Filebeat Multiline Pattern Design Prompt
Design and test a Filebeat multiline parser that correctly stitches stack traces and multi-line log events into single documents without merging unrelated lines or losing the last event.
- Target user
- Engineers taming Java, Python, and application stack-trace logs in Filebeat
- Difficulty
- Intermediate
- Tools
- Claude, ChatGPT, Cursor
The prompt
You are a senior Filebeat engineer who writes multiline parsers that fold stack traces and wrapped log lines into clean single events without ever swallowing the next record. I will provide: - 10-20 representative raw log lines including at least one multi-line event (stack trace, pretty-printed JSON, or SQL dump) - The application/framework and its log format - Whether I use the `log` input (`multiline.*`) or `filestream` input (`parsers: - multiline:`) - Filebeat version Your job: 1. **Identify the anchor** — determine what reliably marks the START of a new event (timestamp prefix, log level, bracketed thread) versus continuation lines, and choose `pattern` + `negate` + `match` (or `flush_pattern`) accordingly. 2. **Write the parser** — produce the exact `multiline` block for my input type, with a regex tuned to the anchor, and explain each field (`pattern`, `negate`, `match: after`, `max_lines`, `timeout`). 3. **Guard the limits** — set `max_lines` and confirm `max_bytes` handling so a runaway trace does not create a multi-megabyte event, and explain what gets truncated when limits hit. 4. **Prove it** — walk through how the pattern groups my sample lines line-by-line, and show one adversarial case (two events with no blank line between) to prove it does not over-merge. 5. **Tune the timeout** — recommend `multiline.timeout` so the last event of an idle file flushes promptly without prematurely cutting an in-progress trace. Output as: the ready-to-paste multiline config, a line-by-line grouping trace against my samples, and the regex explained in plain English. Default to caution: never ship a multiline pattern that has not been validated against real logs, and prefer a slightly conservative pattern that occasionally splits over one that merges unrelated events.
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