This recap includes the following episodes and guests.Â
Guest title reflects the guest's position at the time of the episode.
Recipes:
People: The Heartbeat and Mindset of SRE
Process: From Toil to Teamwide Transformation
Platform: The Foundation for Scalable, Sustainable Reliability
Andrew Lindsay, Software Performance Analyst
Abhay Choudhary, SR. Data Scientist
Ashley Tate, DevOps Developer, SRE Automation
What does it really takes to build reliable systems? It requires not just a technical perspective, but from a human and organizational one. as well. Episode 15 brought us the voices of Ashley, Abhay, and Andrew - three practitioners who represent the “A-Team” of SRE. In Episode 16, Kyle Brown zoomed out to show us how reliability engineering scales across an enterprise. Together, they painted a full picture of what the three-legged stool of SRE looks like in practice.
🎯 Goal: Foster a culture of curiosity, collaboration, and shared responsibility for reliability.
The human side of SRE is where everything begins—and where it scales. The journey into SRE is also rarely linear—and that’s what makes it so powerful.Â
Ashley’s journey from mechanical engineering to automation was driven by curiosity and self-learning: “I started teaching myself how to program… and once I graduated, I got a full-time position at IBM on the SRE automation team.” Her story reflects how SREs often grow into their roles by following their interests and building skills through hands-on experience.
Abhay’s passion for data science is deeply personal: “It makes you feel so amazing when you forecast something and it is about 90% accurate.” But he also emphasized the importance of bringing past experience into new domains: “It makes me understand an SRE problem better if I’ve worked on different types of problems related to that field in the past.” His advice? Leverage your background to ask better questions and challenge assumptions.
Andrew finds meaning in impact: “It’s really gratifying to see the fruits of our labor.” But he also acknowledged the need to shift from reactive work to scalable solutions, which requires a mindset of continuous improvement and shared learning.
Kyle Brown brought a leadership lens to the conversation, emphasizing that technical vitality is not just about individual growth - it’s about building a culture that supports it. “You can be the best engineer, but if you can’t communicate what you’re doing, it doesn’t make any difference.” He encouraged engineers to start small—presenting to their squad, writing blogs, sharing learnings—and grow their influence over time. His advice: “Never publish something once. Reuse your ideas, build on them, and share them in different formats.”
Ashley echoed this with a powerful story about learning to ask for help. Early in her career, she struggled with a complex task and hesitated to speak up. Her manager noticed and encouraged her to reach out. That moment changed her approach: “Asking for help is actually a skill, if you know how to leverage it properly.”She now sees collaboration as a core part of her role: “Everyone has different experiences and everyone can teach you new lessons every day.”
Together, these voices show that technical vitality isn’t just about staying current—it’s about staying connected, being open to learning, and building a culture where reliability is everyone’s responsibility.
🎯 Goal: Build scalable workflows and habits that embed reliability into everyday work.
The path to reliable systems is paved with repeatable, thoughtful processes—and the guests made it clear that this transformation doesn’t happen by accident. It starts with recognizing the friction points and turning them into opportunities for improvement.
Andrew shared a powerful example of this shift. When a customer escalation revealed a blind spot in monitoring, his team didn’t just patch the issue—they built a new alerting and automation workflow to prevent it from happening again: “We weren’t alerting on the data transaction log… so we created new monitoring and automation to take action before it became a problem.” This kind of learning loop—incident to insight to system improvement—is at the heart of SRE practice.
Abhay’s approach to anomaly detection also reflects this mindset. He described how his models identified a brewing issue weeks before it would have triggered an SLA breach: “We told them things are going in the wrong direction… and we were able to avoid a big problem without the customer care being involved.” But he also acknowledged the effort behind the scenes: “Every customer has different data sources… I always end up changing or modifying those functions.” His takeaway? Standardizing data pipelines is just as important as building the models that use them.
Ashley highlighted how even tasks like documentation can drive process improvement. Though she admitted, “I find it hard to put my thoughts onto paper,” she also recognized the value: “It helps me see the solution from a client’s point of view… and improve the automation process to make it more efficient.” Her team’s work on automating client communications and remediation tasks is a great example of how thoughtful process design can reduce support load and improve user experience.
Kyle brought a strategic view to process transformation. He emphasized the importance of embedding reliability into the development lifecycle—not as an afterthought, but as a default. His team created reusable user stories for common security requirements: “We just have a common story for it… then the story gets added into the backlog and people have to fulfill it.” This approach not only saves time but ensures consistency and compliance across teams.
Together, these stories show that scalable reliability isn’t just about tools—it’s about building habits, sharing learnings, and designing processes that make the right thing the easy thing.
🎯 Goal: Build intentional, automated platforms that support both system and service-level reliability.
A resilient platform is more than infrastructure—it’s the connective tissue that enables observability, automation, and proactive operations at scale. For SREs, the platform must not only be reliable, but also operable, adaptable, and designed with their workflows in mind.
A strong platform is what allows people and processes to scale - and that starts with clarity. Kyle Brown challenged the traditional definition of SRE, suggesting we think in terms of system and service reliability engineers. “That distinction is important,” he explained, “because each has different responsibilities and needs to evolve in sync.”
He also expanded the definition of reliability itself. “FinOps is a critical part of site reliability engineering now… and so is carbon footprint.” In other words, reliability isn’t just about uptime—it’s about predictability, sustainability, and governance.
Andrew emphasized that observability is the starting point: “If we don’t have the data, we can’t apply any data science or automation. We don’t know what we don’t know.” His team’s work on closing monitoring gaps—like alerting on database transaction logs—demonstrated how platform-level visibility directly impacts service reliability and customer experience.
Abhay sees the platform as a launchpad for predictive intelligence: “With the right data and AI/ML solution on top of it, we can create solutions that are more productive in the field of SRE.” But he also cautioned that platforms must support flexibility: “Every customer has different data sources… one single solution won’t work.” This highlights the need for modular, configurable platforms that can adapt to diverse workloads while maintaining consistency in how data is collected and used.
Ashley brought the operator’s perspective, focusing on automation as a force multiplier: “To bring together reliability and speed, we must eliminate as much manual work as possible.” Her team’s work on automating client communications and remediation tasks shows how platform-level automation can reduce toil and improve responsiveness—especially when integrated with tools like the Client Communication Center.
Most importantly, Kyle emphasized that automation must be built into the platform from the start—not bolted on later: “Everything is automated. And I mean everything.” His team uses Ansible and CI/CD pipelines to manage infrastructure, security, and compliance as code, making it easier for SREs to operate and evolve the platform without manual intervention.
Together, these perspectives show that building a strong platform isn’t just about uptime—it’s about creating a foundation that enables SREs to work smarter, scale faster, and operate more sustainably.
The message is clear: platform thinking isn’t just about infrastructure—it’s about building the foundation for everything else to stand on.
đź§ How do you balance automation with the need for human insight in reliability engineering?
🎮 What’s one “non-functional” requirement you think should be rebranded as essential?
🙋 How do you ensure your platform and service teams stay aligned as your architecture evolves?