Send logs over HTTP, syslog, OTLP/OpenTelemetry, GELF, Kubernetes agents, Fluent Bit, rsyslog/syslog-ng, or client libraries. Then read streams with live tail, filters, facets, histograms, alerts, scoped tokens, MCP diagnostics, and AI-assisted analysis.
JSON batches plus Go, Python, PHP, NestJS, Node.js, Java, Rust, and .NET libraries.
RFC 3164/5424, rsyslog, syslog-ng, receiver ports, and stream routing.
OTLP logs with service context, trace IDs, span IDs, and telemetry fields.
Application log payloads for stacks that already emit Graylog-style events.
DaemonSet collection, Fluent Bit forwarding, pod metadata, and cluster filters.
Exception search, error summaries, receiver health checks, no-log diagnostics, and AI chat.
Use HTTP JSON batches, syslog, OTLP/OpenTelemetry, GELF, Kubernetes agents, Fluent Bit, rsyslog/syslog-ng, or application clients for Go, Python, PHP, NestJS, Node.js, Java, Rust, and .NET.
Use streams and receivers, live tail, multi-stream scope, host/app/severity filters, labels, Kubernetes filters, histograms, facets, historical windows, and bounded rendering for noisy bursts.
Use scoped access tokens, hosted OAuth MCP, receiver health checks, usage and quota alerts, exception search, error summaries, no-log diagnostics, and built-in AI chat for investigation.
Use the links below for protocol intake, collector setup, live reading, and AI-assisted diagnostics.
Open the syslog server page for RFC 3164/5424 syslog, rsyslog, syslog-ng, receiver ports, and stream routing.
Open OpenTelemetry logging for service and trace context, or OTLP logs when payload shape and protocol handling are the main concern.
Open Kubernetes logging for cluster sources, live log viewer for real-time reading, or AI log analysis for summaries and diagnostics.
Open the Fluxtail feature page for the source, protocol, or log-reading task you care about.
Fluxtail acts as a central syslog server for hosts, VMs, appliances, routers, firewalls, rsyslog, syslog-ng, and legacy services. Create a syslog receiver, point senders at the assigned host and port, then inspect live rows by host, app, severity, message, and time.
OpenTelemetry logging is most useful when logs keep service identity, environment, severity, body fields, trace_id, and span_id. Fluxtail receives OTel-style telemetry logs, keeps common fields searchable when present, and makes them readable through live tail, filters, facets, histograms, alerts, MCP diagnostics, and AI chat.
Use OTLP logs when services already emit OpenTelemetry log data and need a structured transport path into Fluxtail. An OTLP log path should preserve resource attributes, service context, severity, timestamps, log attributes, and trace identifiers when those fields are present.
Kubernetes logging is useful when pod, container, namespace, node, service, and label context survive collection. Fluxtail receives cluster logs into streams and keeps those fields available for live tail, filters, facets, histograms, alerts, MCP diagnostics, and AI chat.
Use AI log analysis in Fluxtail to group repeated failures, summarize a bounded time window, check receiver health, and jump back into the raw log rows that support the answer.
Watch active production logs in Fluxtail as they arrive. Use live tail to confirm receivers are accepting traffic, follow deploy output, filter noisy streams, inspect rows, and debug failures while they are still happening.
Point one syslog, OTLP, Kubernetes, or application source at Fluxtail and inspect the resulting logs.
A real stream will tell you more than another round of comparison shopping.
