In this episode, we welcome Alex Hidalgo and Brian Singer of nobl9 to discuss Service Level Objectives (SLOs). Alex and Brian talk about how SLOs can establish a vernacular across industry verticals, leading to constructive conversations and a shared understanding of how to implement SRE practices. Join us for a lively discussion that ranges across SLO topics!

In this episode, Steph Hippo, Platform Engineering Director at Honeycomb, joins The Prodcast to discuss AI and SRE.

Steph explains how observability helps us understand complex systems from their outputs, and provides a foundation for SRE to respond to system problems. This episode explains how AI and observability build a self-reinforcing loop. We also discuss how AI can detect and respond to certain classes of incidents, leading to self-healing systems and allowing SREs to focus on novel and interesting problems. She advises small businesses adopting AI to learn from others' mistakes (post-mortems) and to commit time and budget to experimentation.

In this special episode hosts Steve McGhee from the Google SRE Prodcast and Kaslin Fields from the Google Kubernetes Podcast, welcome Google Cloud Solutions Architect Ben Good to discuss platform engineering. Listeners can look forward to hearing about the role of Kubernetes as a tool for building platforms, how to create "golden paths" for developers, and the importance of observability and self-service in platform design. The conversation also touches on industry trends, the bespoke nature of platforms, and how DORA metrics can be applied to platform engineering practices.

Google Staff SRE Ramón Llamas and Google Software Engineer Swapnil Haria join our hosts to explore how AI agents are revolutionizing production management, from summarizing alerts and finding hidden errors to proactively preventing outages. Learn about the challenges of evaluating non-deterministic systems and the fascinating interplay between human expertise and emerging AI capabilities in ensuring robust and reliable infrastructure.

This episode features Google Technical Program Manager (TPM) Karanveer Anand, who joins our hosts to discuss the unique role of TPMs in Site Reliability Engineering (SRE). The conversation highlights how SRE TPMs bridge the gap between technical details and business impact, managing complex projects with inter-team dependencies and ensuring system reliability, particularly in the rapidly evolving AI landscape.

This episode discusses Systems Theoretic Process Analysis (STPA), a method for analyzing complex systems. Theo Klein, a Google SRE, and Jeffrey Snover, a Distinguished Engineer at Google, explain that STPA focuses on identifying how system accidents and losses occur due to a loss of control, rather than component failures. STPA helps identify design flaws early, even before code is written! The discussion highlights that STPA is a human-driven process, prompting critical questions about system goals and potential losses, and that Google is adapting the pure STPA approach for commercial software development to make it more practical and efficient.

In this episode, hosts Steve McGhee and Matt Siegler are joined by guest, Adam Fletcher, CEO and Co-Founder of MarketStreet. They discuss the current state of web development with LLMs, managing technical debt in startups, the evolution of infrastructure and reliability engineering, the role of community in technology, and the future of software engineering with AI.

In this episode, Sal Furino, Customer Reliability Engineer at Bloomberg, discusses all things Service Level Objectives (SLOs) with hosts Steve McGhee and Matt Siegler. Together, they dig into what successful SLOs look like, how it relates to users, and how SLOs provide an effective framework for joint decisions about system reliability across product, engineering, and leadership teams.

Matt Zelesko, the head of Site Reliability Engineering at Google, discusses the evolution of SRE, highlighting the shift from traditional operations to a model that balances velocity and reliability to better serve the rapid advancements in AI and ML. He emphasizes that SRE's core mission is to enable partners to move quickly while meeting reliability goals, and that the sheer scale of Google's infrastructure necessitates the SRE model for cross-system problem-solving. Zelesko envisions AI as a crucial assistant for SREs, improving incident detection, mitigation, and postmortem processes, and allowing SREs to focus on more complex engineering challenges and risk management earlier in the development cycle, while still valuing the hands-on experience of operating production infrastructure.

In this Google Prodcast episode, Todd Underwood, a reliability expert from Anthropic with experience at Google and OpenAI, discusses the current state and future of AI in SRE. Todd and the hosts focus on the current state and future of AI and ML in production, particularly for SREs. Topics discussed include the challenges of AI-Ops, limitations of current anomaly detection, the potential for AI in config authoring and troubleshooting, trade-offs between product velocity and reliability, the evolving role of SREs in an AI-driven world, and book publication for optimal timing.