Our Monitoring Backbone Uptime Kuma

A deep look into how Iridium Works builds a multi layer monitoring system that ensures reliability through open source tools custom automation and proactive alerts.

Why Monitoring Is One of the Strongest Foundations of Our Client Operations

Monitoring is not an accessory in modern software development. It is an essential safety layer that ensures stability performance and trust. At Iridium Works we built a monitoring stack that combines open source flexibility with custom automation so we always know how our systems behave long before users feel an issue.

Our Monitoring Backbone Uptime Kuma

Uptime Kuma is an open source monitoring tool that allows us to track service availability with full control. Unlike closed platforms we can extend adapt and integrate it deeply into our workflow.

Below is a simplified overview of what we monitor:

Monitoring LayerDescription
HTTP Status CodesContinuous checks to detect failures slow responses or recurring error patterns
Health EndpointsDirect checks of backend service status through dedicated /health routes
API Route MonitoringCustom payloads that verify expected responses for critical API flows
Slack AlertsImmediate notifications when conditions occur such as non recovering services

Custom Payload Checks for API Routes

Certain business critical processes can only be validated through the exact data an API returns. For this reason we use custom payload checks. Each check ensures that the service not only responds but behaves correctly.

Here is an example of how such a check can look in principle:

// Pseudocode example for a custom API validation 
const response = await fetch("https://api.example.com/status", { method: "POST", body: JSON.stringify({ token: "12345" }) })

if (response.status !== 200) alert("Service unreachable")
if (response.data.health !== "ok") alert("Unexpected API state")

Understanding the Role of HTTP Status Codes in Monitoring

HTTP status codes are one of the most fundamental signals for identifying issues in digital systems. Each request between a client and a server produces a numeric code that reflects the outcome of the operation. Codes in the 200 range indicate that everything works as expected. Codes in the 300 range show redirections that may or may not be intentional. Errors become visible starting in the 400 range when requests cannot be fulfilled usually due to client side issues. Codes in the 500 range point to server side failures that require immediate attention. By continuously monitoring these status codes we gain early insight into performance degradation recurring error patterns or sudden outages. This layer forms the fastest and most direct indicator of system health.

Status Code Range Meaning
100–199 Informational responses indicating that the request is being processed
200–299 Successful responses showing that the request completed correctly
300–399 Redirection responses requiring the client to take further action
400–499 Client errors caused by invalid requests or missing permissions
500–599 Server errors indicating failures within the application or infrastructure

Our Self Developed Slack App

We designed a Slack integration that connects directly to a webhook. It triggers the moment monitoring thresholds are reached for example if a service fails two retry attempts. This gives our team real time awareness.

Advantages of This Setup

AdvantageImpact
Full control through open sourceNo vendor lock in and the freedom to extend or customize
Layered monitoringDetects issues early across multiple dimensions
Direct Slack alertsFaster reaction time and reduced downtime
Custom payload checksValidates entire business flows not just server responses

Possible Limitations

LimitationDescription
Manual configurationLarger infrastructures require initial setup work
No native anomaly detectionAdvanced analytics require external tooling
Scaling complexityWith many services dashboards become more complex

Potential Future Extensions

ExtensionValue
Automated incident classificationFaster triage based on predefined rules
AI based anomaly detectionProactive alerts when patterns change unexpectedly
Integration with deployment pipelinesAutomatic checks after releases for safer rollouts

Monitoring is one of the most powerful tools to ensure reliability. The stronger the monitoring layer the more confidence your users have in the product you deliver.

About the Author

Alessandro is a technical mastermind and Chief Technology Officer at Iridium Works. Over the years he has build countless systems working with Front- and BackEnd, DevOps and as a Tech Lead. He writes about new technology, software development.

Alessandro Frank
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at Iridium Works
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Koblenz, Germany
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