SREDAY

SREs are on the frontlines of uptime, performance, cost efficiency, and incident response. So, at times, policies for security and compliance often live in stale docs enforced inconsistently, if at all, until something breaks or someone has an audit. Policy as Code (PaC) replaces that mess with real-time automation right where the work happens.

We will discuss how PaC bridges the gap between security and operations by making policies transparent, codified, versioned, and customizable so you can enforce external standards (CIS, SOC 2, HIPAA) and your own internal rules (like requiring HA in prod but not in dev). You'll see how to apply policy intent consistently from the pipeline directly to runtime, giving teams proactive control, not reactive fire drills or unnecessary "vibe killers".

We'll walk through a full-lifecycle live demo to see the possibilities of PaC to: - Prevent misconfigurations with real-time checks - Enforce policies consistently across repos, infra, and runtime - Customize and codify controls that reflect unique needs - Control cloud costs through autoscaling, right-sizing, and cleanup - Unify security, dev, and ops with shared policies

What will we accomplish? Well, no more stale docs or arguments around policies, faster deploy, tighter cost controls, and safer infrastructure without slowing anyone down.

Alayshia Knighten is a seasoned engineering leader and customer success strategist with a strong background in DevOps, cloud architecture, and technical enablement. Currently serving as the Founding Principal Customer Success Engineer at Mondoo, she brings over a decade of experience helping organizations build and scale secure, efficient, and reliable infrastructure.

Previously, Alayshia held key roles at Pulumi as a Senior Customer Architect and at Honeycomb.io, where she led implementation engineering and partnerships architecture. Her expertise spans across engineering consulting at Chef Software and hands-on DevOps engineering at Verisign. Passionate about empowering teams and driving technical excellence, Alayshia is known for bridging the gap between engineering and customer success.

We, tech people, have internalized the concept of reliability so deeply that we don't need an explanation for why it's bad to have services failing in production. It doesn't matter what your software is doing — whether it controls train schedules, allows people to make money transfers, or serves funny pictures online.

We have invented an entire language to talk about reliability. We say things like, "This service runs with three nines availability," "Mean-Time-To-Repair for the website is 25 minutes," or "This month, we consumed 80% of our error budget."

And yet, it's a common struggle to convince business stakeholders to prioritize technical improvements.

In the past seven years, I've been responsible for products and services used by millions of people. I have been on call for years and have spent many nights resolving production incidents. From that experience, I learned how to make reliability a shared priority and prove, with data, the value of technical improvements.

In this session, I'll share techniques you can use to improve the reliability of your services, convince business stakeholders of the importance of reliability, and drive positive change in your organization.

Maxim Schepelin has been an engineering leader in various industries including game dev, e-commerce, and travel building teams capable of launching products from idea to world-scale. With over a decade of experience leading engineering teams, Maxim has mastered the art and science of management, as well as how to exit both Vim and Emacs. Maxim continues exploring ways to build effective engineering teams that deliver value at a sustainable pace.

Constructing and managing platforms for diverse teams and workloads presents a significant challenge in today's cloud-native environment. This session introduces the concept of composable platforms, using modular, reusable components as the foundation for platform engineering. This talk will demonstrate how using Kratix, a workload-centric framework, and Backstage, an extensible developer portal, enables the creation of self-service platforms that balance standardization with adaptability. The session will detail platform design for scalability and governance, streamlining developer workflows through Backstage, and using Kratix Promises for varied workload requirements. Attendees will gain practical insights into building scalable and maintainable platforms through real-world examples, architectural patterns, and a live demonstration of a fully integrated Kratix-Backstage deployment.

Hossein is an experienced cloud computing professional with nearly a decade of expertise in distributed systems and cloud technologies. He began as a working student specializing in cloud automation at the Max Planck Institute, progressing to a full-time role focusing on on-premises cloud infrastructure and Docker. He built an on-premises Kubernetes platform in the industry and later honed his cloud and DevOps expertise as a senior consultant. As a tech lead, Hossein drives impactful projects, mentors platform engineers, and contributes to the community through talks and workshops.

Modern observability is built on a flawed foundation: three siloed pillars - logs, metrics, and traces - each powered by different engines with separate query models, storage formats, and operational costs. Users are forced to manually correlate across systems, accept duplication, or pay high SaaS bills. But what if observability is just a data problem? One that needs a general-purpose solution instead of purpose-built compromises? This talk argues that true observability requires fast, high-cardinality queries over unsampled data at scale and at low cost. Traditional search and metrics engines were not designed for this, but column-oriented databases are. We introduce ClickStack, a fully open source, OpenTelemetry-native observability stack built around ClickHouse. It provides fast, flexible querying and efficient storage, enabling real-time visibility without compromise.

Vlad Seliverstov leads the internal observability team at ClickHouse, overseeing the monitoring of ClickHouse Cloud, which handles over 100 petabytes of data and 500 trillion events. With more than a decade of SRE experience at Datadog, Dropbox, and Facebook, Vlad now focuses on building and scaling ClickHouse’s in-house observability platform.

As systems grow more complex, engineering teams must move beyond guesswork when resolving production issues and instead focus on delivering consistent, measurable user value. This talk explores how OpenTelemetry empowers teams to define, measure and improve Service Level Objectives with precision and confidence.

