DevOpsDays Tel Aviv

9:00-9:10 - Robusta.dev: more info coming soon

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9:15 - 9:25 - Quali: Agentic AI as an Accelerator for Infrastructure Operations

At their best, tools should feel like teammates — and AI for infrastructure is no different. In this session, we’ll show how Quali’s Torque MCP Server uses rich environment context to let agents safely provision and clean up infrastructure with traceable, governed actions. Through a live demo, you’ll see how environment-aware agents turn repetitive infra work into fast, reliable, and auditable automation

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9:30-9:40 - Dell: Supercharging Platform Engineering at Scale: The Dell Automation Platform

Join us for a lightning tour into how automation frameworks and AI-driven orchestration are reshaping infrastructure. The Dell Automation Platform is a foundational enabler for platform engineering, empowering your team to deliver any service (XaaS) or IT environment, whether in data centers or the cloud, with the agility and simplicity of a public cloud experience. In just ten minutes, you’ll get a glimpse of tools that make innovation unstoppable.

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• 

  Johnathan Viduchinsky

  R&D Director

  Quali

Sponsors

Tap into the mind of the person who built one of the most useful tools in the DevOps ecosystem - Docker - that fundamentally revolutionized the way we build and deliver software.  He's joining our community to geek out on all the technical thoughts that led him to build Docker (some that he has never shared publicly before), the visionary roadmap vs. what we use today, and how all of that led him to his latest project Dagger - where he's trying to fix everything that's still broken and painful in CI.  

Expect it to be nerdy, filled with code and lore, and come away understanding how to think about codifying the rigors of systems engineering into our day to day work, stack, and tools.

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Software lifecycles extend far beyond the initial build phase. Often a system built in a short time may continue to serve for years longer. These become mountains, foundations for a business or product, and contains encoded decisions, bug fixes, and implicit behaviors that can prove difficult to maintain.

Migrating large systems can be risky and daunting, and the strategy to migrate a system changes significantly based on the requirements.

In this session, Mike will share the approach taken over two years to migrate 6 core systems into a single source of truth, sharing techniques, challenges, and resolutions that worked for overall success.

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Building an AI/ML platform that can analyze and summarize massive volumes of unstructured medical data in real time requires more than just powerful models, it demands a production-grade infrastructure capable of handling complex inference workloads at scale.

This session dives into how to design and operate AI inference workloads on Kubernetes through an Amazon EKS example, for real-world production environments. It will cover model handoff processes from data science teams, validation and readiness assessments, deployment architecture, scheduling and scaling strategies, and inference traffic management. The session will also explore observability, performance tuning, and optimization techniques that are essential for maintaining reliability under heavy load.

Walk away with a deep understanding of the operational challenges, trade-offs, and engineering solutions involved in running high-performance AI/ML inference systems efficiently and responsibly at scale.

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As an SRE, capacity management, including demand forecasting, is a challenging routine when managing one of the world's largest Aurora/Mesos compute clusters. While Twitter Engineering moves forward with re-platforming to Kubernetes. Come hear me speak about implementing a technical solution that increased our existing clusters capacity by 9%—resulting in a multi-year saving of 9-figures in CAPEX by solving inefficiency challenges at data center scale.

● Discovering underutilized resources (CPU, Mem, and Network) within our storage platforms.
● Implementing a modern solution based on past experience with: Solaris Zones, Cgroups and Namespaces
● Colocate compute and storage workload on the same bare-metal machine

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The future of platform engineering is a single, unified control plane, where Kubernetes-native tools like Crossplane and ACK manage both applications and infrastructure through one consistent GitOps workflow. However, the path from this powerful vision to a stable, production-ready reality presents a new class of "Day 2" operational challenges. After the initial launch party, teams face a fundamentally different operational model where the familiar safety nets of traditional IaC no longer exist, and the rules for managing risk have completely changed.

A common engineering incident begins not with a bang, but with a small commit—a typo that a traditional, Terraform plan would have caught instantly, but in the new "plan-less" world, it gets silently reconciled, leading to cascading failures. This session moves beyond the "hello world" to dissect these widespread failure patterns, exploring the architectural anti-patterns that emerge and presenting a playbook of field-tested solutions for operating declarative, continuously-reconciling systems at scale.

This is not a theoretical guide; it is a tour of hard-won lessons from the community. Attendees will leave with a playbook for solving the most critical "Day 2" challenges, learning: a GitOps-native pre-flight check pattern; how to build a 'developer-portal dashboards for allowing developers to use it safely and a step-by-step strategy for safely migrating brownfield resources without downtime.

