Automation

Managing Application Secrets with Brian Kelly - Episode 181

Summary

Any application that communicates with other systems or services will at some point require a credential or sensitive piece of information to operate properly. The question then becomes how best to securely store, transmit, and use that information. The world of software secrets management is vast and complicated, so in this episode Brian Kelly, engineering manager at Conjur, aims to help you make sense of it. He explains the main factors for protecting sensitive information in your software development and deployment, ways that information might be leaked, and how to get the whole team on the same page.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • When you’re ready to launch your next app you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Join the community in the new Zulip chat workspace at podcastinit.com/chat
  • Your host as usual is Tobias Macey and today I’m interviewing Brian Kelly about how to store, deploy, and use sensitive information in your applications

Interview

  • Introductions
  • How did you get introduced to Python?
  • To begin with, how do you define a secret in the context of an application?
  • What are the broad categories for solutions to secrets management?
  • What are the different aspects of secrets management in the lifecycle of developing, deploying, and maintaining an application?
  • How does the scale of a project or organization impact the strategies that are reasonable for secrets management?
  • What are some of the most challenging aspects of secrets management at the different stages of usage?
    • What are some of the common reasons that secrets management strategies fail?
    • What are some of the vulnerabilities or attack vectors that development teams should be thinking about when working with credentials?
  • What are your thoughts on versioning of secrets?
  • Beyond storing and deploying sensitive information, what are some of the secondary concerns around secrets management that development teams should be thinking about?
  • How does the use of multiple environments (e.g. dev, QA, production, etc.) affect the strategies used for secrets management?
  • What are some of the most useful resources that you have found for anyone looking to learn more about this subject?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Keep Your Code Clean Using pre-commit with Anthony Sottile - Episode 178

Summary

Maintaining the health and well-being of your software is a never-ending responsibility. Automating away as much of it as possible makes that challenge more achievable. In this episode Anthony Sottile describes his work on the pre-commit framework to simplify the process of writing and distributing functions to make sure that you only commit code that meets your definition of clean. He explains how it supports tools and repositories written in multiple languages, enforces team standards, and how you can start using it today to ship better software.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • When you’re ready to launch your next app you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Join the community in the new Zulip chat workspace at podcastinit.com/chat
  • Your host as usual is Tobias Macey and today I’m interviewing Anthony Sottile about pre-commit, a framework for managing and maintaining hooks for multiple languages

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by describing what a pre-commit hook is and some of the ways that they are useful for developers?
  • What was you motivation for creating a framework to manage your pre-commit hooks?
    • How does it differ from other projects built to manage these hooks?
  • What are the steps for getting someone started with pre-commit in a new project?
  • Which other event hooks would be most useful to implement for maintaining the health of a repository?
  • What types of operations are most useful for ensuring the health of a project?
  • What types of routines should be avoided as a pre-commit step?
  • Installing the hooks into a user’s local environment is a manual step, so how do you ensure that all of your developers are using the configured hooks?
    • What factors have you found that lead to developers skipping or disabling hooks?
  • How is pre-commit implemented and how has that design evolved from when you first started?
    • What have been the most difficult aspects of supporting multiple languages and package managers?
    • What would you do differently if you started over today?
    • Would you still use Python?
  • For someone who wants to write a plugin for pre-commit, what are the steps involved?
  • What are some of the strangest or most unusual uses of pre-commit hooks that you have seen?
  • What are your plans for the future of pre-commit?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Infection Monkey Vulnerability Scanner with Daniel Goldberg - Episode 177

Summary

How secure are your servers? The best way to be sure that your systems aren’t being compromised is to do it yourself. In this episode Daniel Goldberg explains how you can use his project Infection Monkey to run a scan of your infrastructure to find and fix the vulnerabilities that can be taken advantage of. He also discusses his reasons for building it in Python, how it compares to other security scanners, and how you can get involved to keep making it better.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • When you’re ready to launch your next app you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Join the community in the new Zulip chat workspace at podcastinit.com/chat
  • Your host as usual is Tobias Macey and today I’m interviewing Daniel Goldberg about Infection Monkey, an open source system breach simulation tool for evaluating the security of your network

