Agile + DevOps East 2023 - DevOps Automation
Monday, November 6
A Quality Engineering Introduction to AI and Machine Learning
Although there are several controversies and misunderstandings surrounding AI and machine learning, one thing is apparent — people have quality concerns about the safety, reliability, and trustworthiness of these types of systems. Not only are ML-based systems shrouded in mystery due to their largely black-box nature, they also tend to be unpredictable since they can adapt and learn new things at runtime. Validating ML systems is challenging and requires a cross-section of knowledge, skills, and experience from areas such as mathematics, data science, software engineering, cyber-security,...
How to DevOps Your Testing Strategy – An Exercise in Value Stream Analysis
The DevOps movement is here. Companies across many industries are breaking down siloed IT departments and federating them into product development teams. Testing and its practices are at the heart of these changes. Traditionally, IT organizations have been staffed with mostly manual testers and a limited number of automation and performance engineers. To keep pace with development in the new “you build it, you own it” environment, testing teams and individuals must develop new technical skills and even embrace coding to stay relevant and add greater value to the business. DevOps really...
Leveraging Generative AI for Software Productivity
Executive leaders across the globe have been asking a relatively simple yet profound question: Can we leverage generative AI to transform our business, enterprise, or industry? For software-based companies, focus has either been on differentiating their product and service offerings using this new technology. But how about leveraging generative AI to improve team productivity and efficiency? This may be possible but how do you measure its success? What are some of the key use cases within business analysis, development, and testing that software teams can use? Are there any pitfalls...
Tuesday, November 7
Supercharge Your Workflow: To GitHub and Beyond
Whether you are new or experienced with GitHub this class is for you! Supercharging your workflow caters to anyone who wants to enhance their Agile and DevOps process with the capabilities of GitHub. GitHub has long been the premier site for open-source projects and is now turning a pivotal corner into becoming the predominant platform for all aspects of the development lifecycle. Some examples of this include; protecting company code through various GitHub Products or curating marketplace actions and workflows prior to use. This tutorial will look at how to leverage GitHub Actions (CI/CD...
Prioritizing Like a Pro: Designing and Executing Defensible Ordering Strategies
Effective prioritization is critical to wring the most out of agility. When you’re just delivering once, ordering matters little. However, when the option to release on a regular basis is available, what you do sooner rather than later can have huge impacts on value realization, risk mitigation, and more. However, prioritization is much easier in theory than in practice for most organizations. Arlen has been a practicing agilist for over two decades. Working with hundreds of clients and teaching thousands of students how to effectively prioritize is one of the most frequently raised topics...
Designing (Much) Better Agile Meetings
Many teams have been following the same few patterns for facilitating sessions such as Daily Scrums, Sprint Reviews, Retrospectives, and backlog refinement events for decades now. However, while these well-trodden approaches can be good starting points, there are ways to make them tremendously more effective with minimal effort. You will learn to design agile meetings that account for your particular circumstances and goals while wasting as little time as possible. First, Arlene will cover Exploring the True Purpose of Agile Meetings – Is the Daily Scrum more about status or planning? Is...
Wednesday, November 8
We Got Our Monolith to Move at Light Speed
PreviewIn the financial industry, investment in modernization can take a long time to gain support which slows down momentum for change. While the industry focuses on the next hottest technology, many of us simultaneously continue to own, run, and operate legacy systems. How do we adopt a DevOps culture around a legacy system? How do you evolve the legacy mindset to embrace modernization? Modernization is not solely an application evolution; it is a mindset as well. Embracing a DevOps culture is not technology dependent, it is people dependent. Teaching people the right tools and...
High Octane DevOps: Supercharged CI/CD Pipelines
To reinvent the wheel is to attempt to duplicate, most likely with inferior results and technical debts. Within a large-scale organization the true cost of CI/CD is the toil involved when effort is repeated to create the same or similar pipeline functionality. What Prashant and March discovered during a CI/CD journey is that the key to creating powerful and efficient CI/CD or automation testing pipelines is in not writing pipeline logic at all. The formula that was unlocked is in focusing on the atomic level of the reusable code within pipeline stages. By harnessing the power of creating...
Implementing DevOps Automation: Best Practices and Common Mistakes
Most organizations adopting the cloud have adopted DevOps automation to some degree or another. The primary reason is that continued manual maintenance isn't possible with the same staffing level and increased demand. In short, DevOps automation and cloud consumption are much more than just technology change. They require a fundamental rethinking of how we do things. It's common for DevOps team members to be negatively impacted by the changes others have made. It's common for team members to cause problems by making changes manually instead of through code. Derek has seen managers grow...
