Agile + DevOps USA 2024 - Architecture - Design
Customize your Agile + DevOps USA 2024 experience with sessions covering architecture and design.
Tuesday, October 15
MLOps: DevOps for Machine Learning
Much attention is given to machine learning model training and testing in the industry. While these activities are essential for producing a production-ready machine learning model, organizations face some critical business challenges that must be addressed when building and testing machine learning models. Things like the reproducibility of results, accuracy of predictions, reusability of components, and trackability of experimentation are all vital to the success of any application. The term MLOps has emerged as a method for applying DevOps practices and automation to the machine...
Wednesday, October 16
Everything Old Is New Again: Using What We Already Know for a Safer Future
Our world is filled with complexities and unknowns, and when these collide with emerging technologies, the resulting risk seems insurmountable. We accept this increased risk as a cost of using the new technology, assuming that previous lessons learned don’t apply and that a blank slate is required to gain the most benefit. However, this never turns out to be true. Time and time again, we realize that much of what we already know is still relevant to these emerging technologies, regardless of how advanced or paradigm-shifting they are. This is good news for reducing the risk in innovation...
Scale Test Environments Using Cloud Infrastructure for Continuous Testing
PreviewThe challenges of managing test environments in the fast-paced world of software development are numerous, ranging from complexity and resource limitations. Traditional on-premises solutions often offer limited scalability and cause bottlenecks that hinder continuous testing. This presentation tackles these challenges head-on by proposing a shift to cloud-based test environments underpinned by Infrastructure as Code. By embracing the cloud, organizations can dynamically create and tear down test environments as needed, freeing up valuable resources. Integration with CI/CD pipelines...
Designing Resilient Event-Driven Data Mesh Architecture
Most enterprises deal with large scale data. There are common challenges involved in managing data. One such challenge faced by distributed applications is effective processing, identifying transactional boundaries, and exchange of data across disparate systems, where governance, modeling, ownership, and consumption considerations are tenets. An event-driven data mesh provides capabilities to power both operational & analytical use cases, in both real time & batch. It provides the framework necessary for creating, communicating, and using data. In request-response architecture,...
AI & The Impact on How We Work
Our industry has been transformed by new technologies, radically changing how we work. Thirty years ago, deployment cycles took 3-5 years; today, they happen in seconds. This rapid pace is largely due to our focus on investing in tools that boost developer productivity. We're still driven to create tools that simplify developers' work and make it easier for others to join the field. Many companies are heavily invested in enhancing productivity. However, the abundance of productivity tools doesn't automatically lead to increased productivity. Companies need to examine and adapt their...
Continuous Integration of AWS Serverless Applications
The primary draw for implementation of AWS serverless applications is the supposed simplicity. Anyone that has attempted to implement testing within a CI pipeline on a serverless application, however, knows that it is anything but simple. Serverless technologies allow for the faster construction of more complex applications with more complex integrations while also providing new technologies and execution environments, all of which pose a challenge to those used to testing in a more traditional way. This presentation looks at an API-based serverless application as an example and introduces...
Gen AI: A Co-Pilot to Better Value Sooner, Safer, and Happier in Digital Transformation
Integrating Generative AI (Gen AI) across the Software Development Life Cycle (SDLC) signifies a pivotal shift in digital product development, promising enhancements from planning to maintenance. This session explores this cutting-edge approach, revealing Gen AI's capacity to automate tasks, refine product quality, and elevate non-functional attributes like security and usability. From analyzing user feedback for feature development to auto-generating code and optimizing deployment strategies, Gen AI streamlines processes, boosts efficiency, and ensures robust, user-centric products. It...
Panel: How AI is Revolutionizing the Entire SDLC
Artificial Intelligence is transforming the software development life cycle, reshaping processes, and redefining best practices across the board. This is not just a trend—it's a game-changer. Join our dynamic panel of top-tier experts representing Agile, DevOps, software testing, security, and product development as they dive into how AI is impacting everything from code to culture. What does this mean for your projects, teams, and career? Bring your questions, and together we'll explore the challenges and opportunities AI brings to software development. We’ll use Slido to collect your...
Thursday, October 17
Agile and DevOps Leadership
In the dynamic landscape of software development, agile and DevOps methodologies have emerged as cornerstones for achieving efficiency, innovation, and customer satisfaction. However, successful implementation requires adept leadership capable of navigating multifaceted challenges. During this session, Vijay will delve into common hurdles faced by leaders in agile and DevOps transformations. For instance, envision a scenario where a large enterprise embraces agile but struggles with traditional hierarchical structures. This creates tension between established protocols and agile's...