### Open-source observability platform with S3 storage Ingest and explore logs, traces, and metrics stored in your S3 buckets. Query with natural language. Create AI agents that detect anomalies and send daily/weekly reports to your inbox. [![GitHub Release](https://img.shields.io/github/v/release/monoscope-tech/monoscope?include_prereleases)](https://github.com/monoscope-tech/monoscope/releases) [![License](https://img.shields.io/badge/license-AGPL--3.0-blue.svg)](LICENSE) [![Haskell](https://img.shields.io/badge/Built%20with-Haskell-5e5086?logo=haskell)](https://www.haskell.org/) [![Discord](https://img.shields.io/discord/904634773329297429?color=7289da&logo=discord&logoColor=white)](https://discord.gg/BSFCaUHxt4) [**Website**](https://monoscope.tech) • [**Playground**](https://app.monoscope.tech/p/00000000-0000-0000-0000-000000000000/log_explorer) • [**Discord**](https://discord.gg/BSFCaUHxt4) • [**Twitter**](https://x.com/monoscope-tech) • [**Documentation**](https://docs.monoscope.tech)

What is Monoscope? • Cloud vs Self-hosted • Quick Start • AI Agents • Roadmap

Monoscope Dashboard

## What is Monoscope? Monoscope is an open-source observability platform that stores your telemetry data in S3-compatible storage. Self-host it or use our [cloud offering](https://monoscope.tech). **Core capabilities:** - 💰 **S3 storage** — Store years of logs, metrics, and traces affordably in your own S3 buckets - 💬 **Natural language queries** — Search your data using plain English via LLMs - 🤖 **AI agents** — Create agents that run on a schedule to detect anomalies and surface insights - 📧 **Email reports** — Receive daily/weekly summaries of important events and anomalies - 🔭 **OpenTelemetry native** — 750+ integrations out of the box - ⚡ **Live tail** — Stream logs and traces in real-time - 🕵️ **Unified view** — Correlate logs, metrics, traces, and session replays in one place
## Cloud vs Self-hosted In both options, you bring your own S3 buckets—your data stays yours. | | Cloud | Self-hosted | |---|---|---| | **Storage** | Your S3 buckets | Your S3 buckets | | **Compute** | Managed by us | You manage | | **Auth & SSO** | Built-in | DIY | | **Alert channels** | Slack, PagerDuty, etc. | Basic email | | **Pricing** | [Usage-based](https://monoscope.tech/pricing) | Free (AGPL-3.0) | → [Start free on Cloud](https://monoscope.tech) or continue below to self-host.
## Quick Start ```bash git clone https://github.com/monoscope-tech/monoscope.git cd monoscope docker-compose up ``` Visit `http://localhost:8080` (default: admin/changeme) ### Send Test Data Populate your dashboard with test telemetry: ```bash monoscope auth login # Single event — see your message appear in the dashboard monoscope send-event -m "Hello from Monoscope" # Sustained load — stress-test the pipeline monoscope telemetrygen --kind=trace --rate=5 --count=50 ```
## CLI Manage your Monoscope project from the terminal — search logs, query metrics, manage monitors and dashboards, triage issues, and more. ```bash curl https://monoscope.tech/install.sh | sh monoscope auth login ``` See the [CLI reference](docs/cli.md) for the full command list. ### Agentic pipeline Every CLI command emits a stable JSON envelope, so you can chain discovery → search → triage without manual munging. This is the same pipeline a Claude Code skill runs end-to-end: ```bash # 1. What services exist? (Precomputed; no aggregation query needed.) SVC=$(monoscope facets resource.service.name --top 1 \ | jq -r '.