Agent Skills

redis-observability

devopsredis1.9K installs

Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.

Install

npx skills add https://github.com/redis/agent-skills --skill redis-observability
SKILL.md

Redis Observability

What to watch, what to run, and what to alert on. Covers the metrics every Redis deployment should monitor and the built-in commands for ad-hoc diagnosis.

When to apply

  • Setting up monitoring or alerts for a Redis instance.
  • Diagnosing a Redis performance regression (high latency, memory pressure, connection storms).
  • Profiling a slow FT.SEARCH or pipeline.
  • Wiring Redis metrics into Prometheus, Datadog, CloudWatch, or similar.

1. Monitor these metrics

These come from INFO and should be exported to your monitoring system.

Metric What it tells you Alert when
used_memory Current memory usage > 80% of maxmemory
connected_clients Open connections Sudden spikes or drops
blocked_clients Clients waiting on blocking ops > 0 sustained
instantaneous_ops_per_sec Current throughput Significant drops
keyspace_hits / keyspace_misses Cache hit ratio Hit ratio < 80%
rejected_connections Hit maxclients cap > 0
rdb_last_save_time Last persistence snapshot Too old vs. RPO
info = redis.info()
hit_ratio = info["keyspace_hits"] / max(1, info["keyspace_hits"] + info["keyspace_misses"])
print(f"Memory:    {info['used_memory_human']}")
print(f"Clients:   {info['connected_clients']}")
print(f"Ops/sec:   {info['instantaneous_ops_per_sec']}")
print(f"Hit ratio: {hit_ratio:.1%}")

See references/metrics.md.

2. Built-in commands for debugging

Reach for these when something looks off.

Topic Command
Slow commands SLOWLOG GET 10 / SLOWLOG LEN / SLOWLOG RESET
Server snapshot INFO all (or INFO memory / INFO stats / INFO clients / INFO replication)
Memory diagnostics MEMORY DOCTOR / MEMORY STATS / MEMORY USAGE <key>
Connections CLIENT LIST / CLIENT INFO
RQE / Search FT.INFO <idx> / FT.PROFILE <idx> SEARCH QUERY "..."

The two most useful for incident triage:

  • SLOWLOG GET to find queries that exceeded the slowlog-log-slower-than threshold (10ms by default). The output shows the exact command and duration in microseconds.
  • MEMORY DOCTOR for memory pressure — it returns a one-paragraph summary of what's unusual about memory usage right now.
for entry in redis.slowlog_get(10):
    print(f"{entry['duration']}μs  {entry['command']}")

See references/commands.md.

3. Redis Insight

For interactive use (running queries, browsing keys, profiling indexes), Redis Insight is the official GUI. It surfaces the same SLOWLOG / INFO / FT.PROFILE data visually and includes Redis Copilot for natural-language queries. Useful during development and incident response; not a replacement for exporting metrics to your monitoring system.

References

Related skills

azure-diagnosticsmicrosoft608KDebug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, troubleshoot functions, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, aazure-preparemicrosoft608KPrepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azazure-aimicrosoft608KUse for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.azure-deploymicrosoft607KExecute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: \"run azd up\", \"run azd deploy\", \"execute deployment\",

Search skills and MCP servers

Fuzzy search across 23,137 skills and servers