DFFML / Software Engineering

No description provided.

In dataflow programming, programs are represented as directed graphs (and are often assembled visually); data “flows” through arcs and is processed by nodes.

In this presentation, we’ll compare dataflow against the imperative and functional programming paradigms, and explore the suitability of dataflow for two tasks: big data analysis and DSP.

Presenter: Marvin Humphrey

Video introduction to dataflow programming: https://www.youtube.com/watch?v=iFlT93wakVo

Paper: “Advances in Dataflow Programming Languages”, by Johnston, Hanna, and Millar (2004)

http://www.cs.ucf.edu/~dcm/Teaching/COT4810-Spring2011/Literature/DataFlowProgrammingLanguages.pdf

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How to read the paper, in four optional steps:

0. Skip it and attend anyway - the presentation won't assume attendees have read the paper.

1. Watch the video.

2. Read section 2.1 "The Pure Dataflow Model" on pages 3-4.

3. Read the sections on "hybrid dataflow", "coarse-grained dataflow", and "synchonous dataflow".

Google has been practicing Site Reliability Engineering (SRE) since the early 2000’s but only recently began speaking about it publicly. Some have called SRE “DevOps 2.0,” while others view it as a competing standard. Is SRE the new DevOps? Or is SRE something only large companies can benefit from?

Attendees will learn how SRE and DevOps align, diverge, and disagree.

DevOps vs. SRE → http://bit.ly/2TRsJXK

Watch more:
Next '19 DevOps & SRE Sessions here → https://bit.ly/Next19DevOpsSRE
Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions

Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform

Speaker(s): Seth Vargo

Session ID: OPS100
product:DevOps & SRE; fullname:Seth Vargo; event: Google Cloud Next 2019; re_ty: Publish; product: Cloud - General; fullname: Seth Vargo;