Monitoring modern applications requires more than just logs or metrics. With microservices, containers, and cloud-native tools, observability is key. At Essid Solutions, we implement full-stack observability using OpenTelemetry to unify logs, metrics, and traces across systems.

🔧 What Is OpenTelemetry?

OpenTelemetry (OTel) is an open-source standard for collecting telemetry data:

• Traces – Track how a request flows through services
• Metrics – Measure performance and resource usage
• Logs – Record detailed events for debugging

With OTel, you can collect all three from multiple services in a vendor-neutral way.

⚖️ Benefits of Full-Stack Observability with OTel

• Unified view across frontend, backend, and cloud
• Faster root cause detection and resolution
• No vendor lock-in (compatible with Datadog, Prometheus, Grafana, etc.)
• Works across languages (Python, Node.js, Java, Go, .NET)

🌐 Example Architecture

[ App Services: Python APIs, Frontend, DB ]
       |
       v
[ OpenTelemetry SDKs / Agents ]
       |
       v
[ Collector ] --> [ Exporters: Prometheus, Jaeger, Grafana, Datadog ]

🔬 Tools We Integrate With OTel

• Backend Monitoring: Prometheus, Jaeger, Zipkin, New Relic, Datadog
• Frontend Tracing: Web SDKs + Browser telemetry
• Dashboards: Grafana, OpenObserve, Sentry
• Export Formats: OTLP, JSON, gRPC, HTTP

💼 Use Case: Kubernetes-Based SaaS App

A client running microservices on EKS needed unified observability. We:

• Instrumented Python, Node.js, and Go services with OTel SDKs
• Deployed OpenTelemetry Collector as a sidecar in Kubernetes
• Exported traces to Jaeger and metrics to Prometheus + Grafana

Result: Reduced MTTR (Mean Time to Resolution) by 65% and improved on-call efficiency.

📅 Upgrade Your Monitoring with OpenTelemetry

We’ll help you go beyond basic logs and metrics with unified observability.

👉 Request an OTel implementation call
Or email: hi@essidsolutions.com