Databases
    Updated May 2026
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    KeyDB Monitoring

    Monitor KeyDB multi-threaded performance, active-replica state, FLASH storage tier, and the full Redis-compatible `INFO` metric set (memory, hit rate, evictions, replication) in real time.

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    Why monitor KeyDB?

    KeyDB is the multi-threaded Redis fork — used when one Redis core hits its CPU ceiling, or when active-active multi-master replication beats failover orchestration. Monitoring tracks the same things as Redis plus the KeyDB-specific signals: per-thread CPU distribution and FLASH tier hit rates that decide whether the multi-thread design pays off.

    Auto-discovery via Xitogent — zero manual configuration
    Full Redis-compatible `INFO` metric set (memory, hit rate, evictions, replication, clients, ops/sec)
    KeyDB-specific per-thread CPU tracking (`server-threads`)
    Active-replica / multi-master replication state monitoring
    FLASH storage tier metrics when enabled (`storage-provider flash`)
    Replication lag tracking across active-active topologies
    `SLOWLOG` and `LATENCY HISTORY` integration for command-level diagnostics
    Customizable alert thresholds for every metric
    Wire-compatible with and the entire Redis tooling ecosystem
    1-minute metric collection intervals out of the box
    What is KeyDB monitoring?

    KeyDB monitoring, explained

    KeyDB monitoring catches memory pressure, replication divergence (especially in active-active multi-master setups), thread saturation, and FLASH storage tier issues before they impact cache performance or cause data drift across replicas. Because KeyDB is a drop-in Redis replacement with extra capabilities (multi-threading, active-active, FLASH SSD tier), monitoring it well means tracking both the standard Redis metric set AND the KeyDB-specific signals. Xitoring auto-discovers your KeyDB, reads INFO plus per-thread state, and routes alerts to Slack, PagerDuty, Telegram, or your existing on-call.

    Metrics

    What we monitor

    used_memory / mem_fragmentation_ratio

    Resident memory used vs RSS overhead. Fragmentation ratio above 1.5 means significant overhead — run `MEMORY PURGE` or enable `activedefrag`.

    instantaneous_ops_per_sec

    Live RESP commands processed per second across all worker threads. The headline throughput number where KeyDB's multi-threading shines vs single-threaded Redis.

    Per-Thread CPU (server-threads)

    CPU utilization per KeyDB worker thread. Uneven distribution flags a sticky-connection or single-shard hot-key pattern that's defeating the multi-threaded design.

    Keyspace Hit Ratio

    Computed as `keyspace_hits / (keyspace_hits + keyspace_misses)`. Target 80%+ for cache workloads; below 50% means the cache isn't helping.

    evicted_keys / sec

    Keys removed by the `maxmemory` policy. Any non-zero rate means `maxmemory` is too small for the working set — grow it, or move data to FLASH tier if cost-sensitive.

    connected_clients / blocked_clients

    Currently connected clients and clients blocked on `BLPOP`/`BRPOP`/`WAIT`/etc. Connected_clients approaching `maxclients` triggers `rejected_connections`.

    rejected_connections

    Connection attempts dropped because `maxclients` was hit. Any growth signals app-side connection-pool leaks or traffic spikes.

    Active-Replica State

    When `active-replica yes` is configured, surfaces per-replica replication offset and write-acceptance state — critical for multi-master deployments where every node accepts writes.

    Replication Offset Lag

    `master_repl_offset` minus `slave_repl_offset` per replica. Sustained lag means a replica can't keep up — usually network or CPU on the replica side.

    FLASH Tier Hit/Miss

    When `storage-provider flash` is enabled (KeyDB-specific SSD-backed tier), surfaces hot/warm/cold object split and FLASH miss rate. Lets you size the FLASH tier correctly for working sets larger than RAM.

    Persistence (RDB / AOF)

    `rdb_last_save_time`, `rdb_changes_since_last_save`, `aof_current_size`, `aof_rewrite_in_progress`. Detects failed RDB saves and AOF rewrite stalls before they impact restart recoverability.

    SLOWLOG / Latency

    Slow command count from `SLOWLOG` plus Redis-internal latency events from `LATENCY HISTORY`. Catches the one `KEYS *` or huge `SMEMBERS` call that's stalling worker threads.

    Triggers & Alerts

    Configurable alert triggers

    Set up custom triggers in your dashboard to get notified the moment KeyDB metrics cross your defined thresholds.

    KeyDB monitoring trigger configuration dashboard

    Memory Usage

    critical

    Fires when memory exceeds threshold.

    Replication Lag

    critical

    Alerts on replication falling behind.

    Key Evictions

    warning

    Triggers on high eviction rate.

    Connected Clients

    warning

    Fires when client count approaches limits.

    01

    Importance of KeyDB Monitoring

    KeyDB's multi-threaded architecture handles massive throughput. Without monitoring, memory pressure and replication issues can cause data loss.

    • Track memory to prevent OOM crashes
    • Monitor replication for data consistency
    • Detect key evictions impacting cache
    • Optimize multi-threaded performance
    KeyDB monitoring
    Performance analytics
    02

    Why Choose Xitoring

    Zero-config KeyDB monitoring.

    • One-command install
    • Global nodes
    • Unified dashboard
    • Multi-channel alerts
    • Historical retention
    Overview
    Alerts
    Use cases

    Common KeyDB monitoring scenarios

    Where KeyDB typically runs today — and what could go wrong if no one's watching.

    High-traffic apps that outgrew Redis

    KeyDB is usually chosen when one Redis server can no longer keep up with traffic. We make sure the extra power is actually being used — and flag the patterns that quietly cancel it out, so the upgrade pays off the way it was supposed to.

