A highly efficient utility to convert raw log files into Prometheus metrics, JSON, or CSV formats using customizable regex patterns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install log-parser-to-metrics
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install log-parser-to-metrics using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Log Parser to Metrics?
Log Parser to Metrics simplifies observability workflows by scanning unstructured logs in real-time and translating them into structured quantitative data. It solves the critical bottleneck of parsing messy multi-line logs, normalizing timestamps, and establishing structured metadata taxonomy for downstream monitoring suites.
This application gives developers and system administrators the agility to hook into log streams, automatically generate timeseries datasets, and directly export telemetry data. By leveraging Openclaw Skills, engineering teams can replace clunky custom shell integrations with a unified engine capable of handling intensive data streams.
Log Parser to Metrics Use Cases
- Production Debugging: Instantly monitor specific error patterns across hundreds of servers and parse raw logs into operational request-rate and latency metrics.
- Cost Optimization: Analyze infrastructure and cloud spend by extracting endpoint call frequencies and response sizes from massive API access logs.
- Security Auditing: Detect distributed brute-force attacks from authorization logs by isolating failed login attempts alongside attacker IP addresses into a time-series graph.
How Log Parser to Metrics Works
- Environment Verification: Validates system paths to ensure that the required core binary dependencies such as bash and curl are active.
- Log Stream Ingestion: Hooks directly into stdout or live log aggregations (e.g., via tail -f) to ingest sequential text lines.
- Regex Pattern Matching: Applies explicit regex expressions against raw text strings to cleanly isolate variables like IP address, timestamp, method, path, status, and payload size.
- Structured Format Export: Normalizes extracted tokens into telemetry formats including Prometheus gauge/counter syntax, JSON, or CSV matrixes.
Log Parser to Metrics Setup
System Requirements
Ensure you have bash and curl installed on your system.
Running the Engine
You can pipe standard log files directly into the utility to stream metrics:
tail -f /var/log/nginx/access.log | log-parser-to-metrics --pattern '{ip} - - [{time}] "{method} {path}" {status} {size}' --output prometheus
Log Parser to Metrics Data Schema & Taxonomy
Supported Output Taxonomy
| Property | Data Type | Description |
|---|---|---|
ip |
String | Source IP address of the requester. |
time |
Timestamp | Normalized ISO/Epoch timestamp string. |
method |
String | HTTP verb (GET, POST, PUT, DELETE, etc.). |
path |
String | Targeted endpoint URI resource path. |
status |
Integer | HTTP response status code (e.g., 200, 404, 500). |
size |
Integer | Volume of the payload distributed in bytes. |
Log Parser to Metrics Advanced Features
- Advanced Aggregation Engine (Pro): Perform real-time sliding window statistics, calculating percentiles directly from unorganized text streams.
- High-Volume Parallel Processing (Pro): Unlock a 10x performance boost using batch processing architectures that execute automatically over compressed log files.
- Enterprise Message Streaming (Pro): Integrate native real-time pipeline hooks with built-in Kafka and WebSocket protocol support.
SKILL.md
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