automation
Showing 12 out of 12 results
Expert Talk: War Stories from Moving to the Cloud
Are you a developer ready to embark on your cloud journey but feeling overwhelmed? Fear not! The benefits of the cloud far outweigh the initial struggles. With automation and proper monitoring, you can avoid sky-high bills while elevating your company and user experience to new heights. Don't miss out on the opportunity to learn from Lorna Jane Mitchell and Holly Cummins as they share their practical war stories from their own cloud migration and operations. Join us and take your development game to the next level!
Use Terraform to Scale your Team
In this talk we look at interesting ways to use `Terraform` to help scale companies and teams. As companies get bigger and hire more engineers, they can use automation to ease their growing pains. We take a look at a real world example using a custom Terraform provider to manage GitHub security. The goal is to make sure that only the appropriate engineers have the right level of access to the right repositories. We also need to ensure coding standards, security concerns are managed correctly and uniformly. Fortunately, Github has a great API which enables use to create our own Terraform provider to solve this problem using infrastructure as code! As part of this examination we will explore the inner workings of Terraform and how we can create our own custom providers. You will learn how to extend this principle to any infrastructure or resource that is backed by an API **Who should attend this talk:** Developers and engineers interested in: automation, infrastructure as code or software development life-cycle. **What will you learn from this talk:** You will understand how Hashicorp and the community manages providers, learn how to contribute to existing providers and how to extend Terraform to manage any infrastructure or configuration using your own custom providers
Forget Velocity, Let's Talk Acceleration
Velocity gives us motion in one direction. We want to work faster -- and more, we want to do the most useful work. We need acceleration: deliberate changes in speed and direction. How? The same way we accelerate our customers' work: automation! We already automate our work: from CI to our favorite editors to command-line aliases, we smooth our workflow. We can take this farther -- but should we? Where is the balance between racing forward, and tweaking our racecar? To achieve this, first look closely at our own work. A few observations give us data on what's really slowing us down. It may not be the technical debt you think it is: what hurts us is different from what we dislike. Next consider automation: it changes more than our speed. Jessica suggests more powerful justifications, up to generating contributions larger than our own productivity. Let's find the sticking points in our work, and then apply our superpowers of automation to change our own world, so that we can change our users' worlds, faster.
Automating Security & Compliance (for Fun & Profit)
The business demands innovation. IT infrastructure and application development agree. But of course it’s not that easy. Now the corporate security team would like to meet, and the auditors have a few words for you too. (Those words are “wait just a minute”.) How do we ensure that as we modernize, we don’t introduce unacceptable risk? Incorporating security and compliance into infrastructure updates from the beginning means we can forestall project-derailing last-minute roadblocks. Automated security and compliance tests are how we track and assess our risk levels as we release changes. I’ll demonstrate a live walkthrough of building a compliance testing profile based on an industry-standard CIS Benchmark. Learn how to codify compliance profiles, incorporate such compliance testing into your release automation processes, and keep your internal stakeholders saying “yes, and” instead of “no, because...”.
Automating for Acceleration with Atomist
Software Development is a thousand tasks. Can we save ourselves from some of the annoying ones? In this demo, Jessica and Russ get frustrated with some interrupting tasks, and refuse to do them. Build failed for some trivial reason? Let a bot fix it! Tests breakages in one project after updates in another? Let a bot find them! Don’t bother me until there’s a real decision to make. If you write bash scripts, you already have automations. Take these and make something the whole team can benefit from, a service that you provide but don’t perform. From a trivial tslint to spectacular chaos experiments, automation can be fun for you and generative for your team. Work with existing repos and build systems, listen to specific events across the development flow, and cast the high magic of development automation: coding across multiple repos in one movement. We want to hear what you would do with these powers. The Rock Star Developer is DEAD -- Long live the Rock Band Development Team through team automation.