Interview

  • Introductions
  • How did you get introduced to Python?
  • What is infection monkey and what was the reason for building it?
    • What was the reasoning for building it in Python?
    • If you were to start over today what would you do differently?
  • Penetration testing is typically an endeavor that requires a significant amount of knowledge and experience of security practices. What have been some of the most difficult aspects of building an automated vulnerability testing system?
    • How does a deployed instance keep up to date with recent exploits and attack vectors?
  • How does Infection Monkey compare to other tools such as Nessus and Nexpose?
  • What are some examples of the types of vulnerabilities that can be discovered by Infection Monkey?
  • What kinds of information can Infection Monkey discover during a scan?
    • How does that information get reported to the user?
    • How much security experience is necessary to understand and address the findings in a given report generated from a scan?
  • What techniques do you use to ensure that the simulated compromises can be safely reverted?
  • What are some aspects of network security and system vulnerabilities that Infection Monkey is unable to detect and/or analyze?
  • For someone who is interested in using Infection Monkey what are the steps involved in getting it set up?
    • What is the workflow for running a scan?
    • Is Infection Monkey intended to be run continuously, or only with the interaction of an operator?
  • What are your plans for the future of Infection Monkey?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Continuous Delivery For Complex Systems Using Zuul with Monty Taylor - Episode 172

Summary

Continuous integration systems are important for ensuring that you don’t release broken software. Some projects can benefit from simple, standardized platforms, but as you grow or factor in additional projects the complexity of checking your deployments grows. Zuul is a deployment automation and gating system that was built to power the complexities of OpenStack so it will grow and scale with you. In this episode Monty Taylor explains how he helped start Zuul, how it is designed for scale, and how you can start using it for your continuous delivery systems. He also discusses how Zuul has evolved and the directions it will take in the future.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • When you’re ready to launch your next app you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 200Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Join the community in the new Zulip chat workspace at podcastinit.com/chat
  • Your host as usual is Tobias Macey and today I’m interviewing Monty Taylor about Zuul, a platform that drives continuous integration, delivery, and deployment systems with a focus on project gating and interrelated projects.

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by explaining what Zuul is and how the project got started?
  • How do you view Zuul in the broader landscape of CI/CD systems (e.g. GoCD, Jenkins, Travis, etc.)?
  • What is the workflow for someone who is defining a pipeline in Zuul?
    • How are the pipelines tested and promoted?
    • One of the problems that are often encountered in CI/CD systems is the difficulty of testing changes locally. What kind of support is available in Zuul for that?
  • Can you describe the project architecture?
    • What aspects of the architecture enable it to scale to large projects and teams?
  • How difficult would it be to swap the Ansible integration for another orchestration tool?
  • What would be involved in adding support for additional version control systems?
  • What are your plans for the future of the project?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Keeping The Beets with Adrian Sampson - Episode 152

Summary

Maintaining a consistent taxonomy for your music library is a challenging and time consuming endeavor. Eventually you end up with a mess of folders and files with inconsistent names and missing metadata. Beets is built to solve this problem by programmatically managing the tags and directory structure for all of your music files and providing a fast lookup when you are trying to find that perfect song to play. Adrian Sampson began the project because he was trying to clean up his own music collection and in this episode he discusses how the project was built, how streaming media is affecting our relationship to digital music, and how he envisions Beets position in the ecosystem in the future.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app. And now you can deliver your work to your users even faster with the newly upgraded 200 GBit network in all of their datacenters.
  • If you’re tired of cobbling together your deployment pipeline then it’s time to try out GoCD, the open source continuous delivery platform built by the people at ThoughtWorks who wrote the book about it. With GoCD you get complete visibility into the life-cycle of your software from one location. To download it now go to podcatinit.com/gocd. Professional support and enterprise plugins are available for added piece of mind.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Your host as usual is Tobias Macey and today I’m interviewing Adrian Sampson about Beets, the swiss army knife for managing your music library.

