> Source: https://meetrix.io/blogs/milvus-gcp-developer-guide/ > Markdown copy of that page. Cite the URL above, not this file. Development # Milvus on GCP - Developer Guide [By Binuka Ranatunga](https://meetrix.io/blogs/authors/binuka-ranatunga/) • August 12, 2026 • 7 min read Welcome to the Meetrix Milvus developer guide for Google Cloud Platform! Milvus is the open-source vector database behind many production RAG pipelines, semantic search engines, and recommendation systems. With the Meetrix pre-configured GCP image, you can deploy a production-ready, self-hosted Milvus instance in minutes, without managing the underlying installation and dependencies yourself. This guide walks you through finding the product on GCP Marketplace, configuring the deployment, verifying it is running, and connecting to it with the pymilvus SDK. ### Related Article [ Milvus - Developer Guide (AWS) Step-by-step guide for deploying and configuring the Milvus vector database on AWS using the Meetrix pre-configured AMI. Meetrix.IO • Binuka Ranatunga ![Meetrix Milvus Developer Guide AWS](https://meetrix.io/blog-images/paas-dev-guides/milvus/milvus-image.png)](https://meetrix.io/blogs/milvus-developer-guide/) Prerequisites Before you begin, make sure you have the following: - Basic Google Cloud Platform knowledge. - An active Google account with a GCP project and billing enabled. - Sufficient Compute Engine CPU quota in your target region for the machine type you plan to use. ## Launch the Product ### Step 1: Find the Product 1. Log in to your Google account. 2. Go directly to the product page: [Milvus Vector Database for AI, RAG & Semantic Search on GCP Marketplace](https://console.cloud.google.com/marketplace/product/meetrix-public/milvus-vector-database?project=meetrix-public) 3. You can also browse all Meetrix products at the [Meetrix Solutions Page](https://console.cloud.google.com/marketplace/browse?filter=partner:Meetrix%20Pte%20Ltd&ref=meetrix.io). ![Milvus Vector Database for AI, RAG and Semantic Search product details page on GCP Marketplace showing the Launch button](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-1.png) ### Step 2: Launch the Product 1. Select your GCP project from the project selector at the top. 2. Click the **Launch** button. 3. Review the terms and agreements, tick the acknowledgement checkbox, and click **AGREE**. ![GCP Marketplace Agreements page with the terms and agreements checkbox and Agree button for the Milvus deployment](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-2.png) ### Free Trial This product includes a **5-day free trial** with up to USD 50.00 in licence fee credits. To activate it, tick **I accept the solution trial Terms and Conditions** before proceeding. ![Free trial terms and conditions checkbox on the Milvus GCP Marketplace deployment form](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-3.png) Trial note Infrastructure charges (VM, disk) still apply during the trial. Only the Meetrix licence fee is credited. You can cancel the trial at any time by deleting the deployment. ### Step 3: Configure the Deployment You will see the deployment configuration form. Fill in the fields across the following sections: ![Milvus GCP deployment configuration form showing deployment name, service account, zone, machine type, and boot disk settings](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-4.png) #### General - **Deployment name** - A unique name for this deployment (a default is pre-filled). - **Deployment Service Account** - Select an existing service account that has the `roles/config.agent`, `roles/compute.admin`, and `roles/iam.serviceAccountUser` roles, or let GCP create a new one for you. - **Zone** - Select the GCP zone closest to your users (for example `us-central1-a`). #### Machine Type - **Series** - Default `E2` under the General purpose tab. - **Machine type** - Default `e2-standard-2` (2 vCPUs, 8 GB memory). Choose a larger type for heavier workloads. #### Boot Disk - **Boot disk type** - Default `Balanced Persistent Disk` is recommended. - **Boot disk size** - Default 20 GB is sufficient for most setups. GCP shows an estimated monthly cost, made up of the Meetrix licence fee and the underlying infrastructure fee, based on your selected machine type and disk size before you deploy. ### Step 4: Configure Networking - **Network** and **Subnetwork** - Leave as `default` unless you have a custom VPC. - **External IP** - Leave as `Ephemeral`. Select `None` only if you do not need public internet access. - **Allow SSH (TCP port 22) from the Internet** - Enabled by default. Restrict the source IP range if you want to limit SSH access to specific IPs. ![Milvus GCP networking configuration showing the network interface settings and the Allow SSH firewall rule](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-5.png) Firewall for the Milvus port The deployment form only exposes a toggle for SSH access. After deploying, check **VPC Network → Firewall** in the GCP console and confirm a rule exists that allows inbound TCP traffic on port **19530** (the Milvus client/gRPC port) from the IP ranges you expect to connect from. Restrict the source range before using this in production. Click **DEPLOY** and wait a few minutes for the deployment to complete. ## Access the Deployment ### Step 1: Get the External IP 1. Once deployment is complete, open the VM instance from the deployment details. 