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Crossplane promises a unified API for cloud infrastructure, but many teams hit a wall as they scale. Your Compositions, initially simple, swell with complex patches and functions, creating a dangerous trade-off; you achieve a simple developer interface by hiding complexity in a system that becomes opaque, slow, and nearly impossible to debug. So, how do you trace a production failure through layers of runtime "magic"?
In this session, we'll present cell architectural patterns that resolves this conflict by shifting dynamic logic out of runtime Compositions and into a dedicated, build-time pre-processor - easy dev, test, validate. We'll show you how to decouple the developer's high-level intent from the final, low-level infrastructure specification, giving you the best of both worlds: a great developer experience without sacrificing platform visibility.

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What happens when a serverless application faces a regional outage? Traditional DR strategies don’t always translate to a cloud-native environment, requiring a different approach. This talk explores four key DR strategies—Backup and Restore, Pilot Light, Warm Standby, and Multi-Site—and their trade-offs in cost, complexity, and recovery time. Using real-world scenarios, we’ll discuss multi-region failover, automated recovery with infrastructure-as-code, and best practices for resilience in serverless architectures. Attendees will leave with a practical framework for designing scalable and cost-effective DR strategies in a cloud-native world.

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Managing webhooks at scale is a complex challenge, especially in dynamic environments. Supporting dozens of dynamic development environments introduced bottlenecks due to integration limitations and reliability concerns.

Existing tools, including Argo Events, fell short of meeting our requirements for persistence, observability, and simplicity.
In this talk, we will explore how we used NATS, a lightweight and scalable message queue, to build a custom solution for webhook management.

We'll cover how you can achieve exactly once delivery, fault tolerance, and resource efficiency (40 MB memory, 0.1 CPU) while drastically improving webhook routing and testing across environments.
You will gain practical insights into using NATS for event-driven systems, evaluating CNCF tools, and building tailored solutions that reduce complexity while enhancing scalability.

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We’ve all used them—architectural patterns that seem like the right choice for Serverless architectures. I did, too. At first, they felt efficient, straightforward, and even best practice. However, as my Serverless services matured, complexity kicked in, and I started to see the downsides: increased complexity, maintenance headaches, and even security and performance challenges.

In this session, I’ll walk you through five Serverless patterns I once used (and regretted): API Gateway direct integrations, monolith Lambdas, direct Lambda-to-Lambda invocations, writing all code in the handler, and using the wrong EventBridge service for scheduling.
You’ll learn why these patterns can be problematic, when they make sense, and what to use instead.

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Our hardware is getting faster, why the heck does our software get slower?
our servers are virtual at best. Our databases use storage that is not managed by us and our code is on someone else’s domain.
In this talk we will speak the unspeakable- over-abstractions can hurt the quality of our product and we don’t do anything about it.
I will give examples of before and after, and alongside to a lot of food for thought, we will give some practical tips on how to be quality minded in a world of SaaS

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12:50-13:00 - Binat Internet: Fly with AI

Ready to take off? In the DevOps world, speed is everything; but without security and smart connectivity, you’re flying blind. In this talk, we’ll highlight how to harness the power of AI to build faster, safer, and more connected cloud environments. From protecting your data with next-gen DSPM tools to enabling high-speed global connectivity for AI workloads, we’ll explore how to keep your DevOps pipeline running at full throttle.

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13:00-13:10 - AWS: Streamlining DevOps Workflows with Amazon Q and Kiro: A Practical Demo

1. Infrastructure Code Analysis:
   • Using Amazon Q to review and optimize Terraform configurations
   • Getting instant recommendations for security best practices and cost optimization
2. Incident Response Automation:
   • Demonstrating how Kiro can help automate incident response procedures
   • Showing real-time log analysis and problem identification

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13:10-13:20 - Aerospike: more info coming soon

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13:20-13:30 - DoIT: The Perfect Cluster, A Kubernetes Optimization Framework with PerfectScale by DoiT

Once your Kubernetes environment is live, the real work begins. This is Day-2 Operations—where stability, performance, and cost efficiency must be maintained continuously. Optimization at this stage isn’t about one-off fixes. It’s about creating a repeatable and proactive process.

In this short, practical demo session we’ll present a 6-step framework we’ve developed to help our customers cut waste, improve reliability, and keep their Kubernetes clusters lean and responsive.

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• 

  Anton Weiss

  Software Delivery Futurist

  PerfectScale
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  Maish Saidel-Keesing

  Senior Developer Advocate

  AWS
• 

  Arthur Berezin

  Product Leader & CNCF Ambassador

  PerfectScale

Sponsors

More info coming soon

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Or Cohen, VP Architecture at Melio will be joined by Daniel Schwartzer a Sr. Director of Data and Horizontal AI at CyberArk, and Oron Noah, VP Product at Wiz to talk about their incredible journeys to billion dollar exit success - and the technology out of our very own community that made it possible.