Interview

  • Introductions
  • How did you get introduced to Python?
  • What is Beets and what was your reason for creating it?
    • What was your reason for using Python and if you were to start over today would you make the same choice?
  • If I have a directory with inconsistent naming conventions, poor organization, and some random folders full of mixed MP3 files how can Beets help me and what does the workflow look like?
  • How is Beets architected to allow for interactively processing a large volume of media files and how has the design evolved over the time that you have been working on it?
  • What are your thoughts on the current trend toward streaming music services replacing local media files?
  • What have been some of the most challenging aspects of building Beets?
  • What are some of the most interesting uses for Beets that you have seen?
  • What are some of the other projects for managing a music library and how does Beets compare to them?
  • Are there any features that you have planned for the future of Beets, or any new functionality that you would like to see contributed?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

MonkeyType with Carl Meyer and Matt Page - Episode 146

Summary

One of the draws of Python is how dynamic and flexible the language can be. Sometimes, that flexibility can be problematic if the format of variables at various parts of your program is unclear or the descriptions are inaccurate. The growing middle ground is to use type annotations as a way of providing some verification of the format of data as it flows through your application and enforcing gradual typing. To make it simpler to get started with type hinting, Carl Meyer and Matt Page, along with other engineers at Instagram, created MonkeyType to analyze your code as it runs and generate the type annotations. In this episode they explain how that process works, how it has helped them reduce bugs in their code, and how you can start using it today.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app. And now you can deliver your work to your users even faster with the newly upgraded 200 GBit network in all of their datacenters.
  • If you’re tired of cobbling together your deployment pipeline then it’s time to try out GoCD, the open source continuous delivery platform built by the people at ThoughtWorks who wrote the book about it. With GoCD you get complete visibility into the life-cycle of your software from one location. To download it now go to podcatinit.com/gocd. Professional support and enterprise plugins are available for added piece of mind.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • A few announcements before we start the show:
    • There’s still time to get your tickets for PyCon Colombia, happening February 9th and 10th. Go to pycon.co to learn more and register.
    • There is also still time to register for the O’Reilly Software Architecture Conference in New York Feb 25-28. Use the link podcastinit.com/sacon-new-york to register and save 20%
    • If you work with data or want to learn more about how the projects you have heard about on the show get used in the real world then join me at the Open Data Science Conference in Boston from May 1st through the 4th. It has become one of the largest events for data scientists, data engineers, and data driven businesses to get together and learn how to be more effective. To save 60% off your tickets go to podcastinit.com/odsc-east-2018 and register.
  • Your host as usual is Tobias Macey and today I’m interviewing Carl Meyer and Matt Page about MonkeyType, a system to collect type information at runtime for your Python 3 code

Interview

  • Introductions
  • How did you get introduced to Python?
  • What is MonkeyType and how did the project get started?
  • How much overhead does the MonkeyType tracing add to the running system, and what techniques have you used to minimize the impact on production systems?
  • Given that the type information is collected from call traces at runtime, and some functions may accept multiple different types for the same arguments (e.g. add), do you have any logic that will allow for combining that information into a higher-order type that gets set as the annotation?
  • How does MonkeyType function internally and how has the implementation evolved over the time that you have been working on it?
  • Once the type annotations are present in your code base, what other tooling are you using to take advantage of that information?
  • It seems as though using MonkeyType to trace your running production systems could be a way to inadvertantly identify dead sections of code that aren’t being executed. Have you investigated ways to use the collected type information perform that analysis?
  • What have been some of the most challenging aspects of building, using, and maintaining MonkeyType?
  • What have been some of the most interesting or noteworthy things that you have learned in the process of working on and with MonkeyType?
  • What have you found to be the most useful and most problematic aspects of the typing capabilities provided in recent versions of Python?
  • For someone who wants to start using MonkeyType today, what is involved in getting it set up and using it in a new or existing codebase?
  • What features or improvements do you have planned for future releases of MonkeyType?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Golem: End-To-End Test Automation Framework with Luciano Renzi - Episode 137

