Open-Source Observability · riemann

riemann

Riemann is an open-source event stream processing system written in Clojure that aggregates and processes events from distributed systems. It provides a domain-specific language for defining complex event workflows, making it suitable for real-time monitoring and metrics collection across infrastructure.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/riemann/riemann

4.3k

GitHub stars

502

Forks

Clojure

Primary language

EPL-1.0

License (Requires review (not clearly OSI))

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	riemann/riemann
Owner	riemann
Primary language	Clojure
License	EPL-1.0 — Requires review (not clearly OSI)
Stars	4.3k
Forks	502
Open issues	29
Latest release	0.3.12 (2025-05-26)
Last updated	2026-04-05
Source	https://github.com/riemann/riemann

What riemann is

Riemann ingests events via multiple protocols, applies stream transformations and aggregations using a Clojure-based DSL, and routes results to outputs (alerting, dashboards, databases). It handles event correlation, windowing, and stateful processing natively within a functional programming model.

Quickstart

Get the riemann source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/riemann/riemann.git2cd riemann3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Real-time infrastructure and application monitoring

Aggregates metrics and logs from multiple servers and services, detects anomalies, and triggers alerts based on complex event rules without external dependencies.

Stream-based metric aggregation and enrichment

Processes high-volume event streams, applies windowing and statistical transformations, and forwards refined data to time-series databases or alerting systems.

Custom event processing pipelines for DevOps

Enables teams to define domain-specific event workflows in Clojure, correlate multi-source events, and implement sophisticated conditional routing and state management.

Implementation considerations

Clojure runtime dependency (JVM); operationalize Java environment, GC tuning, and memory management for sustained production workloads.
Event schema design and DSL familiarity required; plan for Clojure training or hire experienced developers to define stream logic safely.
State management and windowing configuration must be carefully sized; unbounded aggregations can exhaust memory on long-running streams.
Input protocol and output sink integrations (TCP, UDP, HTTP, databases) must be vetted and configured for your topology.
Monitoring Riemann itself (recursive monitoring) is possible but must be explicitly configured; avoid circular dependencies or feedback loops.

When to avoid it — and what to weigh

Team lacks Clojure expertise — Configuration and extension require writing Clojure code. Teams unfamiliar with functional programming or Clojure will face a steep learning curve and slower iteration.
Need visual rule builder or no-code configuration — Riemann requires programmatic DSL; there is no web UI for rule definition. Operators without development skills cannot configure monitoring independently.
Require multi-tenant SaaS platform — Riemann is self-hosted infrastructure software. It does not provide managed hosting, isolation, or SaaS deployment models out of the box.
Enterprise support and SLA guarantees are mandatory — Unknown whether commercial support agreements or SLAs are available. The project is community-driven; enterprise support terms are not documented here.

License & commercial use

Licensed under Eclipse Public License 1.0 (EPL-1.0), a reciprocal open-source license. EPL-1.0 is OSI-approved and allows modification and distribution; derivative works must remain open-source under EPL-1.0 or compatible licenses.

EPL-1.0 permits commercial use of Riemann as-is or with modifications, provided modifications remain under EPL-1.0 or compatible open license. Proprietary extensions or internal-only forks are allowed, but any distributed derivative must be open-sourced. Verify your legal and compliance team's interpretation of reciprocal clauses for your specific use case.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

EPL-1.0 licensed code is publicly auditable. Riemann ingests event streams over network protocols; validate input source authentication, encryption in transit (TLS for HTTP), and access controls on the monitoring interface. No mention of built-in encryption, authentication mechanisms, or security audit history in provided data; review threat model and penetration testing maturity independently. Running untrusted Clojure in the DSL carries code-execution risk; sandbox DSL evaluation if accepting user-defined rules.

Alternatives to consider

Logstash (ELK Stack)

Log-centric event pipeline with larger ecosystem; visual rule builders available via Kibana. Heavier resource footprint and less focus on real-time metrics aggregation.

Prometheus + Alertmanager

Dominant open-source metrics-driven monitoring platform with pull-based scraping, PromQL DSL, and wide integrations. Simpler operational model for infrastructure metrics; less flexible for custom stream processing.

Kafka Streams / Apache Flink

General-purpose stream processing frameworks with higher throughput and more mature distributed processing. Steeper learning curve and more heavyweight for small-to-medium monitoring use cases.

Software development agency

Build on riemann with DEV.co software developers

If your team has Clojure expertise and needs a flexible, self-hosted stream processor for complex event workflows, Riemann is worth a proof-of-concept. Otherwise, compare Prometheus, Logstash, or managed platforms first.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

prometheus parseable fluent-bit

Related on DEV.co

Explore the category and the services that help you build with it.

Open-Source Observability DevOps Cloud Deployment Talk to DEV.co

riemann FAQ

Can I run Riemann in Kubernetes?

Yes, as a Clojure application on JVM. You must define Kubernetes Deployment, Service, and ConfigMap manifests; Riemann does not ship with native Helm charts or operators. Requires manual HA and persistence configuration.

Does Riemann replace Prometheus or Grafana?

No. Riemann is a stream processor, not a metrics database or visualization tool. It can feed data *to* Prometheus (via remote write), InfluxDB, or Graphite, and alerts *to* Grafana or PagerDuty.

What is the learning curve for Riemann's DSL?

Moderate-to-high if you lack Clojure experience. The DSL is Clojure; documentation covers basic streams and operators, but advanced patterns require functional programming knowledge.

Is Riemann suitable for small teams or startups?

Possibly, if you have Clojure expertise or can hire it. Otherwise, managed SaaS platforms (Datadog, New Relic) or simpler open-source tools (Prometheus) may be lower-friction.

Work with a software development agency

DEV.co helps companies turn open-source tools like riemann into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source observability stack.

Evaluate Riemann for your monitoring pipeline

Talk to DEV.co Schedule a Consultation