sohutv/cachecloud

搜狐视频(sohu tv)Redis私有云平台 :支持Redis多种架构(Standalone、Sentinel、Cluster)高效管理、有效降低大规模redis运维成本,提升资源管控能力和利用率。平台提供快速搭建/迁移,运维管理,弹性伸缩,统计监控,客户端整合接入等功能。(CacheCloud is a...

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Summary Information

Updated 56 minutes ago
Added to GitGenius on September 7th, 2026
Created on January 26th, 2016
Open Issues & Pull Requests: 36 (+0)
GitHub issues: Enabled
Number of forks: 2,041
Total Stargazers: 9,032 (+0)
Total Subscribers: 558 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 174.0 days
Mean response time: 185.0 days
90th percentile: 174.0 days
Tracked items: 23

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 25% of issues opened in the past year have been closed. Three people close 100% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 3
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,178 days
Stale 30+ days: 3
Stale 90+ days: 1

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

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Detailed Description

CacheCloud is a Redis cloud management platform that supports multiple Redis architectures including Standalone, Sentinel, and Cluster deployments for centralized administration and monitoring.

The platform addresses the operational complexity of managing large-scale Redis infrastructure by providing unified control across diverse deployment topologies. It reduces operational overhead through automated instance provisioning, centralized resource allocation, and integrated monitoring. The approach consolidates Redis management tasks—from initial setup and migration through ongoing maintenance—into a single web-based interface, allowing teams to treat Redis infrastructure as a managed service rather than individual instances requiring separate administration.

Organizations running multiple Redis deployments at scale should consider CacheCloud if they need to reduce operational costs and improve resource utilization across their Redis fleet. The platform suits teams managing hundreds of instances across physical machines or Kubernetes environments who want visibility into performance metrics, application-level statistics, and infrastructure health. It provides client integration through SDKs and language-specific bindings, enabling applications to connect through the platform's managed access layer rather than directly to instances.

The project maintains active development with regular updates addressing operational features and monitoring capabilities. The codebase shows ongoing refinement of deployment automation and diagnostic tooling. The project sustains community engagement through multiple communication channels and welcomes external contributions and feedback.