Malpass, Etsy what’s up or down. ii. Modern Monitoring architecture 1. Data Collection at business logic, application, & environments layer a. Events, logs, & metrics b. Common service to centralize, rotate, and systems need to be more available and scalable than the systems being monitored.” c. CREATE APPLICATION LOGGING TELEMETRY THAT HELPS PRODUCTION i. Dev & Ops create production telemetry as part of their

lexicon for this guide. Later sections will present more detail on the Agile processes and their application in DoD programs. The foundational structure of an Agile program is: Release - Capability system or commercial off-the-shelf (COTS) product, or building a small-scale or self-constrained application. In other words, Agile works well when the program needs to modify software for government purposes team or the target end user cannot be accessed. Program scope is mostly limited to the application layer while using existing infrastructure. Program Scope Program spans core capabilities and

vs BROWNFIELD SERVICES i. DevOps is not just for Greenfield ii. Important Predictor – Is the application architected (or could be re- architected) for testability and deployability? iii. Successful Brownfield mainframe and supporting applications a. They 2X release frequency b. Resulted in increased application reliability c. Reduced deployment lead time from 2 weeks to <1 day 2. Etsy a. “Barely survived the business; defines functionality ii. Development - the team responsible for developing the application iii. QA – team responsible for ensuring feedback loop exists to ensure functions as desired

MethodError: objects of type Int64 are not callable Both expressions are interpreted as function application: any expression that is not a numeric literal, when immediately followed by a parenthetical, is like Int (see Overflow behavior). If we had declared our function as fib(n::Int), however, the application to BigInt would have been prevented for no reason. In general, you should use the most general julia> 1 + 2 + 3 6 julia> +(1,2,3) 6 The infix form is exactly equivalent to the function application form – in fact the former is parsed to produce the function call internally. This also means that

MethodError: objects of type Int64 are not callable Both expressions are interpreted as function application: any expression that is not a numeric literal, when immediately followed by a parenthetical, is like Int (see Overflow behavior). If we had declared our function as fib(n::Int), however, the application to BigInt would have been prevented for no reason. In general, you should use the most general julia> 1 + 2 + 3 6 julia> +(1,2,3) 6 The infix form is exactly equivalent to the function application form – in fact the former is parsed to produce the function call internally. This also means that

MethodError: objects of type Int64 are not callable Both expressions are interpreted as function application: any expression that is not a numeric literal, when immediately followed by a parenthetical, is julia> 1 + 2 + 3 6 julia> +(1, 2, 3) 6 The infix form is exactly equivalent to the function application form – in fact the former is parsed to produce the function call internally. This also means that Exceptions to be tested for, and for the graceful handling of things that may ordinarily break your application. For example, in the below code the function for square root would normally throw an exception