littlehorse
by
littlehorse-enterprises

Description: LittleHorse Server: Workflow Engine for Microservice Orchestration & Business-as-Code, and the core of the Saddle Command Center

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Summary Information

Updated 2 hours ago
Added to GitGenius on March 19th, 2025
Created on July 19th, 2023
Open Issues & Pull Requests: 195 (+0)
Number of forks: 35
Total Stargazers: 385 (+0)
Total Subscribers: 7 (+0)

Issue Activity (beta)

Open issues: 167
New in 7 days: 0
Closed in 7 days: 3
Avg open age: 310 days
Stale 30+ days: 156
Stale 90+ days: 113

Recent activity

Opened in 7 days: 0
Closed in 7 days: 3
Comments in 7 days: 0
Events in 7 days: 3

Top labels

  • server (231)
  • dashboard (186)
  • clients (71)
  • needs-proposal (68)
  • documentation (12)
  • lhctl (12)
  • canary (3)
  • javascript (2)

Repository Insights (GitGenius)

Median issue/PR response: 0.0 hours
Mean response time: 54.8 days
90th percentile: 256.0 days
Tracked items: 626

Most active contributors

Detailed Description

LittleHorse is a high-throughput, low-latency orchestration engine written in Java that enables developers to codify business processes spanning agents, microservices, integrations, and workflows using a Business-as-Code approach. The platform is built on Apache Kafka and Kafka Streams, providing two-way rich integrations with the Kafka ecosystem so that workflows can be triggered by Kafka events and emit state changes back to Kafka in real time. This architecture allows LittleHorse to handle the operational complexity of distributed systems while keeping workflow definitions closely aligned with actual business logic.

The core value proposition of LittleHorse addresses several pain points in microservice orchestration. Rather than manually wiring microservices together with RPC calls or message queues, developers define workflows that LittleHorse executes durably. The platform abstracts away concerns like retries, timeouts, dead-letter queues, distributed tracing, asynchronous scheduling, and backpressure management, allowing teams to focus on business process logic rather than infrastructure plumbing. The Business-as-Code model enables product and engineering teams to maintain better alignment by expressing processes in code that mirrors actual business workflows.

LittleHorse provides multi-language SDK support across Java, Go, Python, JavaScript, and C#, with client packages available through standard package managers including Maven Central, PyPI, npm, and NuGet. The platform includes a dashboard accessible at localhost:8080 for inspecting workflow runs and their execution state. The project also provides lhctl, a command-line interface for interacting with the LittleHorse server and investigating workflow executions.

The repository shows significant development activity with 626 tracked issues and pull requests. The most active contributor, coltmcnealy-lh, has logged 941 events, followed by GhostArrays with 291 events and Snarr with 244 events. Issue tracking reveals that server-related issues dominate with 231 labeled items, followed by dashboard issues at 184 and client-related issues at 71. The median response latency for issues and pull requests is 0.0 hours with a mean of 1315.0 hours, indicating variable response times across the project lifecycle. The repository maintains connections with other significant open-source projects including VMware Photon, Facebook RocksDB, and Odoo through overlapping contributors.

The project is licensed under the GNU Affero General Public License Version 3 for server and dashboard code, while SDKs, lhctl, examples, and other packages use the Apache License 2.0. LittleHorse follows Semantic Versioning after version 1.0 and maintains a documented project lifecycle with guidelines for releases and deprecation strategy. The platform includes comprehensive quickstart examples and documentation at littlehorse.io/docs, with an active Slack community for user engagement. The architecture separates concerns into task definitions (units of work), workflow specifications, and a workflow engine that ensures correct execution while task workers handle integrations with external systems and databases.

littlehorse
by
littlehorse-enterpriseslittlehorse-enterprises/littlehorse

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