Sylvain Kalache

Lessons from leading engineering teams through organizational change and system migrations.

Panel at the AWS GenAI Loft with leaders from a16z, AWS, Dagger, Braintrust, Baseten, and Arize AI on how AI is transforming developer workflows.

Platform engineering at healthcare scale — compliance, reliability, and developer experience.

Building reliable billing infrastructure and the unique challenges of usage-based pricing systems.

Breaking down the Model Context Protocol (MCP) and Agent-to-Agent (A2A) standards — why interoperability matters for the next wave of AI agents.

AI-generated code ships faster but introduces subtle bugs that are harder to trace.

Operating a developer platform company and the reliability challenges of running infrastructure for others.

Invite-only roundtable comparing centralized specialist responders with distributed on-call models — which strategy works for your org.

Developer experience, engineering metrics, and what makes teams productive and reliable.

Panel with leaders from a16z, Y Combinator, and Google Cloud on how MCP servers and agent-to-agent communication are revolutionizing developer tools.

Tracing the arc from ingesting logs at LinkedIn/SlideShare to LLM-driven RCA today.

API gateway architecture, service mesh patterns, and reliability at the network edge.

Building internal developer platforms and the organizational dynamics of platform teams.

Breaking down the EU's Digital Operational Resilience Act — what it means for financial services and tech companies operating in Europe.

Using kpack to automate container image builds natively on Kubernetes with seamless CI/CD pipeline integration.

The platform engineering movement, internal developer platforms, and developer self-service.

Advanced buildpacks techniques for optimizing build times, ensuring portability across clouds, and managing lifecycle updates.

Strategies for managing dependencies and runtimes in containerized environments — keeping images secure and up to date.

Best practices for managing the full container lifecycle — from build to runtime to decommission.

If developers are vibe coding, SREs are now incident vibing.

Training teams for incident response — chaos engineering, game days, and building organizational muscle memory.

Frontend infrastructure reliability, edge computing, and the operational side of Vercel's platform.

Invite-only roundtable examining AI's role in incident response — separating practical applications from hype with industry leaders.

An MCP server for Rootly — enabling AI agents to interact with incident management workflows via the Model Context Protocol.

Observability culture, OpenTelemetry adoption, and the human side of monitoring and debugging.

Reliability at GitHub scale — incident management, deployment practices, and engineering culture.

A benchmark suite for evaluating AI agents on real-world SRE tasks — incident diagnosis, runbook execution, and infrastructure troubleshooting.

A personal MCP server that exposes my portfolio data — articles, podcasts, talks, panels, GitHub projects, news, bio, timeline, and live weather — as queryable tools for AI agents.

Comparing three cloud native approaches to deploying and managing PostgreSQL on Kubernetes — operators, managed services, and hybrid models.

Canyon lets developers provision resources, troubleshoot issues, and interact with internal tooling via natural-language prompts.

Building a unified developer portal with Backstage that spans both Cloud Foundry and Kubernetes clusters.

Combining Argo Workflows with Cloud Native Buildpacks to create a fast, repeatable CI/CD pipeline that eliminates Dockerfile maintenance.

How election infrastructure security is evolving — from paper ballots to digital voting systems and the role of data compliance.

Harbor maintainer Vadim Bauer walks through container image management, OCI artifact storage, replication for disaster recovery, and storing AI models.

Practical techniques to speed up container builds, reduce image size, and improve reproducibility across development and CI environments.

How to embed application performance monitoring directly into your buildpack pipeline without modifying application code.

Detects early warning signs of on-call engineer burnout by pulling data from Rootly, PagerDuty, Linear, GitHub, and Slack.

Moving past the buzzwords — where AI is actually changing developer workflows, internal developer portals, and what it means for platform teams.

A walkthrough of the American Privacy Rights Act — its scope, requirements, and implications for tech companies handling user data.

What the EU AI Act actually requires — risk classifications, compliance timelines, and what it means for AI-driven products.

The evolution of document processing compliance — from physical records to AI-powered intelligent document processing systems.

A grounded look at what LLMs can and can't do in an incident response workflow today, drawn from real production experiments at Rootly AI Labs.

How platform engineering teams can embed security and compliance into their internal developer platforms from day one.

Simplifying Java app containerization with buildpacks — skip the Dockerfile complexity and let the platform handle the build.

How forward-thinking companies are turning data security and compliance requirements into competitive advantages.

PaaS commands a $170B share of the cloud market, yet manual deployments persist.

How Korifi brings Cloud Foundry's developer experience to Kubernetes, enabling simple app scaling without deep K8s knowledge.

The unique data security and compliance challenges that large language models introduce — from training data to inference outputs.

Using Korifi to deploy polyglot applications to Kubernetes with the simplicity of Cloud Foundry's cf push experience.

The growing tension between US SaaS providers and European data sovereignty requirements — what it means for cross-Atlantic business.