The modern landscape of cloud-native infrastructure demands a level of visibility that transcends the boundaries of individual clusters and isolated accounts. As organizations scale their containerized workloads using Amazon Elastic Kubernetes Service (Amazon EKS), they inevitably encounter the challenge of fragmented observability. While Amazon Managed Service for Prometheus (AMP) provides a highly scalable, Prometheus-compatible monitoring and alerting service designed to handle massive amounts of metric data, its architecture is fundamentally built around workspaces. In a multi-cluster or multi-account environment, this creates a significant operational hurdle: each Prometheus workspace exists as an independent data silo. Without an intermediary, an engineer attempting to build a global view of their infrastructure must manually configure separate queries for every single workspace within their visualization layer. This fragmentation leads to dashboard bloat, increased management overhead, and a lack of cohesive visibility across the entire fleet of applications.
To solve this, a sophisticated architectural pattern involves the deployment of an aggregation layer using Promxy, an open-source Prometheus proxy. By implementing this proxy, it becomes possible to present multiple Amazon Managed Service for Prometheus workspaces as a single, unified data source. This allows Amazon Managed Grafana—a fully managed service that eliminates the operational burden of provisioning servers, configuring software, or managing scaling and security—to query a single endpoint. This unified endpoint then intelligently routes queries to the appropriate backend workspaces. This architecture not only simplifies the Grafana configuration but also enables the creation of complex, cross-workspace dashboards that provide a holistic view of health, performance, and latency across diverse Kubernetes environments.
The Architectural Components of a Unified Observability Stack
Building a robust monitoring pipeline requires the orchestration of several distinct AWS managed services and open-source utilities. Each component plays a specific role in the ingestion, aggregation, and visualization of telemetry data.
The foundation of the compute layer is Amazon Elastic Kubernetes Service (Amazon EKS). While EKS is not an absolute mandatory component for the entire architecture—as the core goal is the aggregation of Prometheus data—it serves as the ideal hosting environment for the proxy layer. EKS provides the managed Kubernetes control plane necessary to run complex, containerized workloads such as the NGINX controller and the Promxy deployment itself.
For the metrics layer, Amazon Managed Service for Prometheus acts as the long-term storage and query engine for time-series data. It is designed to scale automatically with the volume of metrics being ingested from containerized applications. Because it is Prometheus-compatible, it integrates natively with the existing ecosystem of exporters and collectors.
The visualization layer is handled by Amazon Managed Grafana. This service is critical for reducing the "heavy lifting" associated with production-grade Grafana instances. It handles the authentication credentials required to access Prometheus workspaces, manages the scaling of the Grafana engine, and provides a seamless interface for analyzing metrics, logs, and traces.
Finally, the aggregation layer consists of:
- Promxy: An open-source utility that functions as a proxy, intercepting queries and fetching data from multiple remote Prometheus workspaces.
- AWS SigV4 Proxy: A Kubernetes sidecar container essential for adding the necessary AWS Signature Version 4 authentication to HTTP requests, allowing the proxy to communicate securely with AWS managed services.
- NGINX Controller: A component used within the EKS cluster to provide basic authentication and traffic management for the proxy.
- Application Load Balancer (ALB) Controller: An AWS controller that manages the lifecycle of an AWS Application Load Balancer, providing an external entry point for Grafana to reach the Promxy service.
Orchestrating the Promxy Deployment on Amazon EKS
Deploying a unified query layer requires a precise sequence of configuration steps to ensure that the proxy can securely reach the back-end Prometheus workspaces while remaining accessible to Grafana.
The deployment process begins with the preparation of the Amazon EKS cluster. Once the cluster is operational, the deployment of the Application Load Balancer controller is necessary to automate the provisioning of AWS network resources. Following this, the NGINX controller must be deployed to handle the ingress traffic and enforce security policies, such as basic authentication, which prevents unauthorized access to the aggregated metrics.
The core of the deployment involves the Promxy configuration. This is not a simple "plug-and-play" operation; it requires managing authentication and the proxy's internal routing logic. Because Amazon Managed Service for Prometheus requires AWS Signature Version 4 (SigV4) for all API requests, a standard Prometheus proxy cannot communicate with it directly without assistance. The solution is to deploy an AWS SigV4 Proxy as a sidecar container within the Promxy pod. This sidecar intercepts the outgoing requests from Promxy, signs them with the appropriate AWS credentials, and forwards them to the Prometheus workspaces.
The technical steps for the deployment are as follows:
- Prepare the Amazon EKS cluster to support containerized workloads and add-ons.
- Deploy the Application Load Balancer controller to manage AWS ALB resources.
- Deploy the NGINX controller for ingress management and basic authentication.
- Configure Promxy authentication by preparing the SigV4 proxy sidecar.
- Update the deployment.yaml file within the directory
~/ekspromxy/promxy/deploy/k8s/helm-charts/promxy/templatesto include the sidecar container. - Install the Promxy helm chart into a dedicated namespace (e.g.,
promxy) using a pre-configured override file. - Verify the deployment by checking that the pods and services for the controllers and Promxy are running.
