Tailor Your Cloud Dashboards: A Step-by-Step Guide to Customizing AWS, Azure, and GCP Views in Grafana Cloud

Introduction

Cloud Provider Observability in Grafana Cloud gives you prebuilt dashboards and drill-downs for AWS, Azure, and Google Cloud. These out-of-the-box views include service overviews, instance-level details, and quick links—perfect for getting started. But you may already have trusted dashboards, need a team-specific layout, or want to change the panels that appear when drilling into a single resource. Good news: you can customize all of this without leaving the app. This guide walks you through three methods: connecting an existing dashboard, creating one with AI and wiring it in, and editing the instance drill-down views that appear across Cloud Provider Observability, Database Observability, and the entity graph. By the end, you'll have a tailored monitoring experience that fits your workflow.

What You Need

• Grafana Cloud account – with Cloud Provider Observability enabled for AWS, Azure, or Google Cloud.
• Cloud provider credentials – properly configured so data streams into Grafana.
• Permissions – editing access to dashboards and the configured cloud services.
• Optional: Existing dashboards you want to link, or a Grafana AI subscription to generate dashboards.

Step-by-Step Customization Guide

1. Step 1: Access the Configure Page for a Cloud Service

   Navigate to the Services tab in Cloud Provider Observability. You’ll see a list of cloud services (e.g., Amazon RDS, Azure Virtual Machines, GCP Cloud SQL). For the service you want to customize, click the Configure button next to it. This opens the service’s configuration page, where all customization happens. Here you’ll find:

   • Preconfigured dashboard – the built-in view for that service.
   • Custom dashboards – any you’ve added as quick links, with one designated as default.
   • Explore-style links for metrics and Grafana Metrics Drilldown.

   Everything you save here is reused wherever that service appears—services tab, entity graph, Database Observability, etc.

2. Step 2: Connect an Existing Dashboard

   If you already have a dashboard that fits this service (e.g., an internal view for RDS or Lambda), you can attach it as a quick link or set it as the default. On the configure page, scroll to the section “Customize your quick links and add new ones to your custom dashboards.” Click Select a dashboard and pick from your existing dashboards. To make it the default, check the box “Set as default dashboard.” Users will then see this dashboard when opening the service from the Services tab, entity graph, or other entry points. Added dashboards become extra quick links for alternative views.

3. Step 3: Create a Dashboard with AI and Wire It In

   Need a tailored view but short on time? Use Grafana AI to generate a dashboard. Create the AI-generated dashboard with the appropriate variables and methodology (e.g., using the same data source and metric naming conventions). Once saved, go back to the configure page, click “Select a dashboard,” and choose your AI dashboard. You can set it as default or keep it as an additional quick link. This way, AI-created views integrate into the same workflows and debugging paths as manual ones.

4. Step 4: Edit the Instance Drill-Down Views

   To change what panels appear when you drill into a single instance (e.g., clicking on an RDS instance), use the “Customize the panels…” section on the configure page. Here you can adjust queries and panel layouts. The panels you configure are rendered everywhere the instance-level view appears—Cloud Provider Observability, Database Observability, entity graph, etc. This ensures consistent, custom insights no matter how you navigate. After editing, click Save to apply changes across all surfaces.

5. Step 5: Review and Test Your Customizations

   After saving, open the service from the Services tab, entity graph, or any other entry point to verify your changes. Check that the default dashboard loads correctly, quick links appear, and instance drill-downs show the panels you configured. If something’s off, return to the configure page to tweak.

Tips for Success

• Start with one service – Master the process on a single cloud service before rolling out to others to avoid confusion.
• Use consistent variables – When creating custom or AI dashboards, ensure they use the same variable names (e.g., $datasource, $instance) as the prebuilt ones for seamless integration.
• Test drill-downs thoroughly – The instance-level view is reused across multiple surfaces; validate that all panels display data correctly for different resources.
• Leverage AI for inspiration – Let AI generate a starting point, then manually refine it to match your exact needs.
• Document your defaults – If you set a custom dashboard as default, inform your team so they know what to expect.
• Remember permissions – Only users with edit access can customize; readers see the final configuration.

Customizing Cloud Provider Observability gives you the flexibility to combine out-of-the-box efficiency with your own expertise. Whether you reuse existing dashboards, generate new ones with AI, or refine drill-downs, you gain consistent visibility across your cloud stack.