Rootprint

Coroot is an open-source observability and application performance monitoring (APM) tool that combines metrics, logs, distributed traces, continuous profiling, service maps, and SLO-based alerting. It uses eBPF for zero-instrumentation data collection, capturing requests and system activity without code changes, and provides predefined inspections, dashboards, application health summaries, log-pattern clustering, logs-to-traces correlation, and anomaly investigation. Coroot includes AI-powered root-cause analysis and built-in inspections that analyze application and infrastructure behavior, consolidate relevant findings into alerts, and recommend or identify likely fixes. It also tracks Kubernetes deployments, compares releases for performance changes, and provides application-level cost monitoring for AWS, GCP, and Azure. It can run as a Docker container or be deployed in Kubernetes. The project is licensed under the Apache License 2.0 and supports vendor-neutral instrumentation through OpenTelemetry.

modelprint is a browser-based tool for fingerprinting OpenAI-compatible API endpoints and investigating which model or serving infrastructure may sit behind an alias. It sends controlled probes and compares results side by side, including normalized tokenizer counts for English, CJK, code, and rare Unicode inputs; template offsets; validation messages and error codes; maximum-output refusals; finish-reason vocabulary; router metadata; generation records; response headers; provider path behavior; context-window classes; and logprob geometry. The tool runs without installation, a build step, or a server: API calls go directly from the browser to the provider, with keys retained in the browser tab. It can pin models to provider hosts to reduce routing noise and labels signals reported or validated by a router. Its documentation cautions that matching fingerprints indicate shared infrastructure or a model family rather than proving model identity, and that probes may report missing signals when headers, logprobs, or other telemetry are unavailable. The project supports community-authored probes through a defined JavaScript contract and is released under the MIT license.

NutriTrace is a self-hosted personal nutrition tracker developed by TraceApps. It runs as a single Docker container and provides a browser Progressive Web App and a native Android app for food diaries, meal and recipe logging, calorie and nutrition goals, adaptive TDEE tracking, intermittent fasting, manual activities, and wellness data. It can use Open Food Facts and USDA data, import recipes from Mealie, and integrate with Fitbit via Google Health, Withings, Garmin, and Health Connect. Its Trace AI features can read diary and wellness data, log food or activities conversationally, and propose food entries from photos for user confirmation. It also exposes selected diary, goal, and food data to external AI agents through an opt-in, read-only Model Context Protocol endpoint. The project supports multi-user access and OIDC single sign-on, provides migration tools for several nutrition trackers, and distributes its server as a Docker image. The source is licensed under AGPL-3.0; the project states that it has no telemetry or cloud synchronization unless a user opts into a third-party integration.

OpenResearch is a local-first workspace for research agents and autoresearch, available as a desktop application and a macOS/Linux CLI. It turns Claude Code, Codex, or OpenCode into agents that can review literature, develop hypotheses, run experiments, and produce research artifacts. The workspace assigns independent agent sessions and isolated Git worktrees to parallel research directions. It tracks experiment variants in a Git-native experiment tree, archives each run against its recorded commit, and keeps logs, diffs, files, results, and artifacts tied to the work that produced them. Its autoresearch loop can propose an idea, modify code, launch an experiment, inspect evidence, and choose the next direction. The same committed source snapshot can run locally or through SSH, Slurm, Kubernetes, Ray, Hugging Face Jobs, Modal, Tinker, or managed OpenResearch compute. By default, projects and run data remain on the user's machine in a local SQLite store, with a browser dashboard served on localhost. An OpenResearch account is used for service-owned capabilities such as organizations and managed compute. The CLI also installs an OpenResearch skill into supported coding agents and provides commands for projects, runs, logs, experiments, discovery, and paper lookup.

OpenObserve is an open-source, self-hosted observability platform for logs, metrics, traces, dashboards, frontend monitoring, pipelines, and incidents. It accepts OpenTelemetry data and provides SQL queries for logs and traces and SQL or PromQL queries for metrics. The platform is built in Rust and supports single-binary deployment, using Parquet columnar storage with an S3-native architecture; it also offers a unified web interface and cloud-hosted edition.