["resource.service.name"][0].value') # 2. Grab one error event from that service — id only, ready to chain. ID=$(monoscope logs search 'severity.text=="error"' \ --service "$SVC" --first --id-only) # 3. Pull the surrounding 5 minutes of traffic, with a per-trace summary # showing which other services were affected. monoscope events context --window 5m --summary \ --at "$(monoscope events get "$ID" | jq -r .timestamp)" \ | jq '.traces | sort_by(-.error_count) | .[0:3]' # 4. Acknowledge the open issue once you have a hypothesis. monoscope issues list --service "$SVC" --status open \ | jq -r '.data[].id' | head -3 \ | xargs -I {} monoscope issues ack {} ``` Each step's output shape is documented and stable: | Command | Envelope | |---|---| | `facets [FIELD]` | `{: [{value, count}, ...]}` | | `events search` (and `logs`/`traces`) | `{events: [...], count, has_more, cursor}` | | `events context --summary` | `{events, count, traces: [{trace_id, services, span_count, error_count}]}` | | `issues list`, `monitors list`, ... | `{data: [...], pagination: {has_more, total, cursor, page, per_page}}` | | `auth status` (agent mode) | `{authenticated, method, api_url, project}` | Set `MONOSCOPE_AGENT_MODE=1` (or run with `--agent`) to force JSON output and disable interactive prompts — auto-detected when `CI` or `CLAUDE_CODE` is set. ### Claude Code Skills Let Claude investigate incidents, triage alerts, and write KQL queries using the `monoscope` CLI — install the skills plugin: ```bash # Claude Code claude plugin marketplace add monoscope-tech/skills claude plugin install monoscope-skills@monoscope-skills # or via npx (Cursor, Cline, Copilot, and other agents) npx skills add monoscope-tech/skills ``` Restart Claude Code after installation. Skills activate automatically when relevant — e.g. *"investigate the 500 errors in payment-api"* or *"do an on-call sweep"*. See [github.com/monoscope-tech/skills](https://github.com/monoscope-tech/skills) for the full skill list and documentation.
## MCP Server Monoscope exposes itself as a [Model Context Protocol](https://modelcontextprotocol.io/) server at `/api/v1/mcp`, so any MCP-aware client (Claude Desktop, Cursor, Cline, custom agents) can search events, manage monitors and dashboards, triage issues, and run composite workflows like `search_events_nl` (natural-language → KQL) and `analyze_issue` (LLM-assisted root-cause). ```json { "mcpServers": { "monoscope": { "url": "https://api.monoscope.tech/api/v1/mcp", "headers": { "Authorization": "Bearer YOUR_API_KEY" } } } } ``` Every public REST endpoint is auto-registered as a verb-first tool (`list_monitors`, `search_events`, `mute_monitor`, …). See the [MCP reference](docs/mcp.md) for the full protocol, tool catalog, and examples.
## Integration ### Auto-instrument your apps

