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Milvus Operator for Kubernetes Deployment

4 posts · Nov 2021 – Aug 2025

What this trail covers

Milvus Operator simplifies the deployment and lifecycle management of Milvus clusters on Kubernetes, automating deployment, scaling, upgrades, and health checks. It abstracts away the complexity of managing individual Kubernetes resources and dependencies like etcd, Pulsar, and MinIO, allowing users to describe their desired Milvus state via Custom Resources. The Operator handles underlying orchestration and ensures reliability through continuous monitoring and self-healing.

All Milvus trails
  1. Deploying Milvus on Kubernetes Just Got Easier with the Milvus OperatorThis post introduces and details the Milvus Operator, a Kubernetes-native tool for automating the deployment and lifecycle management of Milvus clusters. It explains the Kubernetes Operator pattern, the Operator's core capabilities (Automated Deployment, Lifecycle Management, Built-in Monitoring, Operational Best Practices), and contrasts it with Helm/YAML deployments. It also provides a step-by-step guide for installing the Operator and deploying a Milvus cluster using a custom resource manifest, including prerequisites and example configurations.
  2. Deploying Milvus on Kubernetes: A Step-by-Step Guide for Kubernetes UsersThis post provides a step-by-step guide for deploying Milvus on Kubernetes using the Milvus Operator. It details prerequisites, Minikube installation for local testing, StorageClass configuration, cert-manager installation, Milvus Operator deployment, and the process of deploying a Milvus cluster using default or custom configurations via YAML files or the Milvus Sizing Tool. It also covers accessing the deployed cluster through port forwarding and connecting with the Python SDK.
  3. How to Deploy the Open-Source Milvus Vector Database on Amazon EKSThis post details the practical steps and considerations for deploying a Milvus cluster on AWS EKS. It covers prerequisites like AWS CLI, EKS tools, S3, and MSK, with specific guidance on MSK configuration for Kafka's autoCreateTopics feature and message throughput. It outlines the creation of an EKS cluster using eksctl, including IAM service accounts for S3 access and the AWS Load Balancer Controller, and node group configuration. The post then proceeds to detail the deployment of Milvus itself using Helm charts, configuring it to use AWS services like S3 for object storage and MSK for message storage, and setting up an AWS Load Balancer for external access.
  4. Getting started with Milvus cluster and K8sThis post provides a practical guide on deploying Milvus in cluster mode on Kubernetes using Helm. It outlines prerequisites (Docker, Kubernetes, Helm, Kubectl), details the Helm installation command with specific configurations (Kafka enabled, Pulsar disabled), explains port forwarding for local access, and shows how to verify the deployment by checking pod statuses. It also includes basic steps for connecting via pymilvus, creating a collection, inserting data, and performing a similarity search, concluding with instructions for uninstalling Milvus.
  5. How to Modify Milvus Advanced ConfigurationsThis post details how to modify advanced Milvus configurations when deployed on Kubernetes. It explains that for parameters not directly exposed by the Helm Chart, users must manually update the corresponding ConfigMap resource object to include the advanced configuration parameters (e.g., from `root_coord.yaml`) and then modify the deployment resource files of the relevant pods to mount these updated ConfigMaps as volumes. This process ensures that the Milvus components running in pods consume the new configuration settings.