Promabbix

Connecting Prometheus to Zabbix.

TL;DR

This tooling allows you to keep you favourite monitoring tool Zabbix and have a production-ready integration with Prometheus in a way similar to AlertManager. It consists of 2 parts:

• Script to generate Zabbix Template from AlertManager-like definitions of Prometheus metrics
• GitOps tooling allowing you to manage the vast majority of your Zabbix installation in a Infrastructure-as-a-Code (IaaC) pattern (To-be-done)

Zabbix Meetup Introduction

Usage

CLI Commands

Promabbix provides a command-line interface with multiple subcommands:

# Show available commands
promabbix --help

# Generate Zabbix template from alert configuration
promabbix generateTemplate <config-file> [OPTIONS]

# Available options for generateTemplate:
#   -o, --output PATH          Output file path (use "-" for STDOUT, default: -)
#   -t, --templates PATH       Custom template directory path
#   -tn, --template-name NAME  Template file name (default: prometheus_alert_rules_to_zbx_template.j2)
#   --validate-only           Only validate configuration without generating template

Local Development Usage

# Install dependencies
pip install -r requirements.txt -r requirements-dev.txt

# Validate configuration only
python -m promabbix.promabbix generateTemplate examples/minikube-alert-config.yaml --validate-only

# Generate template to file
python -m promabbix.promabbix generateTemplate examples/minikube-alert-config.yaml -o output.json

# Generate template to STDOUT
python -m promabbix.promabbix generateTemplate examples/minikube-alert-config.yaml

# Read from STDIN and output to STDOUT
cat examples/minikube-alert-config.yaml | python -m promabbix.promabbix generateTemplate -

Docker Usage

# Build the image
docker buildx build -t promabbix:local .
# or use image from DockerHub:
# docker pull promabbix/promabbix

# Get help
docker run promabbix:local --help
docker run promabbix:local generateTemplate --help

# Read data from STDIN and output to STDOUT
cat examples/minikube-alert-config.yaml | docker run -i promabbix:local generateTemplate - -o -

# Run with mounted directory and retrieve result file
docker run --mount type=bind,src=$(pwd)/examples/,dst=/mnt promabbix:local generateTemplate /mnt/minikube-alert-config.yaml -o /mnt/output.json

# Validate configuration only
docker run --mount type=bind,src=$(pwd)/examples/,dst=/mnt promabbix:local generateTemplate /mnt/minikube-alert-config.yaml --validate-only

Prometheus (VictoriaMetrics) to Zabbix Integration (simplified version of docs to understand the gist)

Our monitoring stack combines the Prometheus metrics with Zabbix in the following way:

• zabbix-agents run on VMs and provide OS-level monitoring (mostly)
• Prometheus scrapes Kubernetes clusters and other dynamic environments
  • (End-result is that all metrics are sent to a single large VictoriaMetrics instance)
• we want all alerting and evaluation to be done in a single point that is Zabbix
• alerts are pushed to Slack and PagerDuty

Given these technologies have incompatible data model, we've come up with a following process on how to combine them:

• You define PromQL queries for your alerts (could be mostly taken from alertmanager templates without change)
  • The main difference is that we just take the alert calculation and leave out the threshold comparison - this way, we have a history for the value in Zabbix (and not just when the alert is triggered)
• Queries results are filtered with LLD to create (static number of) pseudo-hosts
  • Typically we use one pseudo-host for all Prod envs, QA envs
• Each pseudo-host will have items and triggers generated based on the definition
  • So that each time-series resulting from Query can be tracked separately
• ansible based tooling transfers YAML definitions to live Zabbix instance (so you can track all the definitions in Git with IaaC principles)
  • Zabbix Templates are used behind-the-scenes, so the definitions can be maintained for a long time and kept in sync

Configuration Formats

Promabbix supports two configuration formats:

Unified Configuration Format (Recommended)

The modern approach uses a single YAML file containing all configuration sections:

