Redis Support

24/7 Redis Support with a 15-Minute Emergency SLA

AceMQ supports Redis in production — latency spikes with no traffic correlation, fork stalls during RDB snapshots, eviction storms under memory pressure, and Sentinel or Cluster failovers that leave clients pointed at the wrong node. Self-managed, ElastiCache, Azure Cache, or Redis Enterprise. Every ticket reaches a named senior engineer.

Senior Redis engineers on call right now — 24/7/365
15 min emergency SLA24 /7 global coverage130 + enterprise customers26 + countries served

Trusted for mission-critical Redis by teams in finance, healthcare, defense, and telecom

Escalation Path

Your first hour of a Redis outage

Most vendors publish an SLA number. This is what actually happens, minute by minute, when you page a senior AceMQ engineer.

T+0

You page us

Phone, email, or Slack — any channel reaches the on-call senior engineer directly. No web form, no tier-1 queue.

T+15

Named engineer live

A senior engineer who already knows your environment joins a live bridge. Zero cold-start, no re-explaining your topology.

T+30

Root cause isolated

Direct broker access, log and metric review, and a working hypothesis with a rollback plan before we touch anything.

Post

Written RCA

Documented root cause, the fix applied, and the prevention steps — delivered after every P1, not just when asked.

Response Times

SLA tiers, contractually guaranteed

Every tier reaches a senior Redis engineer. There is no tier-1 triage layer to get through.

P1 — Emergency
15 min

Production down, messages not flowing, cluster or broker failure

P2 — Critical
1 hour

Severe degradation, rising error rates, approaching capacity limits

P3 — High
4 hours

Performance issues, configuration problems, non-critical failures

P4 — Standard
Next day

Questions, guidance, best practices, non-urgent improvements

Incident Triage

Redis problems we fix every week

These are real symptoms from real Redis production environments — and the first thing our engineers check when one comes in.

Latency spikes every few hours, correlating with nothing in app traffic
What we check firstSynchronous fork stalls from RDB snapshots or AOF rewrite, whether appendfsync is set to always and fighting disk fsync latency, and transparent huge pages — THP being enabled is the classic hidden cause and shows up as multi-hundred-millisecond pauses.
Typical resolutionUnder 2 hours
Redis using far more memory than the sum of key sizes suggests
What we check firstused_memory against used_memory_rss for fragmentation, then the encoding of your large collections. A hash that crosses hash-max-listpack-entries converts to a full hashtable and can multiply its footprint several times over with no application change.
Typical resolution1–3 hours
Commands intermittently timing out under normal load
What we check firstSLOWLOG for O(N) commands on the single-threaded command loop. One KEYS, one unbounded SMEMBERS on a large set, or a Lua script iterating a big collection blocks every other client for its full duration.
Typical resolutionUnder 1 hour
Keys disappearing before their TTL, cache hit rate collapsing
What we check firstmaxmemory-policy against actual working set. Under allkeys-lru Redis evicts to stay under maxmemory using approximate sampling, so hot keys can be evicted while cold ones survive if maxmemory-samples is left at the default.
Typical resolutionUnder 2 hours
Replica falls out of sync and triggers a full resync repeatedly
What we check firstrepl-backlog-size against replication lag during peak write volume, plus client-output-buffer-limit for the replica class. A replica disconnected longer than the backlog holds cannot do a partial resync and forces a full RDB transfer, which causes the next stall.
Typical resolution1–3 hours
Sentinel promoted a new primary but the application kept writing to the old one
What we check firstWhether the client library is Sentinel-aware or holds a cached direct connection, and whether min-replicas-to-write is set. Without it the demoted primary keeps accepting writes until it is reconfigured, and those writes are lost on reconnection.
Typical resolution2–4 hours
Cluster returning CLUSTERDOWN or MOVED loops after a resharding
What we check firstSlot coverage across the shard map and any slots left in migrating or importing state from an interrupted reshard. A single uncovered slot takes the whole cluster down by default under cluster-require-full-coverage.
Typical resolution2–4 hours
ElastiCache node degraded during a maintenance window or scaling event
What we check firstEngine CPU rather than host CPU, SwapUsage, and whether the reserved-memory-percent leaves enough headroom for a fork. ElastiCache exposes no direct shell access, so we work from the parameter group, the event log, and the metrics that actually reflect the command loop.
Typical resolution2–4 hours

Resolution times reflect typical Redis engagements under an active AceMQ support contract. Every P1 closes with a written root-cause analysis.

Not on the list? Tell us what's breaking
Support In Practice

Redis problems we've already solved

Representative engagements showing how these incidents get diagnosed and closed under an AceMQ support contract.

Assessment

Middleware Architecture Assessment for Financial Trading

European Online Trading Platform

Independent architecture and performance review of RabbitMQ, Kafka, and Redis for an online trading platform.

RabbitMQKafkaRedis
Read case study
Remediation

Redis Timeout Remediation for Fintech Microservices

Emsyne Technologies

AceMQ diagnosed Redis connection timeout issues causing service disruptions in a legacy fintech platform being modernized, identifying client-side resource exhaustion as the root cause and delivering a remediation plan for high-concurrency caching.

Redis
Read case study
Support

Multi-Technology Support Including Redis for Global Trading Firm

DRW (Global Trading Firm)

AceMQ expanded its enterprise support agreement with global quantitative trading firm DRW to include Redis caching alongside RabbitMQ, providing L3 escalation support across the full messaging and caching technology stack.

