Infrastructure & Ops Superstream Series: What's Next for Infrastructure and Operations?
Published by O'Reilly Media, Inc.
What’s in store for infrastructure and operations in the future? Where’s the field headed? And what technologies will take us there?
Join us for a live event covering some of the key changes you can expect to see in the world of infrastructure and operations. You’ll learn about the trends and new technologies that will shape how you deliver software and meet the needs of your business and customers in the coming years, with a focus on the emerging ideas and tools that you can make use of right now. Whether you’re looking for cutting-edge techniques for today or want to get ahead of the game for tomorrow, this is the event for you.
About the Infrastructure & Ops Superstream Series: This five-part series of half-day online events details what you need to know to effectively manage existing legacy systems while migrating to modern, scalable, cost-effective infrastructures—with no interruption to your business. Each event day covers some of the most challenging and promising topics facing those working in infrastructure and operations today: continuous integration and delivery, cloud delivery, Kubernetes, microservices, and security.
What you’ll learn and how you can apply it
- Explore the technologies that will shape the future of infrastructure and operations
- Learn how to employ new technologies and stay ahead of the curve
This live event is for you because...
- You’re a developer who wants to know what’s coming next for infrastructure and operations.
- You want to better understand new technologies such as data mesh and eBPF.
- You need to apply continuous delivery principles to make the end-to-end process of developing and deploying ML systems more repeatable and reliable.
Prerequisites
- Come with your questions
- Have a pen and paper handy to capture notes, insights, and inspiration
Recommended follow-up:
- Read Data Mesh (book)
- Read Container Security (book)
- Read Building Machine Learning Pipelines (book)
- Read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, second edition (book)
- Read Linux Observability with BPF (book)
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Sam Newman: Introduction (5 minutes) - 7:00am PT | 10:00am ET | 3:00pm UTC/GMT
- Sam Newman welcomes you to the Infrastructure & Ops Superstream.
Liz Rice: A Beginner's Guide to eBPF (45 minutes) - 7:05am PT | 10:05am ET | 3:05pm UTC/GMT
- eBPF is an exciting technology that enables running bespoke programs directly in the kernel—it’s been described as “superpowers for Linux.” Recently we’ve seen an explosion of tools that use eBPF to power observability, security, and more. Liz Rice uses live-coding examples to walk you through how eBPF programs are loaded and run in the kernel and how user-space code can communicate with them to extract valuable information.
- Liz Rice is chief open source officer at cloud native networking and security specialist Isovalent, creator of the Cilium eBPF-based networking project. She’s chair of the CNCF's Technical Oversight Committee and was cochair of KubeCon + CloudNativeCon in 2018. Liz is the author of Container Security, from O'Reilly. She has a wealth of software development, team, and product management experience from working on network protocols and distributed systems and in digital technology sectors such as VOD, music, and VoIP. When not writing code or talking about it, Liz loves riding bikes in places with better weather than her native London and competing in virtual races on Zwift.
- Break (10 minutes)
Zhamak Dehghani: Introduction to data mesh infrastructure (55 minutes) - 8:00am PT | 11:00am ET | 4:00pm UTC/GMT
- Join Zhamak Dehghani for a special discussion on data mesh, a paradigm shift in big data management that draws from modern distributed architecture: considering domains as the first-class concern, applying self-sovereignty to distribute the ownership of data, applying platform thinking to create self-serve data infrastructure, and treating data as a product. You’ll hear what led her to develop data mesh, her observations on the failure modes of a centralized paradigm of a data lake and its predecessor, the data warehouse, and more. Along the way, she’ll recount some of the challenges she’s faced during her career and shed light on the things that worked well and those that didn’t.
- Zhamak Dehghani is a principal consultant at ThoughtWorks focused on distributed systems architecture and digital platform strategy for the enterprise. She’s a member of the ThoughtWorks Technology Advisory Board and contributes to the creation of the ThoughtWorks Technology Radar. Zhamak has worked as a software engineer and architect for 20 years in the areas of distributed computing communications and embedded device technologies and has contributed to multiple patents on embedded mobile sensing devices.
- Break (10 minutes)
Ted Young: Getting Started with OpenTelemetry (45 minutes) - 9:05am PT | 12:05pm ET | 5:05pm UTC/GMT
- Ted Young offers an intro to OpenTelemetry. You’ll explore OpenTelemetry’s core components and see how they all fit together to provide flexible and robust observability. You’ll then learn the easiest way to set up and deploy OpenTelemetry across your entire system.
- Ted Young is one of the founders of the OpenTelemetry project and the director of developer education at Lightstep. He’s spent the last 15 years building distributed systems in a variety of environments, including computer animation, national elections, and elastic compute platforms. Currently he’s focused on distributed tracing and tools for root cause analysis.
- Break (15 minutes)
Danilo Sato: Continuous Delivery for Machine Learning (50 minutes) - 10:05am PT | 1:05pm ET | 6:05pm UTC/GMT
- Machine learning applications are growing increasingly popular in our industry. But the process for developing, deploying, and continuously improving them is more complex than that of more traditional software, such as web services and mobile applications. Continuous delivery for machine learning (CD4ML) is the discipline of bringing continuous delivery principles and practices to machine learning applications. Danilo Sato offers an overview of CD4ML and its technical components, shares his industry experience implementing CD4ML, and explores the future challenges that need to be solved.
- Danilo Sato is a principal consultant at ThoughtWorks with experience in many areas of architecture and engineering, including software, data, infrastructure, and machine learning. He’s the author of DevOps in Practice: Reliable and Automated Software Delivery as well as a member of the ThoughtWorks Technology Advisory Board and the company’s Office of the CTO.
Sam Newman: Closing Remarks (5 minutes) - 10:55am PT | 1:55pm ET | 6:55pm UTC/GMT
- Sam Newman closes out today’s event.
Your Host
Sam Newman
Sam Newman is a technologist focusing on the areas of cloud, microservices, and continuous delivery—three topics which seem to overlap frequently. He provides consulting, training, and advisory services to startups and large multinational enterprises alike, drawing on his more than 20 years in IT as a developer, sysadmin, and architect. Sam is the author of the best-selling Building Microservices (now in its second edition) and Monolith To Microservices, both from O’Reilly, and is also an experienced conference speaker.