AI in DevOps for Improving Engineering Team Productivity
AI and machine learning continue to be hot topics everywhere. The majority of discussions on AI/ML are focused on how generative AI and large language models (LLMs) will change the world. However, LLMs like ChatGPT, Bard, and Llama only represent one area of modern advances in the AI/ML space. Considering the bigger picture of new AI technologies, Chris Navrides has been investigating ways to enable entire new areas of opportunity within the DevOps lifecycle. By leveraging AI in DevOps, he believes teams can improve developer productivity through better code authoring, debugging, and...
Continuous Security Compliance Realized: Reducing the Regulatory Burden with DevSecOps Automation
Most organizations are subject to the rules of an ever-increasing number of regulations, while dealing with rapidly escalating endpoints and environments to test. No matter the time and resources applied to an external assessment or audit, manual processes cannot keep pace with cloud scale and growing technical complexity of modern environments. This creates distractions for technical teams and contributes to delivery inefficiencies (reduced velocity) while also increasing the risk of “non-compliance” (adverse audit findings). A “continuous compliance” approach, empowered by modern DevOps...
Evolve Your Selenium Scripts Into Performance Scripts
You have implemented your site functional tests with Selenium. Now, how can you reuse some of these tests to verify that your site does not only work as expected with one user, but with a big load of them? In this talk, Roger Abelenda will show you a way to achieve this without leaving your IDE. Roger will do a live demo generating a load script using JMeter DSL, from an existing Selenium script. Then, he will run it in combination with the Selenium script to generate load and evaluate user experience while such load is being imposed. Join Roger, add JMeter DSL to your toolbox and let's...
DevSecOps in a Bottle—The Care and Feeding of Pocket Pipelines
PreviewDevSecOps techniques give us the power of receiving rapid feedback and the ability to incorporate new information on an ongoing basis. However, challenges arise when the development pipeline must be established without connection to external networks. There are excellent reasons for doing this, including reducing security risks to systems and proprietary data, but a little more consideration is required to provide our teams on pocket networks the same benefits of an end-to-end DevSecOps pipeline implementation for our container application. We will draw on our practical experience...
Thursday, November 9
Smooth Sailing: Navigating Release Management in the DevOps Landscape
Embark on an illuminating voyage with me ( Priyanka Halder) as we delve into Release Management's uncharted territory within the DevOps era. As a Quality Engineering Leader, I invite you to explore the synergy of agility and stability for triumphant software deliveries. We'll uncover strategies that steer us through challenges, nurture collaboration, and embrace evolution in this dynamic sphere. Unravel core DevOps principles, cultivate collaborative cultures, and refine robust release processes. Discover the pivotal role Release Management plays in bridging the agility-stability divide,...
Integrating FinOps with DevOps for Effective Cloud Cost Optimization and Governance
As enterprises operate in hybrid and multi-cloud environments, their operations teams have to continuously monitor multiple dashboards to keep track of cost, resource consumption, availability, security, etc., across different cloud service providers. There is an acute need for real-time and easy visibility into cloud costs so that everyone including development and testing teams can quickly identify idle resources, prevent virtual sprawl, and implement lifecycle policies. Enterprises also need automation of policy actions (e.g., auto termination of idle resources), anomaly detection,...
Generative AI in Quality Assurance
The need for a new test automation model has been an imperative over the last 10 years as we have moved from waterfall to agile and agile to DevOps. Moving from test coverage to application coverage and reducing test time from months to an hour or less has created a substantial pressure for full success. Now AI in test is a reality. The first generative AI offerings in QA became available in 2018 and since then marked improvements have been made in outcomes. This has changed QA teams' focus, tasks, and work effort. With the ultimate goal of AI finding all our bugs, the advent of...
AutoOps: Harnessing the Power of AI-Augmented Testing with Generative AI
In the rapidly evolving landscape of software development, Continuous Integration and Continuous Deployment (CI/CD) have emerged as pivotal methodologies for delivering high-quality software at an accelerated pace. To ensure the reliability and robustness of software releases in such an environment, the marriage of cutting-edge technologies becomes imperative. Incorporating Generative AI into business process automation seemed daunting just a few years ago. However, the availability and popularization of OpenAI/ChatGPT and other AI/ML technologies have made it a closer reality, and now it...