Deploying code and resource to Microsoft Azure
Building great and scalable cloud services can be a challenging task. Picking the right architecture, tools and platform to support your requirements is hard, but it’s even more hard if you have limited insight into what is provided to you by the cloud vendor of your choice. This session targets you who want to get an introduction or update on how you deploy code or infrastructure to Microsoft Azure and what kind of services there are for you to choose from and how they apply to different architectural patterns. No matter if you are an experienced cloud developer/architect or just starting to get into the area, this session will probably have something for you and will be filled with live demos. Keywords: Cloud, APIs, Web, Micro Services, Actors, Automation
Fireside Chat: Brave New World of Software
Our world is rapidly changing. We can compute, analyze and optimize more, faster but how do we conquer this Brave New World? During this fireside chat, leading industry experts and top practitioners will share their insights on recent developments around Cloud Native, Data Science and more topics and how we can prepare ourselves for the future of software.
Dynamic Non-Events
As more automation rolls out and new software applications become a more critical part of our lives, the impact of failures increases. Safety is a critical attribute and one of the definitions of a safe system is that it has dynamic non-events. Whatever happens to it, it still works. I will illustrate with some examples, and discuss the new view of safety, as the ability to build systems that maintain a margin.
Simplification and Automation in Java: Yesterday, Today and Tomorrow
Rod will discuss how developing Java applications has changed and simplified over the past 15 years, and what may come next around automation and collaboration. What comes after convention over configuration?
Why You Need a Software Delivery Machine
Many teams have a clear vision of how they want their software delivery to work. For example, what checks and staging deployments should occur on commits; what approval steps are required before promotion to production; what code needs to be included in new projects and what provisioning should occur on project creation; and what policies matter around license files and security scanning. But it’s hard to realize that vision. Typical challenges include: * Growing proliferation of services, meaning many delivery pipelines that can’t easily be changed as one, and many repositories with dependencies, configuration and usage practices getting dangerously out of date. * Bringing on new developers, due to lack of effective knowledge sharing and lack of automation * Creating new projects without copy/paste, leading to wasted effort and inconsistency * Lack of visibility into the whole elephant. What is deployed where? What is at what version? What is happening across the organization? Who should be informed in the case of a production alert, and to what code does it relate? The solution to these software problems is more software. These problems can best be addressed together, through greater automation, backed by a model spanning development and delivery. It’s what we call a software delivery machine.
Code + AI: Will Robots Take Our Coding Jobs?" Machine Learning Applied to Programming
Machine learning is permeating every facet of our lives, from learning our preferences to self-driving cars, but what happens when you apply neural networks to code? How do you even view code as data? The key ideas are easy to summarize and fun to play with. This talk will provide an overview of fundamental concepts of machine learning, and then delve into how learning can be used to analyze and improve code. The talk will also provide pointers to available commercial and open source tools and discuss what’s been achieved so far (coding in English, context-aware code completion, automated Stack Overflow). The talk will close with speculation on where the field is going, and how machine learning won’t take our jobs, but hopefully will take over some of the repetitive work we don’t like doing.
Why You Need a Software Delivery Machine
Many teams have a clear vision of how they want their software delivery to work. For example, what checks and staging deployments should occur on commits; what approval steps are required before promotion to production; what code needs to be included in new projects and what provisioning should occur on project creation; and what policies matter around license files and security scanning. But it’s hard to realize that vision. Typical challenges include: * Growing proliferation of services, meaning many delivery pipelines that can’t easily be changed as one, and many repositories with dependencies, configuration and usage practices getting dangerously out of date. * Bringing on new developers, due to lack of effective knowledge sharing and lack of automation * Creating new projects without copy/paste, leading to wasted effort and inconsistency * Lack of visibility into the whole elephant. What is deployed where? What is at what version? What is happening across the organization? Who should be informed in the case of a production alert, and to what code does it relate? The solution to these software problems is more software. These problems can best be addressed together, through greater automation, backed by a model spanning development and delivery. It’s what we call a software delivery machine.
