- Add AI_FEATURES_ENABLED config flag to gate AI/natural-language features - Conditionally register /api/ask router based on AI_FEATURES_ENABLED - Add GET /api/config/features endpoint for frontend feature detection - Update frontend to hide Ask panel when AI features are disabled - Implement standalone MCP server (backend/mcp_server.py) with tools: * search_events, get_event, get_summary, ask - Add mcp dependency to requirements.txt - Update .env.example, AGENTS.md, and ROADMAP.md - Bump VERSION to 1.3.0
74 lines
3.4 KiB
Markdown
74 lines
3.4 KiB
Markdown
# AOC Roadmap
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This roadmap tracks planned improvements for the Admin Operations Center (AOC) project, organized by phase.
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---
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## Phase 1: Harden ✅
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Goal: fix critical security and reliability gaps before production use.
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- [x] Fix JWT signature verification in `auth.py`
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- [x] Fix broken frontend auth button references (`loginBtn` / `logoutBtn`)
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- [x] Add MongoDB indexes (`dedupe_key`, `timestamp`, `service+timestamp`, `id`, text search)
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- [x] Add MongoDB TTL index for data retention (`RETENTION_DAYS`)
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- [x] Add `/health` endpoint with database connectivity check
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- [x] Replace manual `os.getenv` parsing with Pydantic Settings (`pydantic-settings`)
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- [x] Add structured JSON logging (`structlog`)
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- [x] Configure CORS middleware via `CORS_ORIGINS` environment variable
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- [x] Escape user input before MongoDB `$regex` queries (`routes/events.py`)
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- [x] Fix incorrect return value in `maintenance.py dedupe()`
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---
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## Phase 2: Stabilize ✅
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Goal: improve resilience, code quality, and development experience.
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- [x] Cache Graph API tokens and reuse them until near expiry
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- [x] Add exponential backoff / retry logic for Graph API and Office 365 API calls
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- [x] Add unit tests for `normalize_event()`, `_make_dedupe_key()`, and `auth.py`
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- [x] Add integration tests for `/api/events` and `/api/fetch-audit-logs`
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- [x] Configure linter/formatter (`ruff`) and pre-commit hooks
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- [x] Set up GitHub Actions CI pipeline (lint + test)
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- [x] Add Pydantic request/response models for API endpoints
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- [x] Validate `page_size` and `hours` with strict FastAPI constraints
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---
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## Phase 3: Scale ✅
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Goal: handle larger data volumes and support real-time ingestion.
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- [x] Replace skip-based pagination with cursor-based (search-after) pagination
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- [x] Add Prometheus `/metrics` endpoint and a Grafana dashboard
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- [x] Implement incremental fetch watermarking per source (store last fetch timestamp)
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- [x] Add webhook endpoints to receive Microsoft Graph change notifications
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- [x] Evaluate Elasticsearch or Azure Cognitive Search for advanced full-text search (MongoDB text index sufficient for current scale)
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- [x] Add request ID / correlation ID middleware for distributed tracing
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---
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## Phase 4: Enhance ✅
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Goal: evolve from a polling dashboard into a full security operations tool.
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- [x] Migrate frontend to Alpine.js for better state management and maintainability
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- [x] Add rule-based alerting (e.g., alert on privileged operations, after-hours activity)
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- [x] Add SIEM export (Splunk, Sentinel, syslog webhook)
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- [x] Build an audit trail for AOC itself (who queried what, who triggered fetches)
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- [x] Add event tagging and commenting (e.g., `investigating`, `false_positive`)
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- [x] Add export functionality (CSV / JSON) from the UI
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- [x] Add source health dashboard showing last fetch time and status per source
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---
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## Phase 5: Intelligence
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Goal: add AI-powered analysis and external tool integration.
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- [x] AI feature flag (`AI_FEATURES_ENABLED`) to gate LLM-dependent features
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- [x] Natural language query endpoint (`/api/ask`) with intent extraction and smart sampling
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- [x] MCP (Model Context Protocol) server for Claude Desktop / Cursor integration
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- [ ] Advanced analytics dashboard (trending operations, anomaly detection)
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- [ ] Redis caching for LLM responses and frequent queries
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- [ ] Async queue for LLM requests to prevent timeout/cost explosions at scale
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## Completed in this PR
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All Phase 5 items marked done were implemented in v1.3.0.
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