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Author SHA1 Message Date
Sheen Capadngan
ff043f990f doc: monitoring telemetry 2025-08-18 14:20:45 +08:00
Vlad Matsiiako
ef6f79f7a6 Merge pull request #4387 from Infisical/secrets-missing-docs
Bring Back Missing Secrets Documentation
2025-08-16 22:28:39 +08:00
2 changed files with 442 additions and 1 deletions

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@@ -310,7 +310,8 @@
"self-hosting/guides/mongo-to-postgres",
"self-hosting/guides/custom-certificates",
"self-hosting/guides/automated-bootstrapping",
"self-hosting/guides/production-hardening"
"self-hosting/guides/production-hardening",
"self-hosting/guides/monitoring-telemetry"
]
},
{

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---
title: "Monitoring and Telemetry Setup"
description: "Learn how to set up monitoring and telemetry for your self-hosted Infisical instance using Grafana, Prometheus, and OpenTelemetry."
---
Infisical provides comprehensive monitoring and telemetry capabilities to help you monitor the health, performance, and usage of your self-hosted instance. This guide covers setting up monitoring using Grafana with two different telemetry collection approaches.
## Overview
Infisical exports metrics in **OpenTelemetry (OTEL) format**, which provides maximum flexibility for your monitoring infrastructure. While this guide focuses on Grafana, the OTEL format means you can easily integrate with:
- **Cloud-native monitoring**: AWS CloudWatch, Google Cloud Monitoring, Azure Monitor
- **Observability platforms**: Datadog, New Relic, Splunk, Dynatrace
- **Custom backends**: Any system that supports OTEL ingestion
- **Traditional monitoring**: Prometheus, Grafana (as covered in this guide)
Infisical supports two telemetry collection methods:
1. **Pull-based (Prometheus)**: Exposes metrics on a dedicated endpoint for Prometheus to scrape
2. **Push-based (OTLP)**: Sends metrics to an OpenTelemetry Collector via OTLP protocol
Both approaches provide the same metrics data in OTEL format, so you can choose the one that best fits your infrastructure and monitoring strategy.
## Prerequisites
- Self-hosted Infisical instance running
- Access to deploy monitoring services (Prometheus, Grafana, etc.)
- Basic understanding of Prometheus and Grafana
## Environment Variables
Configure the following environment variables in your Infisical backend:
```bash
# Enable telemetry collection
OTEL_TELEMETRY_COLLECTION_ENABLED=true
# Choose export type: "prometheus" or "otlp"
OTEL_EXPORT_TYPE=prometheus
# For OTLP push mode, also configure:
# OTEL_EXPORT_OTLP_ENDPOINT=http://otel-collector:4318/v1/metrics
# OTEL_COLLECTOR_BASIC_AUTH_USERNAME=your_collector_username
# OTEL_COLLECTOR_BASIC_AUTH_PASSWORD=your_collector_password
# OTEL_OTLP_PUSH_INTERVAL=30000
```
**Note**: The `OTEL_COLLECTOR_BASIC_AUTH_USERNAME` and `OTEL_COLLECTOR_BASIC_AUTH_PASSWORD` values must match the credentials configured in your OpenTelemetry Collector's `basicauth/server` extension. These are not hardcoded values - you configure them in your collector configuration file.
## Option 1: Pull-based Monitoring (Prometheus)
This approach exposes metrics on port 9464 at the `/metrics` endpoint, allowing Prometheus to scrape the data. The metrics are exposed in Prometheus format but originate from OpenTelemetry instrumentation.
