Analytics
Analytics recipes
17 admin-reviewed Analytics starting points in the Vault, each installable with one command. Browse every category →
BI Reporting & Warehouse Query Layer
Fast aggregate queries over ClickHouse for internal dashboards — distinct from ETL (which moves data in), Reverse ETL (which pushes data out), and Scheduled Reports (which generates and delivers files): this is live query serving for a BI tool or internal dashboard.
by @ops
Customer Data Platform / Unified Profile Backend
Merges customer data from multiple sources into one resolved profile via a worker doing the identity resolution — distinct from generic analytics: this is specifically about having one true record per customer, not aggregate reporting.
by @ops
Customer Health Score & Churn Signals
Engagement events rolled up into a health/churn-risk score per account, computed by a worker on a schedule rather than live on every dashboard load. For B2B SaaS teams who need to know which accounts are quietly disengaging before the cancellation email arrives.
by @ops
Deno + Postgres + Redis: URL Shortener & Link Analytics
Short-link generation, redirect handling, and click analytics — Redis for the redirect lookup that needs to be near-instant, Postgres for the click history behind it.
by @ops
Go + ClickHouse + Kafka
An event-ingestion pipeline: a Go API publishing to Kafka, with ClickHouse as the analytics store.
by @ops
Go + ClickHouse + Redis: Real-time Fraud Scoring at Scale
A worker scoring transaction streams against ClickHouse-stored patterns at real production volume — distinct from the Node-based Fraud & Anomaly Detection recipe: same problem, built for a much higher event-volume ceiling.
by @ops
Go + ClickHouse: A/B Test Statistical Significance Engine
A worker computing statistical significance over ClickHouse-scale event volume — distinct from the A/B Testing & Experimentation recipe: that assigns variants and tracks results, this is the heavier analytical engine crunching the numbers at real production traffic volume.
by @ops
Go + Postgres + Redis: Weather Data Aggregation & Threshold Alerting
Pulls weather data on a schedule and alerts when conditions cross a defined threshold — a worker doing the polling and evaluation, useful for agriculture, logistics, or event-planning use cases needing weather-aware automation.
by @ops
IoT Device Telemetry Ingestion
High-volume sensor/device data landing straight in ClickHouse, Redis buffering ahead of it — built for write volume a normal Postgres table would choke on. The same ingestion shape as the Logging & Metrics recipe, aimed at device telemetry instead of application logs.
by @ops
Marketing Attribution & UTM Tracking Backend
Campaign source/UTM tracking at real traffic volume via ClickHouse — distinct from generic analytics or the BI Reporting recipe: this is specifically "which channel actually drove this signup," not general event aggregation.
by @ops
PHP + Postgres + Redis: Self-hosted Privacy-first Web Analytics
Pageview and event tracking without cookies or third-party trackers — a self-hosted, privacy-respecting alternative pattern to sending every visitor's data to an external analytics vendor.
by @ops
Python + ClickHouse + Kafka: Data Warehouse ETL Pipeline
A data engineering ETL/ELT pipeline: Python for its rich data-tooling ecosystem, Kafka as the ingestion backbone decoupling producers from processing, and ClickHouse as the analytical warehouse built for fast aggregate queries over large volumes.
by @ops
Python + Postgres: Carbon Footprint / ESG Tracking Backend
Emissions data collection and ESG reporting metrics, a worker computing rollups on schedule — a genuinely growing-relevance category, not yet touched anywhere else in the catalog.
by @ops
Python + Postgres: Research Data Pipeline with Provenance Tracking
A data pipeline that records exactly where every dataset and transformation came from, a worker processing runs and logging lineage — distinct from generic ETL: built for research/pharma contexts where reproducibility and provenance are the actual requirement, not just moving data.
by @ops
Rust + Kafka + ClickHouse: IoT Telemetry Ingestion
A high-throughput device telemetry pipeline: a Rust ingestion API built for low-latency, high-volume writes, Kafka absorbing bursty device traffic, and ClickHouse as the analytical store for time-series queries at scale.
by @ops
Scheduled Reports & Data Export
Batch report generation on a schedule — CSV/PDF export, delivered async by a worker instead of generated inline and blocking a request. Distinct from real-time analytics: this is the "email me the weekly numbers" pattern, done properly.
by @ops
Session Recording & Replay Backend
Captures UI interaction events for session replay, storing recordings in MinIO with a worker processing them for playback — distinct from generic logging/metrics: this is specifically "watch what the user did," not application telemetry.
by @ops