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Building reliable agentic AI systems in prod environments presents unique challenges when dealing with massive, noisy datasets. This talk shares hard-won lessons from developing an AI agent that processes millions of K8s events daily to deliver autonomous troubleshooting that reached 95%+ accuracy in benchmarking.

The fundamental challenge isn't LLM capability—it's building systems that maintain reliability when 90% of your data is noise. We'll explore why most agentic AI fails in production: hallucinations masquerading as insights, inability to validate reasoning chains, and the brittle nature of RAG systems when dealing with complex, interconnected failure modes.

Gain practical tips learned through painful prod iterations: how to build validation frameworks that catch LLM errors before they reach users, architectural patterns for constraining problem spaces without losing effectiveness & methods for creating evidence-based reasoning that can be audited & improved systematically.

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You scaled your Kubernetes clusters. You optimized your workloads. And yet—your cloud bill keeps creeping up.

Hidden in the noise?

Cross-AZ traffic: invisible, expensive, and almost impossible to trace until it’s too late.

This talk is about catching that ghost—before it haunts your budget.

We’ll show how to use eBPF to surface and analyze cross-AZ traffic in real time, tagging flows with just enough context to trace them back to specific services, nodes, and zones—even in fast-changing environments with autoscaling and ephemeral pods. No sidecars. No packet drops. No guesswork.

You'll see how we built a system that gives platform teams the visibility they need to finally control one of the cloud’s most stealthy cost sinks—and even enforce policy to keep traffic local where it counts.

If you’ve ever looked at your network bill and thought, “Where is this coming from?”—this talk has your answer.

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In this quick hands-on session, we’ll explore how to build and deploy a custom self-service hub directly in Slack, empowering your team to handle day-to-day operational tasks without needing to rely on DevOps or platform engineers. Whether you're automating routine infrastructure tasks, managing secrets, or facilitating service requests, Slack can become your team's one-stop-shop for all things self-service.

You'll walk away with the skills to:

Design and implement Slack bots that integrate with your internal tools

Set up Slack commands to automate common workflows and improve team productivity

Leverage Slack APIs and popular frameworks like Slack Bolt to streamline day-to-day tasks

Empower your team to take control of their operational processes while reducing bottlenecks and dependencies

This session is ideal for DevOps professionals, platform engineers, and anyone looking to enhance team autonomy and efficiency through automation and self-service tools in Slack.

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Success is a double-edged sword. As the gaming industry boomed, Playtika’s platform couldn't keep pace. What was once manageable became chaos: Ansible scripts, imperative Jenkins pipelines, a sprawl of internal portals & everyone doing automation their own way.

Environments took days to spin up.
Onboarding was guesswork.
DON'T touch the fragile parts.

This talk unpacks how Playtika modernized that mess into a CNCF-driven platform stack. Learn how they moved to declarative K8s clusters with ClusterAPI, GitOps deployments with FluxCD, and infra managed via Crossplane. Internal tools were replaced with a single Backstage-powered portal, delivering developer efficiency at scale.

But the real shift wasn’t just technical—it was cultural.

Ticket ops became self-service. Teams aligned. Provisioning dropped from days to under an hour all with OSS.

If your platform feels like it’s held together with duct tape and hope, this talk shows how standardization isn’t boring—it’s what scales.

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“Timeouts, Retries, and the Devil” dives into the often-overlooked complexity of error handling in high-scale systems. We’ll explore why short timeouts are essential for resilience—but dangerously easy to misuse—and how naive retries can spiral into system-wide meltdowns. Using real-world examples, including a postmortem-style analysis of a production incident inspired by real world problems, I’ll walk through actionable strategies to design smarter retries, prevent service hammering, and avoid cascading failures. This is a talk full of practical wisdom, gotchas, and system design insights that will stick with you the next time you’re writing retry().

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AI agents are moving from experiments to real tools in DevOps. But with so many frameworks to choose from, it can be hard to know which one fits your needs.

In this talk, we look at three leading multi-agent AI frameworks: Strands Agents, LangChain (LangGraph), and Microsoft AutoGen. We will show how each handles Model Context Protocol (MCP) integration and orchestration for autonomous workflows.

You will see:

- Strands Agents – model-driven orchestration, provider-agnostic setup, built-in MCP support, and agent-to-agent handoffs.

- LangChain (LangGraph) – graph-based workflows, agent swarms, memory management, and scaling to production.

- AutoGen – event-driven collaboration, conversational agents, and the rapid prototyping power of AutoGen Studio.

We will walk through real DevOps use cases like CI/CD automation, incident response, and infrastructure provisioning.