Python

```bash pip install opentelemetry-distro opentelemetry-exporter-otlp opentelemetry-bootstrap -a install OTEL_SERVICE_NAME="my-app" \ OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4317" \ opentelemetry-instrument python myapp.py ```

Node.js

```bash npm install --save @opentelemetry/auto-instrumentations-node OTEL_SERVICE_NAME="my-app" \ OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4317" \ node --require @opentelemetry/auto-instrumentations-node/register app.js ```

Java

```bash curl -L https://github.com/open-telemetry/opentelemetry-java-instrumentation/releases/latest/download/opentelemetry-javaagent.jar -o otel-agent.jar OTEL_SERVICE_NAME="my-app" \ OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4317" \ java -javaagent:otel-agent.jar -jar myapp.jar ```

Kubernetes

```bash # Install OpenTelemetry Operator kubectl apply -f https://github.com/open-telemetry/opentelemetry-operator/releases/latest/download/opentelemetry-operator.yaml # Configure auto-instrumentation kubectl apply -f - <
## Natural Language Queries Query your telemetry data in plain English: - "Show me all errors in the payment service in the last hour" - "What caused the spike in response time yesterday?" - "Which endpoints have the highest p99 latency?"
## AI Agents & Reports Create AI agents that monitor your systems on a schedule: - **Scheduled analysis** — Agents run at intervals you define (hourly, daily, weekly) - **Anomaly detection** — Automatically surface unusual patterns in logs, metrics, and traces - **Email reports** — Receive summaries of important events and insights directly in your inbox - **Customizable focus** — Configure agents to watch specific services, error types, or metrics
## Architecture ```mermaid graph LR A[Your Apps] -->|Logs/Metrics/Traces| B[Ingestion API] B --> C[TimeFusion Engine] C --> D[(S3 Storage)] D --> E[Query Engine] E --> F[Dashboards] D --> G[AI Agent Scheduler] G -->|LLM Analysis| H[Anomaly Detection] H --> I[Email Reports] H --> J[Alert Channels] ``` ### Project Structure Monoscope is organized into four primary components: - **`app/`** — Haskell server binary (WAI/Yesod web application) - **`cli/`** — Command-line interface for managing projects, querying data, and automating workflows - **`web-components/`** — Custom UI elements (Web Components) for dashboards and log exploration - **`src/`** — Core Haskell library exporting shared types, utilities, and business logic ### Powered by TimeFusion Monoscope is built on [**TimeFusion**](https://github.com/monoscope-tech/timefusion), our open-source time-series database for observability workloads. | | | |---|---| | 🗄️ **S3-native** | Data lives in your S3 buckets—no vendor lock-in | | 🐘 **PostgreSQL compatible** | Use any Postgres client or driver | | ⚡ **500K+ events/sec** | Columnar storage with Apache Arrow | | 💵 **Pay only for S3** | No expensive proprietary storage fees |
## How It Compares | Feature | Monoscope | Datadog | Elastic | Prometheus | | ---------------------- | ----------- | --------- | ------- | ---------- | | S3/Object Storage | ✅ Native | ❌ | ✅ | ✅ | | Natural Language Query | ✅ | ❌ | ❌ | ❌ | | AI Agents & Reports | ✅ Built-in | ❌ Add-on | ❌ | ❌ | | Open Source | ✅ AGPL-3.0 | ❌ | ✅ | ✅ | | Self-hostable | ✅ | ❌ | ✅ | ✅ |
## Screenshots ### Log Explorer - Unified View Logs and trace spans displayed together in context for complete observability. Log Explorer Main View

Log Explorer Main View

### Trace Context Integration See detailed trace information alongside logs for debugging complex distributed systems. Log Explorer with Trace Context

Log Explorer with Trace Context

### Dashboard Analytics Real-time metrics and performance monitoring with AI-powered insights. Dashboard Analytics View

Dashboard Analytics View

## Trusted by Leading Companies

> "Monoscope notifies us about any slight change on the system. Features that would cost us a lot more elsewhere." — **Samuel Joseph, Woodcore**
## Documentation - [Getting Started Guide](docs/getting-started.md) - [CLI Reference](docs/cli.md) - [MCP Server](docs/mcp.md) - [Configuration](docs/configuration.md) - [Kubernetes Guide](docs/kubernetes.md) - [Development Guide](docs/DEVELOPMENT.md)
## Roadmap - [x] Custom dashboards builder - [ ] More out-of-the-box dashboards - [ ] AIOps workflow builder - [ ] Full migration to TimeFusion storage engine - [ ] Metrics aggregation rules - [ ] Multi-tenant workspace support - [ ] More alert channel integrations See our [public roadmap](https://github.com/monoscope-tech/monoscope/projects) for details and to vote on features.
## Community 💬 [Discord](https://discord.gg/BSFCaUHxt4) • 🐛 [Issues](https://github.com/monoscope-tech/monoscope/issues) • 🐦 [Twitter](https://x.com/monoscope-tech)
## License AGPL-3.0. See [LICENSE](LICENSE) for details. For commercial licensing options, contact us at [hello@monoscope.tech](mailto:hello@monoscope.tech). ---