Summary

The importance of testing your software is widely talked about and well understood. What is not as often discussed is the different types of testing, and how end-to-end tests can benefit your team to ensure proper functioning of your application when it gets released to production. This week Luciano Renzi shares the work that he has done on Golem, a framework for building and executing an automation suite to exercise the entire system from the perspective of the user. He discusses his reasons for creating the project, how he things about testing, and where he plans on taking Golem in the future. Give it a listen and then take it for a test drive.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app. And now you can deliver your work to your users even faster with the newly upgraded 200 GBit network in all of their datacenters.
  • If you’re tired of cobbling together your deployment pipeline then it’s time to try out GoCD, the open source continuous delivery platform built by the people at ThoughtWorks who wrote the book about it. With GoCD you get complete visibility into the life-cycle of your software from one location. To download it now go to podcatinit.com/gocd. Professional support and enterprise plugins are available for added piece of mind.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Your host as usual is Tobias Macey and today I’m interviewing Luciano Renzi about Golem, a framework and automation tool for end-to-end testing in Python

Interview

  • Introductions
  • How did you get introduced to Python?
  • What is golem and what motivated you to create it?
    • What was your inspiration for the name?
  • Why did you choose to use Python for Golem and if you were to start over today would you make the same choice?
  • For someone who is unfamiliar with the concept, can you describe what end-to-end testing is and the reasons for making it part of their development process?
  • What is the main goal of Golem
  • What does the internal architecture and implementation of Golem look like and how has that evolved from when you first started the project?
  • How does Golem compare to other Python libraries for automated browser testing and what was lacking in the existing solutions when you created it?
  • What are the differences between golem and robot framework?
  • What about projects written in other languages such as protractor?
  • One of the intriguing features of Golem is the web interface for constructing tests. What are the benefits of codeless automation & record-playback functionality?
  • What are some of the most challenging aspects of building and maintaining Golem?
  • It seems that every browser automation library is ultimately a wrapper around Selenium. Why is a wrapper necessary and why haven’t any strong alternatives been created?
  • What are the advantages of making Golem a framework for test automation, rather than a library?
  • What are some of the most interesting or unexpected uses for Golem that you have seen?
  • What do you have planned for the future of Golem?
  • What is the current state of end to end automation and how do you see it evolving in the future?
  • How do you think machine learning and AI will be used in test automation?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Rasa: Build Your Own AI Chatbot with Joey Faulkner - Episode 134

Summary

With the proliferation of messaging applications, there has been a growing demand for bots that can understand our wishes and perform our bidding. The rise of artificial intelligence has brought the capacity for understanding human language. Combining these two trends gives us chatbots that can be used as a new interface to the software and services that we depend on. This week Joey Faulkner shares his work with Rasa Technologies and their open sourced libraries for understanding natural language and how to conduct a conversation. We talked about how the Rasa Core and Rasa NLU libraries work and how you can use them to replace your dependence on API services and own your data.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app. And now you can deliver your work to your users even faster with the newly upgraded 200 GBit network in all of their datacenters.
  • If you’re tired of cobbling together your deployment pipeline then it’s time to try out GoCD, the open source continuous delivery platform built by the people at ThoughtWorks who wrote the book about it. With GoCD you get complete visibility into the life-cycle of your software from one location. To download it now go to podcatinit.com/gocd. Professional support and enterprise plugins are available for added piece of mind.
  • Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • Your host as usual is Tobias Macey and today I’m interviewing Joey Faulkner about Rasa Core and Rasa NLU for adding conversational AI to your projects.

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by explaining the goals of Rasa as a company and highlighting the projects that you have open sourced?
  • What are the differences between the Rasa Core and Rasa NLU libraries and how do they relate to each other?
  • How does the interaction model change when going from state machine driven bots to those which use Rasa Core and what capabilities does it unlock?
  • How is Rasa NLU implemented and how has the design evolved?
  • What are the motivations for someone to use Rasa core or NLU as a library instead of available API services such as wit.ai, LUIS, or Dialogflow?
  • What are some of the biggest challenges in gathering and curating useful training data?
  • What is involved in supporting multiple languages for an application using Rasa?
  • What are the biggest challenges that you face, past, present, and future, building and growing the tools and platform for Rasa?
  • What would be involved for projects such as OpsDroid, Kalliope, or Mycroft to take advantage of Rasa and what benefit would that provide?
  • On the comparison page for the hosted Rasa platform it mentions a feature of collaborative model training, can you describe how that works and why someone might want to take advantage of it?
  • What are some of the most interesting or unexpected uses of the Rasa tools that you have seen?
  • What do you have planned for the future of Rasa?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Cloud-Init with Scott Moser - Episode 126

