The InfoQ Podcast

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Neal Ford, the author of The Productive Programmer, discusses the benefits of polyglot programming and the impact it's had on software development.

Polyglot Programming

Author Harry Percival discusses how he got into TDD, why you should too, and shares some tips

The Case for Test-Driven Development

Summary: For our inaugural podcast QCon chair Wesley Reisz talks to Adrian Cockcroft, who works for Battery Ventures where he advises the firm and its portfolio companies about technology issues and also assists with deal sourcing and due diligence.
Why listen to this podcast
•	Over the last year a large number of frameworks and libraries for building microservices have emerged and we're seeing a lot of rapid change.
•	The stack you choose will often be based on the main language you use, so for example Netflix’s stack is language agnostic but the tooling is very Java-centric.
•	Architectural choices can have a profound impact on success, so some-thing as simple as an overly long timeout with retries can cause your system to suffer from a congestion collapse problem.  Have a large timeout at the edge, and progressively smaller and smaller timeouts as you get deeper into the system.
•	Start with a monolith and move to a distributed architecture when you need to because of team size or to get better separation of concerns.
•	Other disruptive trends include “serverless architecture” like AWS Lambda, and open source itself which is perhaps the true definition of disruptive.
More on this
•	You can access our in-depth coverage on microservices http://bit.ly/1SRnFz3.
•	You can also subscribe to our newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq
•	Attend Adrian Cockcroft 's session at QCon New York 2016, Jun 13-17. http://bit.ly/1TvzlDQ 


Show Notes

Adrian Cockcroft on Microservices, Terraservices and Serverless Computing

In this week's podcast QCon chair Wesley Reisz talks to Matt Ranney who is the Chief Systems Architect at Uber, where he's helping build and scale everything he can. 

Why listen to this podcast:

 - Expanding a company and team at this rate is genuinely hard. Lots of mistakes have been made along the way.
 - Microservices allow companies to grow rapidly but have a cost in terms of aggregate velocity.
 - Uber is gradually moving its marketplace development from Node.js to Go and Java. Java is used for the map services.
 - Aggressive failure testing is used extensively in Uber.
 - Some early design choices - like using JSON over HTTP - make formal verification basically impossible.

Notes and links can be found on InfoQ: http://bit.ly/1TH8app

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq

Attend Matt Ranney's session at QCon New York 2016, Jun 13-17: http://bit.ly/1TH75ht

Uber's Chief Systems Architect on their Architecture and Rapid Growth

In this week's podcast QCon chair Wesley Reisz talks to Heather Fleming, who is the VP of product and program management at GILT, where she is responsible for not only the customer-facing website, but also back office things from distribution to order processing.

Why listen to this podcast:

- GILT treats every person as an individual, with a skillset that is outside their responsibilities.
- You should be able to be your authentic self wherever you are.
- Google found creating a psychologically safe work environment was key to high performing teams.
- You can kill a great team by taking away their autonomy and empowerment.
- Great engineers that want to be managers are fearful of losing their skill, and great engineers that don't want to be managers are put in those roles and are terrible managers.

Notes and links can be found on InfoQ: http://bit.ly/1U2Wgq9

1m 49s - One of the things that makes the culture at GILT so special is the "ingredients framework" that considers every person an individual, with a skillset that is outside what their title might say and what their role and responsibilities might be.
3m 29s - One of the team ingredients is called "motivator" - the ability to make sure that the team understands what they're working on, and more importantly the "why" and how it's driving business or customer value.
4m 35s - The relationship you have with your co-workers should be deeper than many of us are allowing them to be, because they are like your second family.

Quick scan our curated show notes on InfoQ. http://bit.ly/1U2Wgq9 

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq

Attend Heather Fleming's session at QCon New York 2016, Jun 13-17: http://bit.ly/1U2f3og

Show notes

GILT VP Heather Fleming on Unlocking the "Secret Sauce" of Great Teams

In this week's podcast Richard Seroter talks to James Shore, author of The Art of Agile Development and one of the original signatories of the Agile Manifesto. Also on the podcast are Llewellyn Falco, creator of the open source testing tool ApprovalTests and co-founder of Teaching Kids Programming, and Rebecca Wirfs-Brock, inventor of Responsibility-Driven Design, as well as the author of books including Designing Object: Oriented Software and Object Design: Roles, Responsibilities and Collaborations.