Drawing on real-world experiences of a software team navigating the challenges of legacy code, cloud migration and production instability, this session demonstrates how OpenTelemetry helps teams gain the insights they need to reduce Mean Time To Resolution, understand root causes and proactively improve system reliability.

We’ll dive into hands-on examples using the OpenTelemetry Demo Application and show how to help turn technical metrics into business-aligned SLOs that actually mean something. Whether you're an SRE, developer, or engineering leader, this talk will give you the clarity—and tools—to move from reactive firefighting to proactive service reliability.

Martin McLarnon is an engineer with almost 30 years experience working in many different roles within IT. He has worked as a Network Manager, Software engineer, Cloud Architect, Engineering lead and worked as an engineering consultant before joining Coralogix.

Modern SRE teams drown in alerts that show up after damage is done. This talk is a practical blueprint for going proactive: predicting incidents before they page you, and triggering safe, reversible auto-remediation.

I’m a Senior Engineering Manager at Paymenttools in Berlin, leading platform teams across SRE and Security. I focus on reliability, observability, Kubernetes, and policy as code, and I drive green-field work from idea to production. Lately, I’ve been applying GenAI to predict incidents and enable safe, reversible auto-remediation. I like clear processes, data-backed decisions, and practical solutions, and I write for peers to share what works and what doesn’t.

Do you still think that traces are those debug level logs to enable when something goes wrong? Do you think that this modern observability thingy is just another buzzword for other languages like javascript or go? Do you believe that "std::cout" is the best way to debug everything? Well, I do agree up to some point. But it does not scale that easily.

For modern, distributed systems, you will need to adopt modern observability. The path seems too complicated. But you are not alone! In this talk we'll demystify how to simply create metrics and distributed traces from a bunch of logs by using the OpenTelemetry standard and libraries. Metrics included too!

After describing the basics, Jose will also share an example he built to monitor many transactions in production without impacting performance. After this talk, you will be able to talk with higher confidence about OpenTelemetry, Jaeger, distributed tracing, Prometheus or VictoriaMetrics.

Jose is the Product Lead for VictoriaMetrics Cloud. With a focus on Observability and Sustainability, his work has been deeply related to the OpenTelemetry project, distributed tracing and power monitoring projects.

His expertise has been built from previous gigs as a Software Architect, Tech Lead and Product Owner in the Telecommunications industry, all the way from the software programming trenches where agile ways of working where a sound CI, testing and observability best practices have presented themselves as the main principles that drive every successful project.

With a scientific background in Physics and a PhD in Computational Materials Engineering, curiosity, openness and a pragmatic view are always expected. Beyond the boardroom, he is a C++ enthusiast and a creative force: contributing symphonic touches as a keyboardist in metal bands, when he is not playing video games or lowering lap times at the simracing cockpit. He also loves to spend time teaching Physics to Vet students in the Complutense University of Madrid, as an Associate Professor.

The Terraform plugin cache, unfortunately, does not support concurrent Terraform inits. This is a massive efficiency and performance loss for those who use Terraform at a big enough scale, since we're left with the following choices: - (A) Disable caching, and download gigabytes of providers off the Terraform Registry on every single init. - (B) Serialize all terraform init runs so they can safely share the cache, reducing the Terraform pipeline's throughput (and infuriating developers, been there, done that).

We didn't like our options here, so we got creative.

One day, everything clicked: OverlayFS!

OverlayFS is a Linux filesystem which combines the contents of multiple read-only directories and one writable layer on top, into a single volume, effectively implementing a sort of read-through cache within your filesystem. If you've ever used a live linux distribution, this is what those use. Containers use OverlayFS. CoreOS used OverlayFS to provide ephemeral /etc directories.

You rarely see such a low-level tool this high up the stack, so what is doing here?

We tweaked our workflow so that our plugin cache is mounted once per init using OverlayFS, which makes the centralized cache read-only (and thus, concurrent-safe) and gives Terraform a writable overlay where it can write whatever providers were missing. We then added a final, non-blocking step to feed back those new providers to the central cache (in a serial fashion using filesystem locking), effectively implementing a write-back cache.

After testing it on the lab, we promoted it to our production pipeline. After a couple rounds of plans to fill up the cache, we saw stunning results. Plan times dropped by -61%. Our concurrent plan capacity 10x'd because we were no longer saturating both the network (pulling) and the disk (writing providers). And after all, we didn't add much complexity to the setup anyway. We're using long-standing, reliable, kernel tech (overlayfs and flock) to address a shortcoming of a higher level tool like Terraform.

Ricard is a Lead Site Reliability Engineer at Cisco ThousandEyes' SRE team. Ricard is responsible for the Terraform pipeline of 600+ developers, managing over 110k cloud resources.

Coming soon...

Birol Yildiz is the Co-founder and CEO of ilert, adeptly steering the company with a rare combination of technical and product expertise. His prior experience includes a significant role as Chief Product Owner for Big Data products at REWE Digital. With a strong foundation in computer science, Birol bridges the gap between developer and product strategist, constantly striving to innovate and provide customer-centric solutions at ilert.