SREDAY

When you're managing dozens of Kubernetes clusters, across three different clouds, for dozens of individual companies in their own accounts, the challenge of (re)designing tooling is complex. Come hear how we worked through all the many possible options (centralized IaC vs templating, whether to use cluster managers like Rancher, etc.), what high-level tradeoffs were made (i.e. ease-of-use vs speed of changes vs centralized control), and the tangible outcomes of this process. The focus here will be on the process and decision making, given all the different drivers such as technology, business, people, process, etc. This talk will cover how we undertook the process, while giving you tangible next steps to take back to your desk.

From this talk, you'll take away: - Some reasons why you should or should not attempt a rewrite of your Infrastructure-as-Code process. - An overview of the inputs that you should consider when designing an Infrastructure-as-Code tooling stack. - Some idea of how to be successful with a tooling rewrite.

Andrew Suderman has had a lifelong obsession with technology that currently fuels his passion for Kubernetes. He enjoys designing and building new systems that make life easier for developers. Currently he pursues that passion at ReactiveOps, where he maintains dozens of clusters and works on internal tooling.

In his spare time he enjoys off-roading, camping, quadcopters, motorcycles, and far too many other hobbies to afford.

Zero Trust doesn't have to be intimidating. Learn how Identity-Aware Proxies transform service access from perimeter-based to continuous verification, explained through the universal experience of airport security.

Imagine if showing your ID once at airport security meant you could then board any plane, enter the cockpit, or walk into customs. Sounds absurd? Yet this is how perimeter-based security works - one check, then complete trust. Based on Google's BeyondCorp papers, this talk breaks down Zero Trust and Identity-Aware Proxies, where every access request is verified based on identity, device, and context - just as airports verify your credentials at every secure checkpoint, from airport security to boarding gates to airline lounges. Through technical concepts and the analogy of airport security, we'll explore how to implement these principles in real-world applications.

Nick is a developer advocate at Pomerium, a zero trust, identity-aware proxy platform that enables secure, clientless connections to web applications and services without a corporate VPN.

With over a decade of open source contributions and five years of professional open source experience at companies like OpenSauced, dev.to, and Netlify, he brings deep community knowledge to his work. You’ll often find him live streaming tech content, either solo or with friends from the community.

In today's fast-paced world, Agile & security is paramount. Urgent Cloud Services Deployment Practices ensure seamless and secure cloud deployments under tight timelines. Gain actionable insights, maintain robust security, and enhance team coordination for efficient, reliable cloud infrastructure.

Sangeetha Rajkumar is a seasoned technologist and product manager with over 9 years of experience in software product development. As a Senior Technical Program Manager at Microsoft, she leads the development of innovative cloud products for Microsoft customers. Sangeetha has spearheaded numerous automation projects in Deployment and DevOps, showcasing her technical expertise, strong product & program management skills.

She holds a master's degree in engineering management with a specialization in Product Management from Cornell University. With nearly a decade of experience in the IT industry, Sangeetha has worked across various sectors, including Consulting, Fintech, and Enterprise Solutions. Additionally, she mentors early-career professionals at Microsoft, ADPList, and Topmate.io.

Learn how to identify hidden patterns in cluster behavior that impact reliability. Discover methods to detect issues like pod delays and service dependencies, using clustering algorithms and proactive strategies for improved resilience and resource optimization.

Join us for a deep dive session that extracts data-driven observations and insights from heavily utilized clusters to find unique patterns that impact reliability. We'll share how to implement the right signals to detect common challenges such as delays in pod spin-ups, pod termination data to identify workloads most affected by these terminations, or closely occurring failures that indicate hidden service dependencies. We'll then cover methods to preemptively address these to improve resilience using clustering algorithms like DBSCAN, for dependency mapping, and other good practices. We'll walk through a typical journey from experimental setups using scripts and command-line outputs to production-ready practices––from quick prototyping, to refining data pipelines and optimizing performance for operational environments. By uncovering these hidden patterns & signals you can achieve proactive reliability improvements, for improved cluster health & optimization of resource allocation.

Gary Edgar is a seasoned technical support and customer engineer with 15+ years of experience across cloud infrastructure, databases, and monitoring systems. Currently at Komodor, he helps teams streamline Kubernetes troubleshooting.

Previously, Gary was a key early hire at PlanetScale, supporting major clients like Stripe and Twitter with performance tuning, architecture, and hands-on support. He also delivered impactful solutions during his time at SevOne (IBM), working onsite with Microsoft and eBay to improve system reliability and monitoring at scale.

For years, you've hopefully been relying on the Microsoft Well-Architected Framework (WAF) as a starting point to have your workloads set up in a highly available, redundant architecture. Following those guidelines is key to get reliably running business critical applications for your users or customers.

But even after following all the guidelines, did you really know your applications would run as expected? With this session, I'm going to take the guesswork out of that question, and walk you through different tools in Azure, Azure Load Testing and Azure Chaos Studio, which help by stress-testing your critical workloads, running in App Services, Containers, CosmosDB or traditional Virtual Machines.

As usual in Peter's sessions, this will be packed with live demos and only a bare minimum of slides.

Peter has an extensive background in architecting, deploying, managing and training on Microsoft technologies, dating back to Windows NT4 Server in 1996, all the way to the latest and modern cloud solutions available in Azure today. With a passion for cloud Architecture, Devops and App Modernization, Peter always has a story to share on how to optimize your Enterprise-ready cloud workloads. When he's not providing a technical Azure workshop out of his role as Microsoft Technical Trainer at Microsoft Corp, for which he relocated from Belgium to Seattle early 2022, he's developing some new apps in .NET Blazor, or trying another bread baking recipe in his home kitchen. Peter was an Azure MVP for 5 years, is a Microsoft Certified Trainer (MCT) for +15 years and still actively involved in Tech Communities as public speaker, keynote presenter, technical writer and mentor.

This talk is for DevOps and SRE engineers who are looking to optimize the number of SLOs in their system and find methods to manage a large number of various SLIs for their complex, multi-level service architecture. The talk covers practical methods for calculating SLOs based on multiple SLIs and dependencies, including the reliability of third-party service providers and unknowns. Attendees are expected to be familiar with basic SRE principles and terminology. The talk includes some probability math.

Overwhelmed by the complexity of managing SLOs across your microservices architecture? This talk provides DevOps and SRE engineers with actionable strategies for defining, calculating, and optimizing SLOs in systems with a large number of SLIs.

We’ll explore practical techniques for:

• SLO Targets: Right-guessing and improving your SLO goals.
• SLO Optimization: Right-sizing the number of SLOs to ensure effective monitoring without unnecessary overhead.
• SLO Composition: Mastering aggregation and other methods to derive meaningful SLOs from diverse SLIs.
• Dependency Management: Incorporating the reliability of third-party services and unknowns into your SLO calculations.

The talk will include some probability math to illustrate key concepts.

In my work at Google as a Developer Relations Engineer, I help cloud practitioners to solve a wide range of technical and architectural problems related to running workloads in Google Cloud and hybrid environments. Jump start to Google Cloud. Reach 99.99 SLO. Troubleshoot a problem in real time. Or, evaluate a security posture of your application. All these and many other problems that engineers and architects meet every day. Before Google, I worked in healthcare, interactive TV and gaming industries in many engineering roles including SWE, TL and Cloud Architect. In my free time I enjoy swimming, hiking and horseback riding.

What's the worst that can happen? Join me for a story about reliability, secrecy and potential 200k fatalities.