Why listen to this podcast:

 - A lot of people know how to do TDD and refactoring for the back end, but not for the font, but the basics are the same.
 - The basics of Test-Driven Development are the same for the front or back end.
 - If you don't know what's wrong, you don't know how to fix it.
 - The most common code smells, according to Llewellyn Falco: Clutter, long lines, long methods, duplication, and inconsistency.
 - How do we make, in an agile way, the architectural work visible, and not ignore it?
 - How do you have an incremental architecture and get measurements? If I say to you I'm going to go away for six months and figure it out, that's not very measurable.

Notes and links can be found on InfoQ: http://bit.ly/1Pse2r1

1m:10s - The talk 'Agile Engineering for the Web' was about how do you bring typical Agile engineering ideas like TDD and refactoring to the front-end languages.
1m:33s - A lot of people know how to do these things on the back-end, but when you get to the front end a lot of people just throw up their hands.
2m:24s - I see CSS bugs all the time, because it's very hard to refactor CSS without breaking something.

Quick scan our curated show notes on InfoQ. http://bit.ly/1Pse2r1

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James Shore, Llewellyn Falco, and Rebecca Wirfs-Brock on TDD and Architecture

In this week's podcast, professor Barry Burd talks to Shuman Ghosemajumder. Ghosemajumder is VP of product management at Shape Security and former click fraud czar for Google. Ghosemajumder is also the co-author of the book CGI Programming Unleashed, and was a keynote speaker at QCon New York 2016 presenting Security War Stories.

Why listen to this podcast:

With more of our lives conducted online through technology and information retrieval systems, the use of advanced technology gives criminals the opportunity to be able to do things that they weren't able to do.

 - Cyber-criminals come from all over the world and every socioeconomic background, so long as there's some level of access to computers and technology.
 - You see organised cyber-crime focusing on large companies because of the fact that they get a much greater sense of efficiency for their attacks.
 - Cyber-criminals are getting creative, and coming up with ways to interact with websites we haven't thought of before.
 - You can have very large scale attacks that are completely invisible from the point of view of the application that's being attacked.
 - The context of what are you are using software for is more important than just going through an understanding of the code level vulnerability.

Notes and links can be found on http://bit.ly/2atBFgk

The People Behind Cyber-Crime

5:28 - There are all kinds of different personalities and demographics involved. Cyber-criminals come from all over the world and every socioeconomic background, so long as there's some level of access to computers and technology. Even in cases where a cyber criminal doesn't know how to use technology directly, or how to create something like a piece of malware, they can still be involved in a cyber-criminal's scheme.
6:29 - A scheme which uses large groups of individuals and which doesn’t necessarily need to have skills itself, is stealing money from bank accounts. Being able to transfer money using malware on people’s machines from one account to another account that the cyber-criminal controls still involves getting that money out. That last step can involve a set of bank accounts that are assigned to real individuals.

More on this:

Quick scan our curated show notes on InfoQ. http://bit.ly/2atBFgk

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq

InfoQ Podcast

Shuman Ghosemajumder on Security and Cyber-Crime

In this week's podcast QCon chair Wesley Reisz talks to Machine learning research scientist John Langford.  Topics include his Machine Learning system Vowpal Wabbit, designed to be very efficient and incorporating some of the latest algorithms in the space.  Vowpal Wabbit is used for news personalisation on MSN.  They also discuss how to get started in the field and it’s shift from academic research to industry use.

Why listen to this podcast:

 - Vowpal Wabbit is a ML system that attempts to incorporate some of the latest machine learning algorithms.
 - How to learn ML: take a class or two, get accustomed with learning theory and practice.
 - ML has moved from the research field into the industry, 4 out of 9 ICML tutorials coming from the industry.
 - It’s hard to predict when you have enough data.
 - AlphaGo is a milestone in artificial intelligence. It uses reinforcement learning, deep learning and existing moves played by Go masters.
 - Deep Learning is currently a disruptive technology in areas such a vision or speech recognition.
 - What’s trendy: Neural Networks, Reinforcement and Contextual Learning.
 - Machine Learning is being commoditized.
 
Notes and links can be found on http://bit.ly/2b4YNqQ

How to Approach Machine Learning

6m:12s To start learning Machine Learning, Langford recommends taking a class or two, mentioning the course by Andrew Ng and another course by Yaser S. Abu-Mostafa.
6m:50s It is recommended to get accustomed with learning theory to avoid some of the rookie's mistakes.