By the end, you will have a clear view of the strengths and trade-offs of each framework, along with a simple decision guide to choose the right one for your team.

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For years we have been bound by annoying restrictions, but the age of cloud ushered a limitless world where almost anything seems possible. Unfortunately, nothing in life is that easy and we discovered the hard way that although our tech credit cards may not have a spending limit, that doesn't mean there isn't a pay day...

We have become spoiled brats, forgetting the warning of our parents: "you gotta have limits!". This talk is about the long lost engineering principles of resource management which have become oh so relevant in these troubled times.

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AI assisted coding moves fast, sometimes too fast. One stray suggestion can drop a table or break a migration.
Baseshift removes that anxiety by giving developers safe, production-like database copies that are anonymized, subsetted, and instantly resettable, with full visibility into every change. So you can vibe-code fearlessly, recover instantly, and ship with confidence.

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• 

  Amir More

  CEO

  BaseShift

Sponsors

DevOps is all about automation, speed, and reliability - until your pipeline skips a step, your Helm chart misbehaves, or your IaC plan decides to delete production.
Oops.
In this bite-sized lightning talk, we’ll laugh (nervously) at the kinds of mistakes that happen when we don’t test our infrastructure, pipelines, and configs- and then we’ll look at how to stop them. We’ll cover best practices and real tools for testing your DevOps work and share ways to shift testing down into the layers most people forget.
Because let’s be honest: if your job is to keep everything running, so you probably shouldn’t be deploying blindfolded.

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AI agents are more than just LLMs with tools.

In this talk I'll discuss the cost of AI agency - all we need to do to make AI agents useful and secure.

I will then present Kagent - the CNCF project that makes agents cloud native and Khook - the reactive component for Kagent I've contributed and am now maintaining. The listeners will walk out with practical tools for building and running reactive AI agents on K8s.

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You wouldn’t drive without a dashboard. So why do so many engineering teams run without any real operational visibility?
As Engineering Leaders, we have so much on our mind, and we need a tool, like in the car, that will allow us to drive to our destination, with a dashboard focusing us on what matters.

In this talk, I introduce a simple, 3-layer model for building dashboards that are actually helpful:
1. High-Level View – Are we on track?
2. Detailed View – Where’s the work?
3. Red Lights Focused– What’s broken?

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Most systems rely on default configuration values, and that’s usually fine. But these defaults often go untouched for years, even when they no longer match the system’s scale or behavior. The result? Silent performance losses that are easy to miss and hard to trace.

In this talk, I’ll share the true story of how changing a single digit in an obscure timeout setting cut our API latency in half. The issue wasn’t bad code, it was an outdated assumption baked into a default value that didn’t fit our system anymore.

You’ll learn:

- How configuration defaults can quietly create performance bottlenecks
- What invisible inefficiencies look like in an advanced DB connections management (e.g. sharding, connection pools, connections multiplexer)
- How to detect these issues in production systems, even when logs and metrics seem fine
- A practical approach for evaluating, tuning, and monitoring configuration selection

This talk is for anyone working at the intersection of development and operations. If your systems are “working” but not performing, this will help you uncover why, and what to do next.

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Picture this: A government announces a last-minute timezone change with just days of notice. Suddenly, your serverless application has the wrong time assumptions baked into immutable functions. Users get notifications at wrong times, business logic breaks, and support is flooded with "time bug" reports.

This happens 3-6 times per year as governments adjust timezone rules for political, religious, or economic reasons. In traditional servers, you'd update the timezone database and restart. In serverless? Your timezone data is frozen into deployment artifacts.

This lightning talk shows the one hybrid architecture pattern that actually works in production - preventing millions in downtime when governments decide to mess with time.

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When a new CVE drops, applying the fix isn't as simple as merging upstream changes––they hit live systems with layers of legacy, dependencies & constraints.

Welcome to the shadowy underbelly of backports, a delicate operation where the goal is to surgically apply a fix, without disrupting the stability of older releases, prod systems or their intricate web of dependencies.

This talk dissects CVE-2024-37370 in MIT Kerberos - a vuln that can be found in all of the major Linux variants and underpins cloud-native applications broadly, including many CNCF projects.

We'll explore what constitutes a CVE-worthy vulnerability, what the vulnerable code actually looks like, and will reverse engineer how it's fixed. Then we'll walk you through step by step how to reverse-engineer a backport: unpacking the challenges of retrofitting fixes into older codebases, rewriting patches to accommodate shifting APIs, and avoiding side effects that ripple across documentation, test suites, & configs.

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Now is your chance to tap into the builders from our community - Solomon Hykes, creator of Docker and Bobby Dorlus, one of the first SREs at Twitter - an open, mic and AMA - to find out all the juiciest details you can only ask in person.

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