Superlog

Enables natural-language querying and investigation of homelab logs from syslog, Docker, OTLP, and AI transcripts, with SQLite full-text search, timeline correlation, incident clustering, and fleet topology insights.

Enables coding agents to observe any running process — syscalls, CPU flamegraphs, thread stacks, sockets and file descriptors, packets, heap retainers, and container state — without breakpoints, restarts, or instrumentation. It turns output from local tools like strace, py-spy, perf, lsof, tcpdump, and gdb/lldb into structured findings that cite evidence, supporting guided triage of leaks, slowness, hangs, and crashes.

Enables AI agents to query traces, sessions, exceptions, prompts, datasets, scores, and metrics for enhanced debugging and observability. Supports local stdio or HTTP deployment, selective tool loading, and read-only mode.

Connects AI agents to live observability stacks including Sentry, GitHub, Vercel, Better Stack, and Cloudflare, enabling end-to-end incident investigation, deployment correlation, root cause analysis, and regression triage.