Quick scan our curated show notes on InfoQ. http://bit.ly/2atBFgk

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq

John Langford on Vowpal Wabbit, Used by MSN, and Machine Learning in Industry

In this week's podcast InfoQ’s editor-in-chief Charles Humble talks to Data Scientist Cathy O’Neil. O'Neil is the author of the blog mathbabe.org. She was the former Director of the Lede Program in Data Practices at Columbia University Graduate School of Journalism, Tow Center and was employed as Data Science Consultant at Johnson Research Labs. O'Neil earned a mathematics Ph.D. from Harvard University. Topics discussed include her book “Weapons of Math Destruction,” predictive policing models, the teacher value added model, approaches to auditing algorithms and whether government regulation of the field is needed.

Why listen to this podcast:

 - There is a class of pernicious big data algorithms that are increasingly controlling society but are not open to scrutiny.
 - Flawed data can result in an algorithm that is, for instance, racist and sexist.  For example, the data used in predictive policing models is racist. But people tend to be overly trusting of algorithms because they are mathematical.
 - Data scientists have to make ethical decisions even if they don’t acknowledge it. Often problems stem from an abdication of responsibility.
 - Auditing for algorithms is still a very young field with ongoing academic research exploring approaches.
 - Government regulation of the industry may well be required.

Notes and links can be found on http://bit.ly/2eYVb9q

Weapons of math destruction

0m:43s - The central thesis of the book is that whilst not all algorithms are bad, there is a class of pernicious big data algorithms that are increasingly controlling society.
1m:32s - The classes of algorithm that O'Neil is concerned about - the weapons of math destruction - have three characteristics: they are widespread and impact on important decisions like whether someone can go to college or get a job, they are somehow secret so that the people who are being targeted don’t know they are being scored or don’t understand how their score is computed; and the third characteristic is they are destructive - they ruin lives.
2m:51s - These characteristics undermine the original intention of the algorithm, which is often trying to solve big society problems with the help of data.

More on this:

Quick scan our curated show notes on InfoQ. http://bit.ly/2eYVb9q

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

Cathy O'Neil on Pernicious Machine Learning Algorithms and How to Audit Them

In this week’s podcast, QCon chair Wesley Reisz talks to Keith Adams, chief architect at Slack. Prior he was an engineer at Facebook where he worked on the search type live backend, and is well-known for the HipHop VM [hhvm.com]. Adams presented How Slack Works at QCon SanFrancisco 2016.

Why listen to this podcast:

 - Group messaging succeeds when it feels like a place for members to gather, rather than just a tool
 - Having opt-in group membership scales better than having to define a group on the fly, like a mailing list instead of individually adding people to a mail
 - Choosing availability over consistency is sometimes the right choice for particular use cases
 - Consistency can be recovered after the fact with custom conflict resolution tools
 - Latency is important and can be solved by having proxies or edge applications closer to the user

Notes and links can be found on: http://bit.ly/keith-adams

3m:30s Voice and video interactions are impacted by latency; the same is true of messaging clients
4m:00s The user interface can provide indications of presence, through avatars indicating availability and typing indicators
4m:15s Latency is important; sometimes the difference is between 100ms and 200ms so the message channel monitors ping timeout between server and client
4m:40s 99th percentile is less than 100ms ping time
5m:15s If the 99th percentile is more than 100ms then it may be server based, such as needing to tune the Java GC
5m:25s Network conditions of the mobile clients are highly variable&nbsp;
6m:20s Mobile clients can suffer intermittent connectivity

More on this:
Quick scan our curated show notes on InfoQ. http://bit.ly/keith-adams

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

Keith Adams on the Architecture of Slack, using MySql, Edge Caching, & the backend Messaging Server

In this week’s podcast, Thomas Betts talks with Chris Richardson, a developer, architect, Java Champion and author of POJOs in Action. Before his workshop on Microservices w/ Spring Boot and Docker at QCon San Francisco 2016, Richardson took time to discuss his ideas on how to use DDD and CQRS concepts as a guide for implementing a robust microservices architecture.

