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121 lines
3.1 KiB
Markdown
121 lines
3.1 KiB
Markdown
# 📈 Aralez Prometheus Metrics Reference
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This document outlines Prometheus metrics for the [Aralez](https://github.com/sadoyan/aralez) reverse proxy.
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These metrics can be used for monitoring, alerting and performance analysis.
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Exposed to `http://config_address/metrics`
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By default `http://127.0.0.1:3000/metrics`
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# 📊 Example Grafana dashboard during stress test :
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---
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## 🛠️ Prometheus Metrics
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### 1. `aralez_requests_total`
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- **Type**: `Counter`
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- **Purpose**: Total amount requests served by Aralez.
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**PromQL example:**
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```promql
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rate(aralez_requests_total[5m])
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```
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---
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### 2. `aralez_errors_total`
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- **Type**: `Counter`
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- **Purpose**: Count of requests that resulted in an error.
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**PromQL example:**
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```promql
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rate(aralez_errors_total[5m])
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```
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---
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### 3. `aralez_responses_total{status="200"}`
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- **Type**: `CounterVec`
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- **Purpose**: Count of responses by HTTP status code.
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**PromQL example:**
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```promql
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rate(aralez_responses_total{status=~"5.."}[5m]) > 0
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```
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> Useful for alerting on 5xx errors.
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---
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### 4. `aralez_response_latency_seconds`
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- **Type**: `Histogram`
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- **Purpose**: Tracks the latency of responses in seconds.
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**Example bucket output:**
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```prometheus
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aralez_response_latency_seconds_bucket{le="0.01"} 15
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aralez_response_latency_seconds_bucket{le="0.1"} 120
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aralez_response_latency_seconds_bucket{le="0.25"} 245
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aralez_response_latency_seconds_bucket{le="0.5"} 500
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...
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aralez_response_latency_seconds_count 1023
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aralez_response_latency_seconds_sum 42.6
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```
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| Metric | Meaning |
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|-------------------------|---------------------------------------------------------------|
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| `bucket{le="0.1"} 120` | 120 requests were ≤ 100ms |
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| `bucket{le="0.25"} 245` | 245 requests were ≤ 250ms |
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| `count` | Total number of observations (i.e., total responses measured) |
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| `sum` | Total time of all responses, in seconds |
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### 🔍 How to interpret:
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- `le` means “less than or equal to”.
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- `count` is total amount of observations.
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- `sum` is the total time (in seconds) of all responses.
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**PromQL examples:**
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🔹 **95th percentile latency**
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```promql
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histogram_quantile(0.95, rate(aralez_response_latency_seconds_bucket[5m]))
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```
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🔹 **Average latency**
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```promql
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rate(aralez_response_latency_seconds_sum[5m]) / rate(aralez_response_latency_seconds_count[5m])
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```
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---
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## ✅ Notes
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- Metrics are registered after the first served request.
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---
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✅ Summary of key metrics
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| Metric Name | Type | What it Tells You |
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|---------------------------------------|------------|---------------------------|
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| `aralez_requests_total` | Counter | Total requests served |
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| `aralez_errors_total` | Counter | Number of failed requests |
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| `aralez_responses_total{status="200"}` | CounterVec | Response status breakdown |
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| `aralez_response_latency_seconds` | Histogram | How fast responses are |
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📘 *Last updated: May 2025*
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