Awesome-omni-skill valkey

Valkey (Redis-compatible) in-memory data store for caching, session storage, pub/sub, queues, and distributed locks. Use when configuring Valkey or Redis-compatible caching, choosing eviction policies, implementing rate limiting, setting up pub/sub or streams, writing Docker Compose services, migrating from Redis, or tuning performance. Use for valkey, redis, cache, session, pub/sub, streams, distributed-lock, rate-limit, sorted-set.

install

source · Clone the upstream repo

git clone https://github.com/diegosouzapw/awesome-omni-skill

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/devops/valkey" ~/.claude/skills/diegosouzapw-awesome-omni-skill-valkey && rm -rf "$T"

manifest: skills/devops/valkey/SKILL.md

source content

Valkey

Open-source, Redis-compatible in-memory data store maintained by the Linux Foundation. Forked from Redis OSS 7.2.4 (BSD 3-Clause license). Drop-in replacement for Redis OSS 2.x through 7.2.x — same protocol, commands, and data formats.

When to use: Caching, session storage, rate limiting, pub/sub messaging, task queues, leaderboards, distributed locks, real-time counters, or any workload requiring sub-millisecond key-value operations.

When NOT to use: Primary relational data store, large object storage (>512 MB values), workloads requiring strong ACID transactions across multiple keys without Lua scripting.

Quick Reference

Task	Approach	Key Point
Cache-aside	`GET` -> miss -> DB read -> `SET key val EX ttl`	Always set a TTL, even a long one
Session storage	`HSET session:{id} field val` + `EXPIRE`	Sliding TTL on each request
Rate limiting	`INCR` + `EXPIRE` (fixed window) or sorted set (sliding)	Sorted set for precision
Distributed lock	`SET lock:{res} token NX PX 30000`	Always set expiry to prevent deadlocks
Queue (simple)	`LPUSH` + `BRPOP`	Blocking pop with timeout
Queue (reliable)	Streams + `XGROUP` + `XACK`	Consumer groups for at-least-once
Pub/Sub	`SUBSCRIBE` / `PUBLISH`	Fire-and-forget, no persistence
Streams	`XADD` + `XREADGROUP`	Persistent, replayable, consumer groups
Leaderboard	Sorted set: `ZADD` / `ZREVRANGE`	O(log N) rank operations
Unique count	`PFADD` + `PFCOUNT` (HyperLogLog)	~12 KB memory, 0.81% error
Eviction policy	`maxmemory-policy allkeys-lru`	Best default for most workloads
Docker setup	`valkey/valkey:8.1-alpine`	Health check: `valkey-cli ping`
Persistence	AOF ( `appendonly yes` ) + RDB snapshots	AOF for durability, RDB for backups
Client library	`ioredis` or `iovalkey` (official fork)	All Redis clients work unchanged
Migrate from Redis	Swap binary, keep data files	RDB/AOF compatible through Redis 7.2

Common Mistakes

Mistake	Correct Pattern
Using `KEYS *` in production	Use `SCAN` with cursor for iteration
No TTL on cache keys	Always set TTL — unbounded growth causes OOM
`DEL` on large keys blocking server	Use `UNLINK` for async deletion
Pub/Sub for durable messaging	Use Streams with consumer groups for persistence
Same TTL on all keys (thundering herd)	Add jitter: `EX (base + random(0, spread))`
No `maxmemory` set in production	Set `maxmemory` + eviction policy explicitly
Using `MULTI/EXEC` for locking	Use `SET ... NX PX` for distributed locks
Storing large blobs (>1 MB values)	Store references; keep values small
No health check in Docker Compose	Add `valkey-cli ping` health check
Ignoring `requirepass` in production	Always set authentication + ACLs

Delegation

Discover caching patterns and data model review: Use
```
Explore
```
agent
Plan migration strategy from Redis to Valkey: Use
```
Plan
```
agent
Implement full caching layer with tests: Use
```
Task
```
agent

If the
docker
skill is available, delegate Compose networking and multi-stage build patterns to it. If the
performance-optimizer
skill is available, delegate application-level caching strategy to it. If the
database-security
skill is available, delegate ACL and TLS configuration review to it.

References

Data structures and commands -- Strings, hashes, lists, sets, sorted sets, streams, HyperLogLog, bitmaps, geospatial
Caching patterns -- Cache-aside, write-through, TTL strategies, eviction policies, client-side caching, invalidation
Common patterns -- Rate limiting, distributed locks, queues, session storage, pub/sub, streams, leaderboards
Docker and deployment -- Compose setup, persistence, replication, Sentinel, Cluster, security, migration from Redis