Why listen to this podcast:

 - "Microservice architecture" is a better term than "microservices".   The latter suggests that a single microservice is somehow interesting
 - The concepts discussed in Domain-Driven Design are an excellent guide for how to implement a microservices architecture
 - Bounded Contexts correspond well to individual microservices
 - Event sourcing and CQRS provide patterns for how to implement loosely coupled services
 - When converting a monolith to microservices, avoid a big bang rewrite, in favor of an iterative approach

Notes and links can be found on: http://bit.ly/2hZ8TM1

11m:51s - Microservices must be loosely coupled, usually creating a model with one database per service.
12m:45s - There is a business requirement to maintain data consistency across services, and using an event driven architecture is a good way to achieve that.
13m:38s - Event sourcing is specific technique for persisting domain objects as a series of events.
14m:11s - Just as transactions don’t like to be split across microservices, queries cannot simply join across multiple data sources. CQRS provides a solution that accommodates querying via microservices and materialized views.

More on this:
Quick scan our curated show notes on InfoQ. http://bit.ly/2hZ8TM1

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

Chris Richardson on Domain-Driven Microservices Design

Eric Horesnyi, CEO @streamdata.io, talks to Charles Humble about how hedge funds are applying deep learning as an alternative to the raw speed favoured by HFT to try and curve the market.

Why listen to this podcast:

 - Streamdata.io was originally built for banks and brokers, but more recently hedge funds have begun using the service.
 - Whilst Hedge Funds like Renaissance Technologies have been using mathematical approaches for some time deep learning is now being applied to markets. Common techniques such as gradient descent and back propagation apply equally well to market analysis.
- The data sources used are very broad.  As well as market data the network might be using, sentiment analysis from social networks, social trading data, as well as more unusual data such as retail data, and IoT sensors from farms and factories.
 - By way of contrast High Frequency Trading  focusses on latency. From an infrastructure stand-point  you can play with propagation time, Serilization (the thickness of the pipe), and Processing time for any active component in chain.
 - One current battleground in HFT is around using FPGA to build circuits dedicated to feed handlers.  Companies such as Novasparks are specialists in this area.

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2nv71M8

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Eric Horesnyi on High Frequency Trading and how Hedge Funds are Applying Deep Learning to Markets

Wesley Reisz talks to Daniel Bryant on moving from monoliths to micro-services, covering bounded contexts, when to break up micro-services, event storming, practices like observability and tracing, and more.

Why listen to this podcast:

- Migrating a monolith to micro-services is best done by breaking off a valuable but not critical part first.
 - Designing a greenfield application as micro-services requires a strong understanding of the domain.
 - When a request enters the system, it needs to be tagged with a correlation id that flows down to all fan-out service requests.
 - Observability and metrics are essential parts to include when moving micro-services to production.
 - A service mesh allows you to scale services and permit binary transports without losing observability.

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2pFYBiT

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Daniel Bryant on Microservices and Domain Driven Design

Wesley Reisz talks to Sid Anand, a data architect at cybersecurity company Agari, about building cloud-native data pipelines. The focus of their discussion is around a solution Agari uses that is built from Amazon Kinesis Streams, serverless functions, and auto scaling groups.

Sid Anand is an architect at Agari, and a former technical architect at eBay, Netflix, and LinkedIn.  He has 15 years of data infrastructure experience at scale, is a PMC for Apache Airflow, and is also a program committee chair for QCon San Francisco and QCon London.

Why listen to this podcast

 - Real-time data pipeline processing is very latency sensitive
 - Micro-batching allows much smaller amounts of data to be processed
 - Use the appropriate data store (or stores) to support the use of the dataIngesting data quickly into a clean database with minimal indexes can be fast
 - Communicate using a messaging system that supports schema evolution

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2rJU9nB

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Sid Anand on Building Agari’s Cloud-native Data Pipelines with AWS Kinesis and Serverless

Werner Schuster talks to Martin Hadley, data scientist at University of Oxford. They discuss the state of the R language, the rich R ecosystem that covers development (RStudio), notebooks for publication (R Notebooks, RPubs), writing web apps (Shiny), and the pros/cons of the different data frames implementations.

Why listen to this podcast:

 - R is the tool for working with rectangular data
 - Modern data frame implementations are Tibble and data.table (for large amounts of data)
 - RMarkdown and R Notebooks allow to explore data and then publish it the results and (interactive) visualization
 - Use Shinyapps to publish server side R applications
 - Tidyverse is the place to look for modern R packages

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2twOXWJ

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Martin Hadley on R and the modern R ecosystem

Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering.

