pipekit/talk-demos
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About
Code & docs for Pipekit's talks
DataREADME.md
Original
This repo contains demos from ArgoCon, KubeCon, Open Source Summit, and Observability Summit.
Observability Summit Europe 2026
KubeCon + CloudNativeCon EU 2026
ArgoCon EU 2026
- Bring Your Own Artifact Driver To Workflows
- Don't Do What Donny Don't Does: The 10 Dos and 500 Don'ts of Workflows Success
ArgoCon EU 2025
- Argo Workflow Templates: A Practical Deep Dive
- Automated Resilience: Using Argo Events for Real-Time Incident Remediation
ArgoCon USA 2024
- Dog Food Delight: How Argo Workflows Eats Its Own CI
- Demystifying Argo Events: An Architectural Deep Dive
- Untangling the Threads: Understanding Argo Workflows with Workflow Tracing
- Data Science Workflows Made Easy: Python-Powered Argo for Your Organization
ArgoCon EU 2024
- Mastering Argo Workflows at Scale: A Practical Guide to Scalability Excellence
- Orchestrating Python Functions Natively in Argo Using Hera
- Panel: Argo for ML: Achieving Scalability and User Experience
- Demystifying Argo Workflows: An Architectural Deep Dive
- Scaling Cloud-Native CI/CD with Jenkins and the Argo Projects
- Argo CD - Plugins as Services
ArgoCon USA 2023
- Scaling to Thousands of Data and CI/CD Pipelines using Argo and Virtual Clusters
- Migrating CI/CD from Jenkins to Argo
- Streamlining big data workflows with memoization and work avoidance
- How to Train an LLM with Argo Workflows with Hera
- Comparing Airflow and Argo Workflows at Scale
ArgoCon EU 2023
- Configuring Volumes for Parallel Workflow Reads and Writes
- Managing Artifacts at Scale for CI and Data Processing
- Leveraging Argo WorkflowTemplates Within a Data Platform
ArgoCon 2022
Open Source Summit 2022
ArgoCon 2021
Argo Workflows Support
Pipekit’s team of Argo experts provide professional support for companies using Argo Workflows. Pipekit's Argo contributors help platform teams optimize pipeline performance, squash upstream bugs, and make faster technical decisions. Learn more at pipekit.io/services.
For more information about Argo Workflows, please see the following resources:
- The Argo Workflows Documentation
- The Argo Workflows GitHub Repository
- The Argo Workflows Slack Channel
About Pipekit
Pipekit is the control plane for Argo Workflows. Platform teams use Pipekit to manage data & CI pipelines at scale, while giving developers self-serve access to Argo. Pipekit's unified logging view, Workflow Metrics dashboards, enterprise-grade RBAC and multi-cluster management capabilities lower maintenance costs for platform teams while delivering a superior devex for Argo users. Sign up for a 30-day free trial at pipekit.io/signup.