    Apps serving users in multiple regions

    When a cache runs in several regions and accepts writes everywhere, the regions can quietly drift apart. We watch for that drift so users in different parts of the world never see inconsistent data.

    Large caches that mix memory and SSD

    When the cache is too big to fit in memory, KeyDB stores the most-used items in RAM and the rest on disk. We watch the balance so the cache stays fast — and so the SSDs underneath don't quietly wear out from heavy use.

    Before you start

    Prerequisites for KeyDB

    Make sure you've got these in place — most installs are a 60-second job once they are.

    • KeyDB 5.x or 6.x running on its configured port (default 6379)
    • AUTH password if requirepass is set (ACL also supported)
    • Network reachability from Xitogent to the KeyDB instance (or each node in active-replica deployments)
    Setup Guide

    Get started in minutes

    1

    Install Xitogent on your KeyDB host

    Install the lightweight Xitogent monitoring agent on the host running KeyDB.

    curl -s https://xitoring.com/install.sh | sudo bash -s -- --key=YOUR_API_KEY
    2

    Confirm INFO command access

    KeyDB is wire-compatible with Redis and uses the `INFO` command for runtime stats. Ensure KeyDB is reachable on its bind address (default 6379) and supply credentials if `requirepass` is set.

    sudo xitogent integrate
    3

    Enable the KeyDB integration

    Use the Xitoring dashboard or CLI to enable the KeyDB integration. Xitogent auto-detects your KeyDB instance and replication topology.

    4

    Configure alert thresholds (optional)

    Set custom thresholds for Memory Usage, Replication Lag, or Key Evictions to catch capacity issues before they cause cache misses or replication divergence.

    5

    Verify it's working

    Run this command on the server to confirm Xitogent picked up the integration. Fresh metrics will start streaming to your dashboard within ~30 seconds.

    sudo xitogent status
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    Frequently asked questions

    What is KeyDB and how does it differ from Redis?
    KeyDB is a BSD-licensed multi-threaded fork of Redis (maintained at github.com/Snapchat/KeyDB after the Snap acquisition). It's wire-compatible — the same RESP protocol, the same commands, the same `INFO` output — but adds: (1) multi-threading via `server-threads N` for higher single-instance throughput, (2) active-active multi-master replication where every node accepts writes, (3) FLASH storage tier for SSD-backed datasets larger than RAM. Existing Redis tooling (`redis-cli`, ) works on KeyDB unchanged.
    How do I monitor KeyDB latency?
    Use `redis-cli --latency -h ` for end-to-end RTT samples, or `LATENCY LATEST` / `LATENCY HISTORY` for Redis-internal latency spikes (with `latency-monitor-threshold` configured in `keydb.conf`). KeyDB also ships `keydb-diagnostic-tool` for deeper analysis. Xitogent surfaces both per-event latency from `LATENCY HISTORY` and trend data over time.
    How do I monitor KeyDB active-replica replication?
    With `active-replica yes` and `multi-master yes`, every node accepts writes and replicates to peers. Monitor per-peer replication offset (`INFO replication`), `master_link_status` on each peer connection, `master_repl_offset` divergence between masters, and any `sync_partial_err` rate. Conflicts in multi-master are resolved last-write-wins by timestamp — alert on clock drift between nodes.
    How many server-threads should I set in KeyDB?
    Match `server-threads` to your physical CPU cores (not hyperthreads) on a dedicated KeyDB host — typically 4 to 8. More than 8 hits diminishing returns from coordination overhead. Monitor per-thread CPU utilization after a tuning change: if one thread is saturated while others are idle, you've got a sticky-connection or hot-key pattern that needs application-side work.
    Is KeyDB really 5x faster than Redis?
    KeyDB's own benchmarks claim 2–5x throughput vs single-threaded Redis on the same hardware (independent InfraCloud benchmarks confirm 2–3x in typical workloads). The win shows up when you're CPU-bound on one Redis core. For memory-bound or network-bound workloads, the win is much smaller. Xitogent's per-thread metrics let you measure the actual multiplier on your workload.
    How do I monitor KeyDB FLASH storage?
    When `storage-provider flash ` is enabled, KeyDB stores hot keys in RAM and warm/cold values on SSD. Monitor FLASH hit/miss ratio (similar to `keyspace_hits`/`misses` but at the storage tier), SSD I/O latency, and total FLASH-resident bytes. Watch SSD write amplification — cache workloads can wear consumer-grade SSDs quickly; use enterprise SSDs for production FLASH tiers.
    Does KeyDB work with, Prometheus, and Grafana?
    Yes. KeyDB speaks RESP, so reads it unchanged, Prometheus scrapes the exporter, and existing Grafana dashboards (e.g. dashboard ID 763) work as-is. Xitogent reads `INFO` directly (no exporter needed) but is compatible with environments running for Grafana visualization.
    KeyDB vs Valkey vs Redis — which to monitor in 2026?
    All three speak RESP and share the same monitoring vocabulary. Redis (AGPLv3 since 2025) is the original, now with RedisJSON/RediSearch/RedisTimeSeries/RedisBloom in the core distribution. Valkey (Linux Foundation BSD fork) backs AWS ElastiCache Serverless and GCP Memorystore. KeyDB (BSD) is the multi-threaded + active-active + FLASH choice for specific workloads. Xitoring monitors all three with the same integration patterns.
    What KeyDB versions are supported?
    KeyDB 5.x and 6.x are fully supported. The integration auto-detects whether multi-threading, active-replica, or FLASH storage features are enabled and surfaces the appropriate KeyDB-specific metrics on top of the standard Redis-compatible `INFO` set. Wire-compatibility with and the Redis ecosystem is preserved.

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