diff --git a/source/cloud/gcp/compute-engine.md b/source/cloud/gcp/compute-engine.md
index 567ab1db..c2acd797 100644
--- a/source/cloud/gcp/compute-engine.md
+++ b/source/cloud/gcp/compute-engine.md
@@ -6,11 +6,11 @@ review_priority: "p1"
 
 ## Create Virtual Machine
 
-Create a new [Compute Engine Instance](https://cloud.google.com/compute/docs/instances) with GPUs, the [NVIDIA Driver](https://www.nvidia.co.uk/Download/index.aspx) and the [NVIDIA Container Runtime](https://developer.nvidia.com/nvidia-container-runtime).
+Create a new [Compute Engine Instance](https://console.cloud.google.com/compute/overview) with GPUs, the [NVIDIA Driver](https://www.nvidia.com/drivers/) and the [NVIDIA Container Runtime](https://developer.nvidia.com/nvidia-container-runtime).
 
 NVIDIA maintains a [Virtual Machine Image (VMI) that pre-installs NVIDIA drivers and container runtimes](https://console.cloud.google.com/marketplace/product/nvidia-ngc-public/nvidia-gpu-optimized-vmi), we recommend using this image.
 
-1. Open [**Compute Engine**](https://console.cloud.google.com/compute/instances).
+1. Open [**Compute Engine**](https://console.cloud.google.com/compute/overview).
 1. Select **Create Instance**.
 1. Select the **Create VM from..** option at the top.
 1. Select **Marketplace**.
@@ -19,6 +19,11 @@ NVIDIA maintains a [Virtual Machine Image (VMI) that pre-installs NVIDIA drivers
 1. **Read and accept** the Terms of Service
 1. Select **Deploy** to start the virtual machine.
 
+```{note}
+If you run into any UI issues while selecting the tile for **NVIDIA GPU-Optimized VMI** follow
+the this link to [Deploy a VM with NVIDIA GPU-Optimized VMI](https://console.cloud.google.com/marketplace/product/nvidia-ngc-public/nvidia-gpu-optimized-vmi). This should redirect you to the last step to be able to deploy the VM.
+```
+
 ## Allow network access
 
 To access Jupyter and Dask we will need to set up some firewall rules to open up some ports.