2. Copy the **External IP** from the Network interfaces section. ![Milvus VM instance network interfaces showing the internal IP address and the ephemeral external IP](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-6.png) ### Step 2: Verify Milvus Is Running Visit **http://** in your browser. You should see a confirmation page. ![Milvus is running status page displayed in the browser at the instance's public IP address](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-7.png) Note If the page does not load right away, wait a few minutes for the instance to finish booting and for Milvus to start, then try again. ## Connect to Milvus Milvus listens on port **19530** and ships with a default admin user, so you can connect immediately using the pymilvus SDK. No web UI is bundled with this deployment - if you want one, run [Attu](https://github.com/zilliztech/attu) yourself in a separate container pointed at this host's port 19530. ```plaintext pip install pymilvus ``` ```plaintext from pymilvus import connections, utility connections.connect( host="", port="19530", user="root", password="Milvus" ) print("Connected!") print(utility.list_collections()) ``` ![Python script connecting to a Milvus instance on GCP with pymilvus and listing collections](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-8.png) Running the script confirms the connection and lists any existing collections (empty on a fresh instance): ![PowerShell terminal output showing a successful pymilvus connection to Milvus on GCP](https://meetrix.io/blog-images/paas-dev-guides/milvus-gcp/milvus-gcp-9.png) Deprecation notice Newer versions of pymilvus flag `connections.connect` and `utility.list_collections` as deprecated ORM-style calls in favor of `MilvusClient`. The script above still works, but consider migrating to `MilvusClient` for new projects. Security Change the default root password before storing production data, and restrict the firewall rule's source IP ranges instead of leaving them open to the internet. ## Manage the Deployment ### Stop the VM To stop the VM without deleting it, go to **Compute Engine → VM Instances** in the GCP console, select your instance, and click **Stop**. You can restart it later with your data intact. ### Delete the Deployment To fully remove the deployment and stop all billing: 1. Go to **[Solution deployments](https://console.cloud.google.com/products/solutions/deployments)** in the GCP console. 2. Find your Milvus deployment. 3. Click **Delete** to remove all associated resources. Back up any collections or data you need before deleting the deployment. ## Upgrades When a new image version is available in the GCP Marketplace, back up your Milvus data, delete the previous deployment, and relaunch with the new version. ## Troubleshoot ### Check Server Logs Open an SSH session to the instance from the GCP console, then check the running containers and their logs: ```plaintext sudo docker ps sudo docker logs ``` ### Quota or Capacity Errors GCP enforces regional CPU quotas. If you hit a quota error when deploying, request a Compute Engine API CPU quota increase for that region, or choose a different region or zone with available capacity. ### Connection Issues If pymilvus cannot connect, confirm a firewall rule in **VPC Network → Firewall** allows inbound TCP traffic on port **19530** from your IP address. ### Disk Space If Milvus becomes unresponsive, check whether the boot disk is full: ```plaintext df -h ``` If the root volume is between 90-100% full, resize the persistent disk in the GCP console, then reboot the instance and restart the service. ## Conclusion The Meetrix Milvus Deployment Guide helps you get a self-hosted vector database running on your own GCP project in minutes. Whether you're building a RAG pipeline, a semantic search feature, or a recommendation engine, this guide gives you a secure, scalable starting point. ## Technical Support If you run into any issues, our support team is here to help. Reach out to us at [support@meetrix.io](mailto:support@meetrix.io) and we will respond within 12 hours. ## Frequently Asked Questions What is Milvus? Milvus is a high-performance, open-source vector database purpose-built for storing, indexing, and searching massive-scale embedding vectors. It powers AI applications such as retrieval-augmented generation (RAG), semantic search, recommendation systems, and image or video similarity search. What are the prerequisites for installing Milvus on GCP? You need basic knowledge of Google Cloud Platform, an active Google account with a GCP project and billing enabled, and sufficient Compute Engine CPU quota in your target region to launch the required machine type. Which machine type is recommended? e2-standard-2 (2 vCPUs, 8 GB memory) is the vendor-recommended default in the deployment form. Choose a larger General purpose or Compute-optimised machine type for heavier workloads. How do I connect to Milvus after launching it? Use the pymilvus SDK to connect to the instance's public IP address on port 19530 with the default root credentials, or point your own client at that endpoint. What is the default username and password? The Milvus GCP image ships with the default admin user root and password Milvus. Change this password immediately after your first login for production use. How do I handle upgrades? When a new image version is available in the GCP Marketplace, back up your Milvus data, delete the previous deployment, and relaunch with the new version. How do I get technical support? Reach out to Meetrix Support at [support@meetrix.io](mailto:support@meetrix.io) for assistance with Milvus issues. ## Deploy Milvus Vector Database on GCP in Minutes Launch a production-ready, self-hosted Milvus vector database on Google Cloud with a pre-configured Meetrix image. 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