Summary

Server administration is a complex endeavor, but there are some tools that can make life easier. If you are running your workload in a cloud environment then cloud-init is here to help. This week Scott Moser explains what cloud-init is, how it works, and how it became the de-facto tool for configuring your Linux servers at boot.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
  • Need to learn more about how to scale your apps or learn new techniques for building them? Pluralsight has the training and mentoring you need to level up your skills. Go to www.pythonpodcast.com/pluralsight to start your free trial today.
  • Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
  • To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
  • If you work with data for your job or want to learn more about how open source is powering the latest innovations in data science then make your way to the Open Data Science Conference, happening in London in October and San Francisco in November. Follow the links in the show notes to register and help support the show in the process.
  • Your host as usual is Tobias Macey and today I’m interviewing Scott Moser about cloud-init, a set of python scripts and utilities to make your cloud images be all they can be!

Interview

  • Introductions
  • How did you get introduced to Python?
  • What is cloud-init and how did the project get started?
  • Why was Python chosen as the language for implementing cloud-init?
  • How has cloud-init come to be the de-facto utility for managing cloud instances across vendors and distributions?
  • Are there any viable competitors to cloud-init? coreos-cloudinit, some others.
  • How much overlap is there between cloud-init and configuration management tools such as SaltStack, Ansible, Chef, etc.
  • How have you architected cloud-init to allow for compatibility across operating system distributions?
  • What is the most difficult or complex aspect of building and maintaining cloud-init? [os integration, networking, goal of “do stuff without reboot”]
  • Given that it is used as a critical component of the production deployment mechanics for a large number of people, how do you ensure an appropriate level of stability and security while developing cloud-init?
  • How do you think the status of cloud-init as a Canonical project has affected the level of contributions that you receive?
  • How much of the support and roadmap is contributed by individual vs corporate users such as AWS and Azure?
  • What are some of the most unexpected or creative uses of cloud-init that you have seen? [https://wiki.ubuntu.com/OpenCompute “disposable use os”]
  • In your experience, what has been the biggest stumbling block for new users of cloud-init?
  • Do you have any notable features or improvements planned for the future of cloud-init, or do you feel that it has reached a state of feature-completeness?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

opsdroid with Jacob Tomlinson - Episode 124

Summary

Server administration is an activity that often happens in an isolated context in a terminal. ChatOps is a way of bringing that work into a shared environment and unlocking more collaboration. This week Jacob Tomlinson talks about the work he has done on opsdroid, a new bot framework targeted at tying together the various services and environments that modern production systems rely on.

Preface

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at www.podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app.
  • Need to learn more about how to scale your apps or learn new techniques for building them? Pluralsight has the training and mentoring you need to level up your skills. Go to www.pythonpodcast.com/pluralsight to start your free trial today.
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  • Your host as usual is Tobias Macey and today I’m interviewing Jacob Tomlinson about opsdroid

Interview

  • Introductions
  • How did you get introduced to Python?
  • What is opsdroid and what was the problem that you were trying to solve when you started the project?
  • What led you to choose Python as the language for implementing opsdroid?
  • What did you find lacking in the multitude of other chat bots that necessitated starting a new project? (e.g. Hubot, Errbot, Lita)
  • One of the main features that you list in the documentation is the ease of installation. Why is that such an important aspect of the project and how is that implemented?
  • What has been the most interesting and the most challenging aspect of implementing opsdroid?
  • On the opsdroid organisation on GitHub there are many repositories for plugin modules. Do you see this being a management issue in the long term?
  • How is opsdroid architected and what were the system requirements that led to the current system design?
  • How do you manage authorization and authentication for performing commands against your production infrastructure in a group chat environment?
    • What are some of the other security implications that users should be aware of when deploying a bot for interfacing with their deployment environment?
  • How does a chat-oriented bot framework differ from those that are being created for voice-oriented interaction?
  • What do you have planned for the future of opsdroid?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA