How does this skill identify Redis performance bottlenecks?

It analyzes slow logs, latency history, and command execution times to pinpoint specific operations that cause delays, offering actionable fixes like replacing KEYS with SCAN.

Does it support benchmarking for high-traffic scenarios?

Absolutely. It includes configurations for redis-benchmark, supporting pipelining and specific command testing to simulate production loads.

What metrics does this skill monitor?

It tracks critical health indicators including memory fragmentation ratio, instantaneous ops/sec, hit ratios, and slow log length to ensure environment stability.

Can I use this skill to manage Redis memory usage?

Yes, it provides tools for memory analysis, big key detection, and configuration of eviction policies like allkeys-lru to prevent out-of-memory errors.

Redis Performance Optimizer

Name: Redis Performance Optimizer
Author: pluginagentmarketplace

bypluginagentmarketplace

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Database Management

Optimizes Redis environments through advanced memory analysis, slow log troubleshooting, and high-concurrency benchmarking.

About

The Redis Performance skill provides a comprehensive toolkit for developers and DevOps engineers to maximize the efficiency of their Redis deployments. It offers automated analysis of memory fragmentation, latency bottlenecks, and command execution speeds, enabling users to transition from basic caching to production-grade data management. By leveraging deep-dive commands and performance-tuning patterns, this skill helps identify 'big keys,' optimize eviction policies, and benchmark throughput to ensure high availability and low-latency responses in high-traffic applications.

Key Features

High-performance benchmarking with pipelining and custom command testing
Observability metrics for fragmentation, hit ratios, and operations per second
Real-time slow log monitoring and expensive command identification
1 GitHub stars
Automated memory usage analysis and eviction policy recommendations
Latency monitoring and bottleneck detection via LATENCY DOCTOR

Use Cases

Load testing Redis infrastructure before deploying high-traffic features
Optimizing memory footprints for large-scale caching layers to reduce costs
Troubleshooting production latency spikes and identifying slow-running queries

About

Key Features

High-performance benchmarking with pipelining and custom command testing
Observability metrics for fragmentation, hit ratios, and operations per second
Real-time slow log monitoring and expensive command identification
1 GitHub stars
Automated memory usage analysis and eviction policy recommendations
Latency monitoring and bottleneck detection via LATENCY DOCTOR

Use Cases

Load testing Redis infrastructure before deploying high-traffic features
Optimizing memory footprints for large-scale caching layers to reduce costs
Troubleshooting production latency spikes and identifying slow-running queries