# Single unified configuration file (e.g., service-alerts.yaml)
groups:
  - name: recording_rules
    rules:
      - record: elasticsearch_cluster_health_red
        expr: sum(elasticsearch_cluster_health_status{color="red"}) by (cluster)
  - name: alerting_rules  
    rules:
      - alert: elasticsearch_cluster_health_red_simple
        expr: elasticsearch_cluster_health_red > 0
        annotations:
          description: "Elasticsearch cluster {{$labels.cluster}} is in RED state"
        labels:
          __zbx_priority: "AVERAGE"

prometheus:
  api:
    url: "http://victoria-metrics:8428/api/v1/query"
  labels_to_zabbix_macros:
    - pattern: '\{\{(?:\s*)\$value(?:\s*)\}\}'
      value: "{ITEM.VALUE1}"
    - pattern: '\{\{(?:\s*)\$labels\.(?P<label>[a-zA-Z0-9\_\-]*)(?:\s*)\}\}'
      value: "{#\\g<label>}"

zabbix:
  template: service_elasticsearch_cluster
  name: "Template Module Prometheus Elasticsearch Cluster"
  hosts:
    - host_name: elasticsearch-cluster-prod
      visible_name: "Service Elasticsearch Cluster PROD"
      host_groups: ["Prometheus pseudo hosts", "Production hosts"]
      link_templates: ["templ_module_promt_service_elasticsearch_cluster"]
      macros:
        - macro: "{$ES.CLUSTER.LLD.MATCHES}"
          value: "^prod-(us|eu)$"
  macros:
    - macro: "{$ES.THRESHOLD}"
      value: "1"
      description: "Elasticsearch cluster health threshold"

# Optional: Documentation for alerts
wiki:
  knowledgebase:
    alerts:
      alertings:
        "elasticsearch_cluster_health_red_simple":
          title: "Elasticsearch cluster in RED state" 
          content: "See runbook for troubleshooting steps"

Legacy Multi-File Format (Backward Compatible)

The legacy approach splits configuration across multiple files:

Configuration definitions

Typically each directory is related to a single service and contains 3 types of files.

• MYSERVICE_alerts.yaml - contains 2 parts:
  • recording_rules - these are being send to Prometheus/VictoriaMetrics backend for evaluation
  • alerting_rules - how are values from the previous point evaluated inside Zabbix

groups:
  - name: recording_rules
    rules:
      - record: elasticsearch_cluster_health_red
        # this expression is evaluated inside Prometheus/VictoriaMetrics
        expr: sum(elasticsearch_cluster_health_status{color="red"}) by (cluster)
  - name: alerting_rules
    rules:
      - alert: elasticsearch_cluster_health_red_simple
        # this experssion is a trigger rule inside of zabbix
        expr: elasticsearch_cluster_health_red > 0

      # multiple alerts can be used for the same metric
      - alert: elasticsearch_cluster_health_red_advanced
        # Zabbix macros can be also used
        expr: elasticsearch_cluster_health_red > {$ES.THRESHOLD}
        annotations:
          description: At least one member of Elasticsearch {{$labels.cluster}} is reporting RED state.  summary: Elasticsearch {{$labels.cluster}} (at least one node) is reporting RED state. 
        # Zabbix evaluation threshold
        for: 5m
        labels: # each alert can override general attributes
          __zbx_priority: "AVERAGE"
          grafana_dashboard: "p-abs/elasticsearch-clusters"

• zabbix_vars.yaml The LLD variables and pseudo-hosts definition - there are generated in Zabbix as Hosts

zabbix:
  template: service_elasticsearch_cluster
  name: "Template Module Prometheus service Elasticsearch Cluster"
  lld_filters:
    filter:
      conditions:
        - formulaid: "A"
          macro: "{#CLUSTER}" # ! "elasticsearch" cluster name
          value: "{$ES.CLUSTER.LLD.MATCHES}"
      evaltype: "AND"
  macros:
    - macro: "{$ES.CLUSTER.LLD.MATCHES}"
      description: "This macro is used in metrics discovery. Can be overridden on the host or linked template level."
      value: ".*"
    - macro: "{$SLACK.ALARM.CHANNEL.NAME}"
      description: "Macro for define additional endpoint for alert"
      value: "myteam_alerts"
  tags:
    - tag: service_kind
      value: elasticsearch
  hosts:
    - host_name: elasticsearch-cluster-prod
      visible_name: Service Elasticsearch Cluster PROD
      host_groups:
        - Prometheus pseudo hosts
        - Production hosts
        - Elasticsearch
      link_templates:
        - templ_module_promt_service_elasticsearch_cluster
      status: enabled
      state: present
      proxy: zbx-pr02
      macros:
        - macro: "{$ELASTICSEARCH.CLUSTER.LLD.MATCHES}"
          value: "^prod-(us|eu)$"
    - host_name: elasticsearch-cluster-qa
      visible_name: Service Elasticsearch Cluster QA
      host_groups:
        - Prometheus pseudo hosts
        - QA hosts
        - Elasticsearch
      link_templates:
        - templ_module_promt_service_elasticsearch_cluster
      status: enabled
      state: present
      proxy: zbx-pr02
      macros:
        - macro: "{$ELASTICSEARCH.CLUSTER.LLD.MATCHES}"
          value: "^(qa-.*)$"

