Agenda
Industry leaders, practitioners, experts, SRE and developers are gathering to share and learn at this virtual conference
VP Product Management
Harish Doddala is currently VP Product Management at Harness, where he spearheads the development of new products and businesses, including the company's AI strategy. Before joining Harness, Harish held leadership positions in helping lead analytics product management at UiPath and AppDynamics, contributing significantly to their growth pre/post-IPO. Harish started his career in machine learning having built NLP systems, and published research in speech coding and language technologies at IBM Research labs and holds a Masters Degree from MIT.
Al and Software: The Good, The Bad, The Scary
Artificial intelligence is becoming an integral part of our lives, revolutionizing various industries and transforming the way we interact with technology. Especially for the DevOps community as they leverage automation via machine learning and generative AI to expedite code creation. However, while AI has brought numerous benefits, it also raises concerns about its potential negative impacts.
The Good: AI has the power to enhance efficiency and productivity across various sectors. It can automate repetitive tasks and generate code at an exponential rate, freeing up developer resources for more creative and complex endeavors.
The Bad: There is an explosion of code, but maintainability of the code, associated costs, and security can be hard. Which means unnecessary toil is still stealing roughly 40% of development time. Organizations are also struggling to understand what the technology stack and required skill sets of the future will be considering the pervasiveness of AI.
The Scary: Despite its advantages, AI also presents certain challenges and drawbacks. Most notably, security and privacy are major issues as AI systems often require access to vast amounts of data, raising concerns about data sovereignty and misuse.
To explore these issues and more, Latha Srinivasan Director of Cloud Engineering at HPE, Vrushali Joshi, Director of Software Engineering at Taco Bell, Sean Corkum, Director of DevOps Platform at Marriott, and Harish Doddala, VP of Product Management at Harness, sit down for a fireside chat to help organizations navigate the emerging world of AI for DevOps.
VP Product Management
Harish Doddala is currently VP Product Management at Harness, where he spearheads the development of new products and businesses, including the company's AI strategy. Before joining Harness, Harish held leadership positions in helping lead analytics product management at UiPath and AppDynamics, contributing significantly to their growth pre/post-IPO. Harish started his career in machine learning having built NLP systems, and published research in speech coding and language technologies at IBM Research labs and holds a Masters Degree from MIT.
Head of Engineering - Backstage
Helen Greul, Head of Engineering for Backstage at Spotify, is a results-driven and collaborative engineering leader with over 15 years of experience, including a decade in general management. She has a proven track record of building and leading autonomous R&D teams in multinational environments, with expertise in strategic initiatives, value optimization, and growth. Helen's well-rounded background encompasses products, business development, and GTM partnerships, enabling her to translate user needs into innovative solutions and scalable revenue. Notable achievements include building and leading engineering departments from startups to IPOs, establishing disciplined functions at Spotify, and fostering healthy, happy remote teams. As a community builder, Helen actively contributes to the growth of the Backstage developer community, emphasizing the importance of teamwork, trust-building, and alignment with customer needs.
The Rise of Internal Developer Portals and the Future with AI
If you are part of a tech-driven business, the productivity and satisfaction of developers is critical for your success. The most common challenges faced by developers today in large organizations are slow and manual processes, prolonged project kick-offs, and a dire lack of automation that hampers performance and disrupts the flow state that keeps developers productive. Moreover, the absence of standardized practices leads to chaos and fragmentation. Lack of visibility within the internal software ecosystem impedes knowledge sharing and discovery.
Join Helen Greul, Head of Engineering for Backstage at Spotify, and Himanshu Mishra, Product Manager for Harness IDP, in a conversation about Developer Experience and Internal Developer Portals. They will discuss the history and influence of the Backstage project, open sourced by Spotify and donated to CNCF - one of the fastest growing projects for building developer portals. They will also discuss the future of IDPs, Developer Experience and the role of AI has to play in the journey.
