Getting Started with LogTrunk

Step 1: Installation

LogTrunk is available for macOS, Windows, and Linux. Download the latest version from our homepage or directly from GitHub releases.

macOS

1. Download the .dmg file for your architecture (Apple Silicon or Intel)
2. Open the DMG and drag LogTrunk to your Applications folder
3. Right-click and select "Open" the first time to bypass Gatekeeper

Windows

1. Download the .exe installer
2. Run the installer and follow the prompts
3. LogTrunk will be available in your Start menu

Linux

1. Download the .deb package
2. Install with: sudo dpkg -i LogTrunk_*.deb
3. Run logtrunk from your terminal or application menu

Step 2: Create Your First Tab

LogTrunk uses tabs to organize different log sources. Each tab can have multiple sources and its own parser configuration.

1. Launch LogTrunk
2. Click the + button in the tab bar
3. Give your tab a name (e.g., "My App Logs")

Think of tabs as separate workspaces. You might have one tab for your backend services, another for your frontend, and another for database logs.

Step 3: Add a Log Source

Now let's add a source to receive logs. The easiest way to get started is with a TCP source.

1. In your tab, click TCP in the source toolbar
2. Enter a port number (e.g., 9000)
3. Make sure the source is enabled (checkbox checked)

LogTrunk will immediately start listening on that port. The status indicator will show green when the source is active.

Step 4: Send Test Logs

Let's send some test logs to verify everything is working. Open your terminal and run:

echo "Hello from LogTrunk!" | nc localhost 9000

You should see the message appear in LogTrunk immediately!

Try sending a JSON log to see automatic parsing:

echo '{"level":"info","message":"User logged in","user_id":123}' | nc localhost 9000

LogTrunk will automatically detect and parse JSON, extracting fields like level, message, and user_id.

Step 5: Next Steps

Now that you have LogTrunk running, here are some things to explore:

• Configure parsing - Set up JSON, Grok, or regex parsers for your log format
• Use filters - Filter logs by field values to focus on what matters
• Pin important logs - Keep critical logs visible while streaming continues
• Add markers - Mark deployment times or important events in your log stream
• Connect Claude - Use AI to help analyze and debug your logs