  # you can customize alert messages
  labels:
    slack_alarm_channel_name: '{$SLACK.ALARM.CHANNEL.NAME:"{{$labels.job}}"}'
    grafana_dashboard: 'L-abc/elasticsearch-clusters'

• wiki_vars.yaml And you can define docs the the alert is trigger. This is passed to Slack/PagerDuty, so the duty person has the links to all diagnostics tools and typically some hint (redbook) on how to manage the particular alert

wiki:
  templates:
    wrike_alert_config:
      templates:
        - name: 'elasticsearch cluster'
          title: 'Alerts regarding Elasticsearch clusters'
  knowledgebase:
    alerts:
      alertings:
        "elasticsearch_cluster_health_red_simple":
          title: "Elasticsearch cluster in RED state"
          content: |
            {{toc/}}
            # Overview
            This documentation generated from YAML file.
            # How to investigate the case
            * Go to Grafana dashboard, [link](https://grafana.company.net/d/L-abc/elasticsearch-clusters).
            ...

Examples

• Generated pseudo-hosts in Zabbix

• LLD rules for the discovery on a template

• Zabbix Items collected on a host
  • There is one time for executing a query to Prometheus/VictoriaMetrics
  • For each time-series result, there is a separate Item tracking that particular combination of labels (and alert is connected to this Item)

• Item history can be visible in Zabbix

• When you receive an Alert in Slack, there are links to better align with a response

• If you receive an Alert via PagerDuty (mostly SysOps) - there is a clear connection to Zabbix Trigger (and Item triggering it)

• It is also possible to setup Zabbix Maintenance based on the Tags - so you won't receive the alerts (both in Slack and PagerDuty)

Limitations

• You need to use aggregate functions (max, sum etc.), otherwise the metrics are typically flaky or might lead to explosion of items in Zabbix (comes out of a lot of experience here)
• There are edge cases when the evaluation or logic is just different between Zabbix and Prometheus (typically for: clause)

Compatibility Zabbix 6.0+

Development

Project Structure

The project follows a modular architecture:

src/promabbix/
├── cli/                    # CLI command implementations
│   ├── generate_template.py   # generateTemplate command
│   └── __init__.py
├── core/                   # Core business logic modules
│   ├── fs_utils.py            # File system operations (DataLoader, DataSaver)
│   ├── template.py            # Jinja2 template rendering
│   ├── validation.py          # Configuration validation
│   ├── migration.py           # Legacy format migration
│   └── data_utils.py          # Data validation utilities
├── schemas/               # JSON/YAML schemas
│   └── unified.yaml          # Unified configuration schema
├── templates/             # Jinja2 templates
│   └── prometheus_alert_rules_to_zbx_template.j2
└── promabbix.py          # Main CLI entry point

Local Development Setup

# Create and activate virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt -r requirements-dev.txt

# Install additional type checking dependencies
pip install mypy types-PyYAML

# Run the CLI locally
PYTHONPATH=src python -m promabbix.promabbix generateTemplate --help

Running Tests

The project includes comprehensive unit tests covering all functionality with 92% code coverage.

# Run all tests
python -m pytest tests/ -v

# Run tests with coverage
python -m pytest tests/ -v --cov=src/promabbix --cov-report=term-missing

# Run tests with coverage requirement (80% minimum)
python -m pytest tests/ -v --cov-fail-under=80 --cov=src/promabbix --cov-report=term-missing --cov-report=xml

# Run using the test runner script (recommended)
python run_tests.py

Code Quality Checks

The project maintains high code quality standards:

# Run linting
flake8 src/ --count --max-complexity=10 --max-line-length=127 --statistics

# Run type checking
mypy src/ --ignore-missing-imports

# All quality checks together (CI pipeline)
python run_tests.py && flake8 src/ --count --max-complexity=10 --max-line-length=127 --statistics && mypy src/ --ignore-missing-imports

Architecture Overview

• CLI Layer: Click-based commands with proper argument parsing and help
• Business Logic: Core modules for validation, template rendering, and file operations
• Dependency Injection: Testable architecture with mockable dependencies
• Error Handling: Rich console output with user-friendly error messages
• Type Safety: Full type annotations and mypy compliance

See tests/README.md for detailed information about the test suite.