### Configuration
1. **Enable Prometheus export in Infisical**:
```bash
OTEL_TELEMETRY_COLLECTION_ENABLED=true
OTEL_EXPORT_TYPE=prometheus
```
2. **Expose the metrics port** in your Infisical backend:
- **Docker**: Expose port 9464
- **Kubernetes**: Create a service exposing port 9464
- **Other**: Ensure port 9464 is accessible to your monitoring stack
3. **Create Prometheus configuration** (`prometheus.yml`):
```yaml
global:
scrape_interval: 30s
evaluation_interval: 30s
scrape_configs:
- job_name: "infisical"
scrape_interval: 30s
static_configs:
- targets: ["infisical-backend:9464"] # Adjust hostname/port based on your deployment
metrics_path: "/metrics"
```
**Note**: Replace `infisical-backend:9464` with the actual hostname and port where your Infisical backend is running. This could be:
- **Docker Compose**: `infisical-backend:9464` (service name)
- **Kubernetes**: `infisical-backend.default.svc.cluster.local:9464` (service name)
- **Bare Metal**: `192.168.1.100:9464` (actual IP address)
- **Cloud**: `your-infisical.example.com:9464` (domain name)
### Deployment Options
#### Docker Compose
```yaml
services:
prometheus:
image: prom/prometheus:latest
ports:
- "9090:9090"
volumes:
- ./prometheus.yml:/etc/prometheus/prometheus.yml:ro
command:
- "--config.file=/etc/prometheus/prometheus.yml"
grafana:
image: grafana/grafana:latest
ports:
- "3000:3000"
environment:
- GF_SECURITY_ADMIN_USER=admin
- GF_SECURITY_ADMIN_PASSWORD=admin
```
#### Kubernetes
```yaml
# prometheus-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
template:
metadata:
labels:
app: prometheus
spec:
containers:
- name: prometheus
image: prom/prometheus:latest
ports:
- containerPort: 9090
volumeMounts:
- name: config
mountPath: /etc/prometheus
volumes:
- name: config
configMap:
name: prometheus-config
---
# prometheus-service.yaml
apiVersion: v1
kind: Service
metadata:
name: prometheus
spec:
selector:
app: prometheus
ports:
- port: 9090
targetPort: 9090
type: ClusterIP
```
#### Helm
```bash
helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm install prometheus prometheus-community/prometheus \
--set server.config.global.scrape_interval=30s \
--set server.config.scrape_configs[0].job_name=infisical \
--set server.config.scrape_configs[0].static_configs[0].targets[0]=infisical-backend:9464
```
## Option 2: Push-based Monitoring (OTLP)
This approach sends metrics directly to an OpenTelemetry Collector via the OTLP protocol. This gives you the most flexibility as you can configure the collector to export to multiple backends simultaneously.
### Configuration
1. **Enable OTLP export in Infisical**:
```bash
OTEL_TELEMETRY_COLLECTION_ENABLED=true
OTEL_EXPORT_TYPE=otlp
OTEL_EXPORT_OTLP_ENDPOINT=http://otel-collector:4318/v1/metrics
OTEL_COLLECTOR_BASIC_AUTH_USERNAME=infisical
OTEL_COLLECTOR_BASIC_AUTH_PASSWORD=infisical
OTEL_OTLP_PUSH_INTERVAL=30000
```
2. **Create OpenTelemetry Collector configuration** (`otel-collector-config.yaml`):
```yaml
extensions:
health_check:
pprof:
zpages:
basicauth/server:
htpasswd:
inline: |
your_username:your_password
receivers:
otlp:
protocols:
http:
endpoint: 0.0.0.0:4318
auth:
authenticator: basicauth/server
prometheus:
config:
scrape_configs:
- job_name: otel-collector
scrape_interval: 30s
static_configs:
- targets: [infisical-backend:9464]
metric_relabel_configs:
- action: labeldrop
regex: "service_instance_id|service_name"
processors:
batch:
exporters:
prometheus:
endpoint: "0.0.0.0:8889"
auth:
authenticator: basicauth/server
resource_to_telemetry_conversion:
enabled: true
service:
extensions: [basicauth/server, health_check, pprof, zpages]
pipelines:
metrics:
receivers: [otlp]
processors: [batch]
exporters: [prometheus]
```
**Important**: Replace `your_username:your_password` with your chosen credentials. These must match the values you set in Infisical's `OTEL_COLLECTOR_BASIC_AUTH_USERNAME` and `OTEL_COLLECTOR_BASIC_AUTH_PASSWORD` environment variables.