Head of Engineering - Backstage
Helen Greul, Head of Engineering for Backstage at Spotify, is a results-driven and collaborative engineering leader with over 15 years of experience, including a decade in general management. She has a proven track record of building and leading autonomous R&D teams in multinational environments, with expertise in strategic initiatives, value optimization, and growth. Helen's well-rounded background encompasses products, business development, and GTM partnerships, enabling her to translate user needs into innovative solutions and scalable revenue. Notable achievements include building and leading engineering departments from startups to IPOs, establishing disciplined functions at Spotify, and fostering healthy, happy remote teams. As a community builder, Helen actively contributes to the growth of the Backstage developer community, emphasizing the importance of teamwork, trust-building, and alignment with customer needs.
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Vice President, Cyber Risk & Governance
De-risking Deployments in an AI World
Artificial intelligence (AI) has revolutionized the way developers generate code, offering a range of powerful tools and techniques that streamline the development process and enhance productivity. More specifically, developers now have access to advanced algorithms and models that can assist in code generation, making their work more efficient and effective.
However, though often overlooked, monitoring AI-generated code for malicious elements is of utmost importance in today's digital landscape. As AI continues to advance, it has become increasingly capable of generating complex and sophisticated code. While this brings numerous benefits and advancements, it also poses significant risks if not properly monitored.
With that said, we want to help organizations get educated on the current threat landscape and protect themselves against emerging threats they may not be aware of. This session will focus on how we got here, followed by a detailed discussion of how to de-risk deployments for AI generated code.
Vice President, Cyber Risk & Governance
Break
Transforming Developer Platforms with Generative AI
There is so much talk about using generative AI for code generation. And while GenAI has truly been a game changer for developers from this aspect, it only addresses roughly 25% of the scope of the developer workload. The tasks that really add to developer toil are elsewhere in the software development lifecycle (SDLC).
Software developers spend equally significant amounts of time building, testing, refactoring their code, fixing security issues, and documentation. AI needs to be utilized across the SDLC in order to truly become a force multiplier for developers.
With that said, Wes Whitlam, Director of Software Engineering at Rockwell Automation, Nick Colyer, VP of Digital Engineering at AHEAD, and Srinivas Bandi, VP of Product & Engineering at Harness, explore how organizations can utilize generative AI to transform developer platforms and reduce toil across the entire software development lifecycle.
Amazon Web Services
Harness
Al Augmented DevOps for the Cloud
Traditional approaches to DevOps and cloud scaling present several challenges for developers – most notably around resource management, CI/CD delays, and a lack of real-time security monitoring. The repercussions of these challenges can be severe.
Without proper monitoring and optimization, organizations overprovision and underutilize their resources. Slow and cumbersome delivery pipelines can lead to delays in delivering new features and bug fixes, impacting the organization's competitiveness. Additionally, security breaches have serious consequences, including legal liabilities and financial penalties. By leveraging AI technologies, organizations can streamline their development processes, enhance scalability, and proactively address security vulnerabilities.
With that said, James Bland, Global Tech Leader of DevOps at Amazon Web Services (AWS), and Paige Johnson Senior Director, Global Cloud Platform Alliances at Harness, discuss how Al augmented DevOps enables intelligent resource allocation and optimization in the cloud. They will explore how AI-based automation tools can streamline the CI/CD pipeline by automating repetitive tasks, such as code testing, building, and deployment – while autonomously mitigating security incidents.
Co-Author of the DevOps Handbook
Scaling the Delivery of AI Applications
GenAI is the bright shiny object that everyone is focused on in some capacity. And much of our event today is tailored around how AI can be utilized to reduce developer toil. But for this session, we’re going to flip things around and discuss how we can use DevOps to deliver GenAI.
Join the “Father of DevOps” Patrick Dubois and Harness CEO Jyoti Bansal in this intimate conversation about the transformational journey organizations are on delivering GenAI apps. They will explore the business considerations organizations need to make, specifically around cost, privacy, legal, and organizational structure.
They will also take a deep dive into the tools landscape and share thoughts around what organizations need for development, testing, operations, and observability. The session will close with both reflecting on the implications of GenAI and its significance in the ever-evolving landscape of technology.
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