Integrating Prometheus into Our Cloud Management Platform

Introduction

As our infrastructure continues to evolve and scale, so does the need for deep, real-time visibility into the health and performance of our systems. Monitoring is no longer just about uptime checks—it’s about understanding trends, anticipating failures, and optimizing resource usage. To address these demands and enhance the observability of our Cloud Management Platform (CMP), we have successfully integrated Prometheus, a widely adopted open-source monitoring and alerting toolkit. This integration not only enables proactive issue detection but also ensures that our engineering and operations teams can make faster, data-driven decisions for improved platform reliability and performance.

Why Prometheus?

Prometheus was selected due to its flexibility, powerful features, and widespread community adoption. Here are the key reasons we chose it:

✔ Time-series Data Collection via Pull-based HTTP Endpoints

Prometheus collects metrics data from configured targets by periodically sending HTTP requests to endpoints that expose data in a simple text-based format. Each metric is stored as a time series, allowing us to track changes over time, analyze trends, and correlate metrics across services.

✔ Flexible Querying using PromQL

PromQL (Prometheus Query Language) is a powerful and expressive language that allows users to query real-time data from Prometheus in a human-readable way. With PromQL, we can write queries to extract metrics, perform calculations, and build meaningful dashboards. For example, we can easily detect CPU usage spikes or count error responses per service.

Observability Benefits in Our CMP

With Prometheus integrated, we can now gather deeper insights into our system:

Infrastructure and Resource Utilization

Track CPU usage, memory usage, disk usage, system uptime, and CPU count of the VMs. This allows for better infrastructure planning, workload balancing, and detecting over-/underutilized

How We Integrated Prometheus

We integrated Prometheus with our Ruby-based backend by both instrumenting services and consuming Prometheus metrics directly via its HTTP API.

• Metrics Visualization Using Prometheus HTTP API:

In addition to service-level instrumentation, we implemented functionality in our Ruby backend to query the Prometheus HTTP API. This allows us to retrieve time-series metrics such as CPU usage, memory consumption, and request rates directly from Prometheus.

• Frontend Display with PatternFly:

The retrieved metrics data is passed to the frontend, where we use PatternFly components to present it in a clean, interactive UI. This includes graphs, tables, and alerts that help users quickly understand system performance and health at a glance.

Sample Use Cases

Here’s how Prometheus is already delivering value within our platform:

Capacity Planning

By analyzing historical CPU, memory, and I/O data from Prometheus, we can forecast infrastructure needs and plan hardware or instance provisioning in advance. This helps prevent resource shortages and enables cost-optimized scaling strategies.

Root Cause Analysis

During incidents or anomalies, Prometheus enables fast drill-down into specific metrics. With metrics retained over time, we can correlate symptoms with changes or deployments, aiding faster issue resolution.

Compliance Monitoring

Uptime and usage metrics from Prometheus help us verify compliance with internal SLAs and external regulatory requirements. For example, we can track whether services meet 99.9% uptime targets or detect underutilized resources for cost optimization.

Conclusion

The integration of Prometheus into our Cloud Management Platform has established a strong, extensible foundation for observability. By combining service-level instrumentation with real-time metric queries via the Prometheus HTTP API and visualizing those metrics using PatternFly in our frontend, we’ve built a powerful and user-friendly monitoring layer. This enables our teams to detect issues early, understand system behavior in depth, and make data-driven decisions with confidence. As we scale the platform and integrate tools like Grafana and more advanced alerting logic, Prometheus will continue to serve as a critical pillar in ensuring reliability, transparency, and performance across our infrastructure.