Join us for a discussion with Carla Geisser of Layer Aleph, a company focused on "crisis engineering". Carla distinguishes a crisis from a standard incident by noting that a crisis is novel and lacks a playbook. She outlines five criteria for a true crisis: fundamental surprise, broken critical functions, high visibility, a rigid deadline (unlike internal tech deadlines), and perception breakdown. Crises often arise in organizations that struggle to admit computers control core decisions, leading to complex, glued-together systems. Carla emphasizes that SRE-adjacent skills are essential for connecting the dots and exposing the full system. The key takeaway for SREs is to recognize when a true crisis is happening, as leadership will only be willing to "break rules" and enable substantive change once three of these criteria are met.1

This episode of the Prodcast tackles the challenges of maintaining AI safety and alignment in production. Guests Felipe Tiengo Ferreira and Parker Barnes join hosts Matt Siegler and Steve McGhee to discuss AI model safety, from examining content to emerging security risks. The discussion emphasizes the vital role of SREs in managing safety at scale, detailing multi-layered defenses, including system instructions, LLM classifiers, and Automated Red Teaming (ART). Felipe and Parker dive into the evolving world of AI safety, from core product policies to the groundbreaking Frontier Safety Framework. The guests explore the need for SRE principles like drift detection and context observability. Finally, they raise concerns about the velocity of AI development compressing long-term research, urging the industry to collaborate and share vocabulary to address rapidly emerging risks.

In this episode of the Prodcast, guest Shannon Neufeld-Brady speaks with hosts Jordan Greenberg and Florian Rathgeber about managing Google's vast fleet of internal devices. Shannon explains how Google's Linux platform uses core SRE principles—specifically testing, canarying, and monitoring—for weekly stage rollouts of its Debian-based distribution. Configuration is efficiently managed using Puppet to ensure the right setup for a diverse user base. The conversation pivots to "the year of Linux everything," underscoring its widespread adoption. Discussing AI, Shannon identifies its greatest utility for SREs in rapidly analyzing signals and generating complex queries to resolve outages. This episode reinforces that practicing SRE fundamentals is paramount, demonstrating that you can be an SRE at heart, regardless of your official title.

Curious about the real impact of AI on Site Reliability Engineering? In this episode of The Prodcast, Google SRE Denia del Cid breaks down how her team is leveraging AI to transform production workflows.

Denia details practical applications like early outage detection, incident similarity analysis, and toil reduction. She explains the critical importance of validating against "golden data sets" and keeping humans in the loop to build trust. Discover how SREs are evolving from skepticism to strategic adoption with Gemini.

Tune in for a pragmatic, measured look at the future of reliability.

Join us on The Prodcast as we host Heather Adkins, leader of Google's Office of Cybersecurity Resilience, for a critical look at the future of digital defenses. We explore the intersection of SRE and security , unpacking the "Secure by Design" philosophy and the shared DNA of incident management.

Heather candidly discusses the rise of "Agentic AI hackers" and polymorphic malware , revealing how defenders can use AI to stay ahead. From "castle" defense strategies to "nodal biology" theories, this episode is a must-listen for anyone navigating the new era of AI-driven threats.

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.