3. **Create Prometheus configuration** for the collector:
```yaml
global:
scrape_interval: 30s
evaluation_interval: 30s
scrape_configs:
- job_name: "otel-collector"
scrape_interval: 30s
static_configs:
- targets: ["otel-collector:8889"] # Adjust hostname/port based on your deployment
metrics_path: "/metrics"
```
**Note**: Replace `otel-collector:8889` with the actual hostname and port where your OpenTelemetry Collector is running. This could be:
- **Docker Compose**: `otel-collector:8889` (service name)
- **Kubernetes**: `otel-collector.default.svc.cluster.local:8889` (service name)
- **Bare Metal**: `192.168.1.100:8889` (actual IP address)
- **Cloud**: `your-collector.example.com:8889` (domain name)
### Deployment Options
#### Docker Compose
```yaml
services:
otel-collector:
image: otel/opentelemetry-collector-contrib:latest
ports:
- 4318:4318 # OTLP http receiver
- 8889:8889 # Prometheus exporter metrics
volumes:
- ./otel-collector-config.yaml:/etc/otelcol-contrib/config.yaml:ro
command:
- "--config=/etc/otelcol-contrib/config.yaml"
```
#### Kubernetes
```yaml
# otel-collector-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: otel-collector
spec:
replicas: 1
selector:
matchLabels:
app: otel-collector
template:
metadata:
labels:
app: otel-collector
spec:
containers:
- name: otel-collector
image: otel/opentelemetry-collector-contrib:latest
ports:
- containerPort: 4318
- containerPort: 8889
volumeMounts:
- name: config
mountPath: /etc/otelcol-contrib
volumes:
- name: config
configMap:
name: otel-collector-config
```
#### Helm
```bash
helm repo add open-telemetry https://open-telemetry.github.io/opentelemetry-helm-charts
helm install otel-collector open-telemetry/opentelemetry-collector \
--set config.receivers.otlp.protocols.http.endpoint=0.0.0.0:4318 \
--set config.exporters.prometheus.endpoint=0.0.0.0:8889
```
## Alternative Backends
Since Infisical exports in OpenTelemetry format, you can easily configure the collector to send metrics to other backends instead of (or in addition to) Prometheus:
### Cloud-Native Examples
```yaml
# Add to your otel-collector-config.yaml exporters section
exporters:
# AWS CloudWatch
awsemf:
region: us-west-2
log_group_name: /aws/emf/infisical
log_stream_name: metrics
# Google Cloud Monitoring
googlecloud:
project_id: your-project-id
# Azure Monitor
azuremonitor:
connection_string: "your-connection-string"
# Datadog
datadog:
api:
key: "your-api-key"
site: "datadoghq.com"
# New Relic
newrelic:
apikey: "your-api-key"
host_override: "otlp.nr-data.net"
```
### Multi-Backend Configuration
```yaml
service:
pipelines:
metrics:
receivers: [otlp]
processors: [batch]
exporters: [prometheus, awsemf, datadog] # Send to multiple backends
```
## Setting Up Grafana
1. **Access Grafana**: Navigate to your Grafana instance
2. **Login**: Use your configured credentials
3. **Add Prometheus Data Source**:
- Go to Configuration → Data Sources
- Click "Add data source"
- Select "Prometheus"
- Set URL to your Prometheus endpoint
- Click "Save & Test"
## Available Metrics
Infisical exposes the following key metrics in OpenTelemetry format:
### API Performance Metrics
- `API_latency` - API request latency histogram in milliseconds
- **Labels**: `route`, `method`, `statusCode`
- **Example**: Monitor response times for specific endpoints
- `API_errors` - API error count histogram
- **Labels**: `route`, `method`, `type`, `name`
- **Example**: Track error rates by endpoint and error type
### Integration & Secret Sync Metrics
- `integration_secret_sync_errors` - Integration secret sync error count
- **Labels**: `version`, `integration`, `integrationId`, `type`, `status`, `name`, `projectId`
- **Example**: Monitor integration sync failures across different services
- `secret_sync_sync_secrets_errors` - Secret sync operation error count
- **Labels**: `version`, `destination`, `syncId`, `projectId`, `type`, `status`, `name`
- **Example**: Track secret sync failures to external systems
- `secret_sync_import_secrets_errors` - Secret import operation error count
- **Labels**: `version`, `destination`, `syncId`, `projectId`, `type`, `status`, `name`
- **Example**: Monitor secret import failures
- `secret_sync_remove_secrets_errors` - Secret removal operation error count
- **Labels**: `version`, `destination`, `syncId`, `projectId`, `type`, `status`, `name`
- **Example**: Track secret removal operation failures
### System Metrics
These metrics are automatically collected by OpenTelemetry's HTTP instrumentation:
- `http_server_duration` - HTTP server request duration metrics (histogram buckets, count, sum)
- `http_client_duration` - HTTP client request duration metrics (histogram buckets, count, sum)
### Custom Business Metrics
- `infisical_secret_operations_total` - Total secret operations
- `infisical_secrets_processed_total` - Total secrets processed
## Troubleshooting
### Common Issues
1. **Metrics not appearing**:
- Check if `OTEL_TELEMETRY_COLLECTION_ENABLED=true`
- Verify the correct `OTEL_EXPORT_TYPE` is set
- Check network connectivity between services
2. **Authentication errors**:
- Verify basic auth credentials in OTLP configuration
- Check if credentials match between Infisical and collector