Why listen to this podcast:

- Chaos engineering is a discipline where you formulate hypotheses, perform experiments, and evaluate the results afterwards.
- Injecting a bit of failure over time is going to make your system more resilient in the end.
- Start with Tier 2 or non-critical services first, and build up success stories to grow chaos further.
- As systems become more and more distributed, there becomes a higher need for chaos engineering.
- If you’re running your first experiment, get your service owners in a war room and get them to monitor the results of the test as it is running.

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2vJoimw

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

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Nora Jones on Establishing, Growing, and Maturing a Chaos Engineering Practice

Shubha Nabar is a senior director of data science for Salesforce Einstein. Prior to working for Salesforce, she was a data scientist at LinkedIn and Microsoft.  In the podcast she discusses Salesforce Einstein and the problem space that they are trying to solve, explores the differences between enterprise and consumer for machine learning, and then talks about the Optimus Prime Scala library that they use in Salesforce.

Why listen to this podcast:
* The volume of data, and hardware advances have made it possible to do machine learning to do them a lot faster.
* AI is a science of building intelligent software, encompassing many aspects of intelligence that we tend to think of as human.
* If you can’t measure something, you can’t fix it.
* You have to think about what you can automate, rather than having a human to try and engineer out all those features.
* Get feedback on design.

Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering.

Why listen to this podcast:

- Chaos engineering is a discipline where you formulate hypotheses, perform experiments, and evaluate the results afterwards.
- Injecting a bit of failure over time is going to make your system more resilient in the end.
- Start with Tier 2 or non-critical services first, and build up success stories to grow chaos further.
- As systems become more and more distributed, there becomes a higher need for chaos engineering.
- If you’re running your first experiment, get your service owners in a war room and get them to monitor the results of the test as it is running.

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2vJoimw

You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

Subscribe: www.youtube.com/infoq
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Shubha Nabar Discusses Einstein, the Machine Learning System in Salesforce

In this podcast, recorded live at Strange Loop 2017, Wes talks to Charity, cofounder and CEO of honeycomb.io.  They discuss the social side of debugging and her Strange Loop talk “Observability for Emerging Infra: What got you Here Won't get you There”.  Other topics include advice for testing in production,  shadowing and splitting traffic, and sampling and aggregation.

Why listen to this podcast:

 - Statistical sampling allows for collecting more detailed information while storing less data, and can be tuned for different event types.
 - Testing in production is possible with canaries, shadowing requests, and feature switches
 - Pulling data out of systems is just noise - it becomes valuable once someone has looked at it and indicates the meaning behind it.
 - Instrumenting isn’t just about problem detection - it can be used to ask business questions later
 - You can get 80% of the benefit from 20% of the work in instrumenting the systems.

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2y6OP1b

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InfoQ - Podcast

Charity Majors on Honeycomb.io, the Social Side of Debugging and Testing in Production

In this podcast Shane Hastie, Lead Editor for Culture & Methods, spoke to Josh Evans, former engineering manager at Netflix on how Netflix does DevOps and the freedom and responsibility culture that undermines their way of working. 

Why listen to this podcast:

•	There are many interpretations of the term DevOps, it is a useful shorthand for a wide variety of technologies and approaches 
•	“You build it, you run it” is the concrete application of the freedom and responsibility culture
•	When building a platform tool make it so easy to use that the product teams are not tempted to try and build something for themselves
•	Product teams are free to experiment and learn, which can feel chaotic and is a valuable part of the freedom and responsibility culture
•	The value of blameless and safe incident reviews – the goal is to learn and find patterns and use that information to present whole classes of failure from happening in the future
•	Don’t view the value stream in a fragmented way – see the whole end to end system with all its interactions and dependencies and optimize the system as a cohesive whole rather than different tools and domains

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2mtCIr1

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Josh Evans on DevOps at Netflix

Software engineers, architects and team leads have found inspiration to drive change and innovation in their team by listening to the weekly InfoQ Podcast. They have received essential information that helped them validate their software development map. We have achieved that by interviewing some of the top CTOs, engineers and technology directors from companies like Uber, Netflix and more. Over 1,200,000 downloads in the last 3 years.