Log Timeline Visualizer
Paste raw logs → get a chronological, grouped timeline of what happened.
No timeline yet. Paste logs above and click Visualize timeline, or try a sample.
How it works
1. Paste your logs
Plain text or structured JSON - the parser auto-detects timestamps, log levels, and request/trace IDs across common formats.
2. Flows are reconstructed
Related log lines are grouped into a single request/trace flow, even when no explicit correlation ID exists (falls back to worker-thread session detection).
3. Spot errors and slow gaps
Every flow is rendered as a timeline with time deltas between events. Gaps past your threshold, and every error, are flagged and jump-to-able.
Parsing and rendering both happen locally in JavaScript. Nothing you paste is uploaded, stored, or sent to any server.
What Is Log Timeline Visualizer?
Log Timeline Visualizer is a free, browser-based log timeline visualizer and log analyzer built for developers, SREs, and DevOps engineers who need to make sense of raw application logs quickly. Instead of scrolling through thousands of unordered log lines, you paste your logs, either plain text or structured JSON, and the tool instantly reconstructs a chronological, grouped timeline of what actually happened. As a log parser, it automatically detects timestamps across common formats, including ISO 8601, syslog, US date, and Unix epoch, classifies log levels such as INFO, WARN, ERROR, and FATAL, and identifies request IDs, trace IDs, and correlation IDs so related events end up in a single, readable flow instead of scattered across a wall of text.
Why Developers Use This Free Online Log Analyzer
Debugging a production incident usually starts the same way: a dump of raw logs, no obvious order, and a handful of request IDs you have to trace by eye. Log Timeline Visualizer removes that manual step. As a log correlation tool, it groups related log lines into a single request or trace flow automatically, and when a service does not emit an explicit trace ID, it falls back to worker-thread session detection to reconstruct the flow anyway. This makes it especially useful as a microservices log analyzer and distributed tracing companion, where a single user action can touch multiple services and log streams. Whether you are an SRE triaging an outage, a backend engineer reviewing a failed deployment, or a QA engineer reproducing a bug, this online log viewer turns disconnected log lines into a timeline you can actually read, in seconds, without installing anything.
Key Features
Key features include a timestamp parser that recognizes ISO 8601, syslog, US date, and Unix epoch formats automatically, log level detection that highlights TRACE, DEBUG, INFO, WARN, ERROR, and FATAL with color-coded badges, and request and trace ID grouping that reconstructs each request or trace flow even across services. The built-in JSON log parser understands structured, pretty-printed JSON log objects as easily as plain text, including mixed formats in the same paste. Slow-gap detection flags unusually large time gaps between events so you can spot exactly where a request stalled, multi-line stack traces are automatically collapsed under the log line that raised them so an error log stays readable instead of flooding the page, and a dedicated error insights panel jumps you straight to every failure in the timeline. Perhaps most importantly, everything runs one hundred percent client-side: every line you paste is parsed and rendered locally in your browser, and nothing is uploaded, stored, or sent to a server, so this stays safe to use even with sensitive internal logs.
Frequently Asked Questions
Is Log Timeline Visualizer free to use?
Yes. It is completely free, with no account, sign-up, or usage limit of any kind.
Does this tool upload or store my log data?
No. Parsing happens entirely in your browser using JavaScript, and your logs are never transmitted to any server or stored anywhere.
What log formats are supported?
Both plain-text logs with timestamps and structured JSON log objects are supported, including mixed formats pasted together in the same window.
How does it group logs without a trace ID?
If no request ID, trace ID, or correlation ID is present in a log line, the tool falls back to detecting worker-thread sessions and API endpoints to approximate the flow automatically.
Can I use it for microservices or distributed systems logs?
Yes, it is commonly used as a lightweight distributed tracing and log correlation tool for reconstructing request flows when a full observability platform is not available or is simply overkill for the task at hand.
Which languages and log formats does it work with?
Any log output works as long as it includes a recognizable timestamp - this covers Java, Node.js, Python, Go, and most other backend stacks, whether they log in plain text or as structured JSON.