ArgoCD Reconciliation - Milvus Performance Tuning

Join us at the Station Austin for Food, Drinks, and Kubernetes on January 29th, 2026!🎉

Everyone is invited to join! We hope to bring the latest news about the Kubernetes and CNCF projects. 

We have two guests, Raghu Shankar and Vishva Gandhi!

We will be meeting at Station Austin! The address is 701 Brazos St, Austin, TX 78701. Upon arrival at the building, please proceed to the 1st floor.

We'll be in the Apollo Room (look for Capital Factory signs) after 5:45 pm.

We know parking in Downtown is tricky!

So, you can park in the building garage for just $8.00 (validation parking tickets will be distributed)! 

Street parking will still be an option. More information on parking here: https://www.capitalfactory.com/parking/

Venue Sponsored by Station Austin

Thank you to Station Austin for sponsoring Kubernetes Austin! Station Austin is the center of gravity for entrepreneurs in Texas. They meet the best entrepreneurs in Texas and introduce them to their first investors, employees, mentors, and customers. To sign up for a Station Austin membership, click here.

Vishwa Gandhi

ArgoCD Under the Hood (GitOps Reconciliation)

Configuration drift is one of the most common causes of instability in Kubernetes. In this talk, she will explain what actually happens after a commit is pushed to Git and how ArgoCD continuously reconciles the cluster back to the desired state. She will break down the reconciliation loop and the roles of key ArgoCD components like the Application Controller, Repo Server, and API Server—so you can build a strong mental model to debug issues and run GitOps confidently in production.

Raghu Shankar

Cloud-Native Vector Databases with Milvus (Benchmarking + Tuning + Observability)

Vector databases are becoming critical for fast similarity search in LLM apps, recommendations, genomics, and more—often at massive scale. This session introduces Milvus, a cloud-native vector database, and shares real benchmarking results from a CNCF-based 2-node Kubernetes cluster (40 cores, 64GB RAM). He will cover key tuning parameters (m, ef, ef_construction), how they impact latency/recall/throughput, and how performance correlates with observability metrics using Prometheus and Grafana.