RedisRabbitMQ
Read case study
Assessment

Redis Cluster Health and Architecture Assessment

Enterprise Technology Organizations

AceMQ's Redis Health and Architecture Assessment identifies cluster vulnerabilities, performance bottlenecks, and optimization opportunities before they become production incidents — delivering a prioritized remediation roadmap.

Redis
Read case study
Remediation

Redis Latency Spike Remediation from Fork Stalls

Real-Time Bidding Platform

Eliminating periodic multi-hundred-millisecond latency spikes traced to RDB snapshot fork stalls amplified by transparent huge pages.

RedisLinuxKubernetes
Read case study
Support

Redis Memory and Eviction Policy Support

Healthcare Analytics Provider

Ongoing support for instances where the eviction policy did not match how the keyspace was used, causing session data to be evicted under memory pressure.

RedisKubernetesPrometheus
Read case study
Assessment

Redis Persistence and Durability Assessment

Public Sector Agency

Assessment of persistence configuration, replication topology, and failover behavior against the durability the workloads actually require.

RedisRedis SentinelLinux
Read case study
Support

Kong Rate Limiting Consistency Support

B2B SaaS Provider

Fixing rate limits that allowed several times the configured quota because the plugin was using the local counter policy across a multi-node gateway.

KongRedisKubernetes
Read case study
What's Included

Everything in your Redis support contract

No add-on pricing for incidents. No per-ticket charges. One contract covers the whole surface.

Emergency Incident Response

Redis unresponsive, a failover that stranded clients, or a cluster with uncovered slots. A senior engineer joins a live bridge within 15 minutes with access to diagnose — not a ticket acknowledgement.

Root Cause Analysis

Every P1 closes with a written RCA: what failed, why, the fix applied, and the specific configuration, data model, or client change that prevents recurrence.

Latency & Memory Tuning

maxmemory policy selection, fragmentation and encoding thresholds, THP and kernel settings, persistence strategy, and pipeline or connection pool sizing tuned against your actual command mix.

Data Model Review

Key design, collection sizing, TTL strategy, and where a Sorted Set, Stream, or Hash is the wrong structure for the access pattern. Most Redis performance problems are data model problems wearing a config costume.

Security & CVE Advisory

ACL design, TLS configuration, protected-mode and bind auditing, Lua sandbox exposure review, and proactive alerts for CVEs affecting your exact Redis or Valkey version with tested upgrade paths.

HA, Upgrades & Migration

Sentinel and Cluster topology design, resharding without downtime, major version upgrades, and migration between self-managed, ElastiCache, Azure Cache, and Redis Enterprise with verified key parity.

Anywhere You Run It

We support Redis wherever it's deployed

Cloud, Kubernetes, bare metal, hybrid, and air-gapped — including environments where you can't give us outbound network access.

AWS (EC2, ECS, EKS)Amazon ElastiCache for RedisAmazon MemoryDBAzure Cache for RedisGoogle Cloud MemorystoreRedis Enterprise & Redis CloudValkey deploymentsKubernetes & OpenShift operatorsRedis Sentinel topologiesRedis Cluster (sharded)Bare metal & on-premiseAir-gapped / no outbound access
Why AceMQ

What you get that you don't get elsewhere

Named Engineers, Zero Cold Start

The same senior engineers stay on your account. They know your key patterns, your persistence choice, and your failover topology — so a P1 call starts with diagnosis instead of you describing your setup while latency climbs.

No Tier-1 Triage Layer

You reach a senior Redis engineer directly by phone, email, or Slack. Nobody collects information to pass along, and no escalation approval sits between you and someone who can read a SLOWLOG and a LATENCY DOCTOR report.

Data Model, Not Just Config

Vendors tune parameters. A large share of Redis incidents trace to a single unbounded collection, a missing TTL, or an O(N) command on the hot path — and no amount of maxmemory tuning fixes those. We review the access pattern, not just redis.conf.

Genuine Follow-the-Sun Coverage

Engineers across 26+ countries and every time zone. Your 3am incident is someone's mid-afternoon — no overnight skeleton crew, no waiting for a region to wake up.

Proactive, Not Just Reactive

Quarterly health checks covering memory headroom, fragmentation trend, big-key growth, and eviction rate — so you resize before an eviction storm rather than after one takes your cache hit rate to the floor.

Managed Redis, Fully Covered

ElastiCache, MemoryDB, Azure Cache, and Memorystore remove node management but leave you every problem that causes real incidents. We support managed Redis as a first-class environment, working from parameter groups and metrics when shell access does not exist.

FAQ

Redis support questions

A Cache Outage Shouldn't Take Your Application With It

Whether you need emergency response tonight or a support contract that catches the next eviction storm before it starts, AceMQ staffs every engagement with a named senior Redis engineer. Support quotes returned within 24 hours.

Get in Touch

Talk to a Support Expert

Send us a message and we'll follow up within one business day — or book a free 30-min consultation directly.

305-204-2607
info@acemq.com
66 W. Flagler St. 9th Floor
Miami, FL 33130

Prefer to talk now? Call us directly or use the consultation tab to find a time that works.

We respond within 1 business day.

Pick a time that works — no pressure, no pitch. Just 30 minutes with an expert.

We respond within 1 business day.