Author: Nate Reuck
Nate Reuck is a Senior SRE and Incident Management leader with deep experience operating large-scale cloud platforms and distributed systems. He specializes in reliability engineering, incident response, on-call operations, and building durable operating models that scale. Nate's focus is reducing toil, improving MTTR, and turning incidents into repeatable learning through strong runbooks, automation, and clear ownership. He works closely with engineering, product, and partner teams to align reliability with real business outcomes, and believes strong systems, clear decision paths, and empowered teams win over heroics. Nate is also an author, builder, and lifelong learner with a passion for technology, systems thinking, and continuous improvement.
A runbook is the difference between a 4-minute resolution and a 45-minute one at 2 AM. Not because it’s magic, but because it eliminates the cognitive load of figuring out what to do when you’re already stressed, paged, and half awake.This page gives you a complete SRE runbook template, a real production example, a downloadable Markdown version, and answers to every common question about how to write one that holds up under pressure.What Is a Runbook (and Why Most Are Too Vague to Use)A runbook is a documented procedure for responding to a specific operational event — typically an incident,…
Containers have revolutionized application development and deployment by providing a lightweight, portable, and consistent environment for running applications.
Documenting and sharing lessons learned from incidents and post-mortems is crucial for driving continuous improvement.
Let’s explore the significance of work-life balance in the workplace.
Let’s delve into the challenges associated with SRE on-call work and provide comprehensive strategies to prevent burnout and maintain a healthy work-life balance.
Let’s delve into the importance of SRE leadership and the key roles it plays in driving operational excellence in SRE.
By harnessing the power of artificial intelligence (AI) and machine learning (ML), organizations can supercharge their observability efforts.
Let’s explore the fundamentals of AI Ops anomaly detection, examine its benefits for IT professionals, and discuss popular tools and techniques for its implementation.
Observability tracing involves instrumenting the code across different services and components of a system to capture and propagate trace data.
Example of Python code using the spaCy library for NLP to analyze incoming support tickets and automatically assign them to the appropriate IT teams based on the content of the ticket.