- Retrieve the Application Load Balancer URL using the following command:
kubectl get svc -n promxy(or the specific command provided in the deployment workflow to obtain the ALB URL).
| Component | Role | Technology Type |
|---|---|---|
| Amazon EKS | Orchestration and compute hosting | AWS Managed Service |
| Amazon Managed Service for Prometheus | Metric storage and querying | AWS Managed Service |
| Amazon Managed Grafana | Data visualization and analysis | AWS Managed Service |
| Promxy | Metric aggregation and query routing | Open-Source Utility |
| SigV4 Proxy | Request signing and AWS authentication | Kubernetes Sidecar |
| NGINX Controller | Ingress control and basic authentication | Open-Source/Kubernetes |
| ALB Controller | AWS Load Balancer management | AWS/Kubernetes Controller |
Configuring Amazon Managed Grafana for Unified Data Access
Once the Promxy proxy is operational and accessible via an Application Load Balancer, the final phase is configuring Amazon Managed Grafana to recognize this new, unified data source. The power of this configuration lies in its simplicity: instead of managing dozens of different Prometheus data sources, the administrator manages only one.
The configuration process is performed through the Amazon Managed Grafana console. This involves establishing a connection that points Grafana to the URL of the Load Balancer serving the Promxy instance. Because Amazon Managed Grafana is designed to simplify the connection to AWS services, it can manage the underlying authentication complexity once the initial link is established.
Detailed configuration steps:
- Access the Amazon Managed Grafana console and log in to your specific Grafana workspace URL.
- Navigate to the Configuration menu and select Data sources.
- Click on the option to Add data source and select Prometheus from the list of available types.
- Provide a descriptive Name for the data source (e.g., "Unified AWS Prometheus").
- Enter the URL obtained from the ALB deployment step in the URL field.
- Configure any necessary authentication settings if required by your specific NGINX setup.
In addition to metrics, this architecture allows for advanced dashboarding capabilities. Users can leverage pre-built dashboards, such as the "AWS Prometheus" dashboard, which provides out-of-the-box visualization for over 60 different AWS resources. This can be extended to include CloudWatch data sources, allowing for a "single pane of glass" that combines Prometheus metrics with CloudWatch logs and metrics for EC2, S3, and other critical services.
Security Considerations and Operational Constraints
While this architecture provides immense visibility benefits, it introduces specific security responsibilities that must be addressed before moving into a production environment. It is critical to recognize that Promxy is an open-source project and does not carry official AWS support. Consequently, users must perform rigorous security assessments and implement their own hardening measures.
The primary security concern involves the exposure of the Promxy endpoint. Since the proxy is intended to be accessible to Grafana, the NGINX controller must be configured to enforce strict access controls. Implementing basic authentication or integrating with an identity provider is a mandatory step to prevent unauthorized parties from querying your infrastructure metrics.
Furthermore, the use of the SigV4 Proxy sidecar is a critical security component. Without the sidecar, the proxy would be unable to present the necessary credentials to the Amazon Managed Service for Prometheus workspaces, rendering the entire pipeline non-functional. The sidecar ensures that the principle of least privilege can be maintained by using IAM roles for service accounts (IRSA) within EKS, allowing only the necessary permissions to be granted to the proxy.
When evaluating the costs and scalability of the visualization layer, users should consider the different tiers of Grafana Cloud if they choose to extend beyond the managed AWS service:
- Grafana Cloud Free Tier: Provides a limited experience with a maximum of 3 users.
- Grafana Cloud Paid Plans: Costs approximately $55 per user per month above the included usage limits.
- Enterprise Plugins: Access to advanced features is available through paid plans.
- Management Model: Grafana Cloud is a fully managed service and does not offer self-management options.
Analysis of the Unified Observability Pattern
The implementation of Promxy as an aggregation layer between Amazon Managed Grafana and multiple Amazon Managed Service for Prometheus workspaces represents a significant shift from fragmented monitoring to unified observability. This architectural pattern addresses the fundamental limitation of workspace-based isolation by providing a logical abstraction layer that treats a distributed fleet of clusters as a single entity.
From a DevOps perspective, the reduction in configuration complexity is the most significant advantage. The ability to use a single Grafana data source eliminates the need for repetitive, error-prone dashboard updates whenever a new cluster or workspace is added to the environment. Instead, the update is handled within the Promxy configuration, allowing the visualization layer to remain static and stable.
However, this complexity is moved from the visualization layer to the infrastructure layer. The management of the EKS cluster, the maintenance of the SigV4 sidecar, and the orchestration of the NGINX and ALB controllers require a high level of Kubernetes expertise. Organizations must weigh the benefits of simplified dashboard management against the increased operational burden of maintaining the proxy infrastructure.
Ultimately, for large-scale enterprises operating hundreds of microservices across multiple AWS accounts, the architectural benefits of unified querying far outweigh the overhead. The ability to perform cross-cluster correlation—such as tracking a single request's latency as it traverses multiple Kubernetes clusters—is only possible through this type of aggregated observability strategy.