Most RabbitMQ incidents get closed when the alert clears, not when the cause is understood — which is why they come back. AceMQ engineers diagnose the actual failure, prove it, and hand you the configuration change that stops it recurring.
The only partner with direct RabbitMQ core team access
11 + senior RabbitMQ SMEs15 min emergency SLA130 + enterprise customers26 + countries served
Trusted for Mission-Critical RabbitMQ by Teams in Finance, Healthcare, Defense, Telecom, and More
Named by the RabbitMQ Core Team
The Featured Authorized Partner for RabbitMQ — named by the engineers who build it
AceMQ is the Featured Authorized Partner for RabbitMQ, named by the RabbitMQ Core Engineering Team — the people who write and maintain the broker. That recognition covers RabbitMQ support, licensing and professional services, and it makes AceMQ the only RabbitMQ partner with a direct line to the core team. When an escalation needs an answer that is not in the documentation, it does not stop at a support tier.
You do not have to take our word for it — RabbitMQ lists AceMQ on its own site.
RabbitMQ partner with a direct line to the Core Engineering Team
Support · Licensing · Services
the full scope the partner status covers
Below 72 cores
the only provider globally licensing commercial RabbitMQ under Broadcom's minimum
Is This You?
You probably need this if…
Your cluster hits a memory or disk alarm and you restart nodes to clear it, without knowing why it filled
Queues are backing up with tens of thousands of unacked messages and consumers look healthy
Quorum queues are running fewer members than you configured, and you don't know when they dropped
Federation or shovel links restart every time you add or remove a node
rabbitmqctl and rabbitmq-diagnostics stopped working after a security agent rollout
A partition healed itself but you can't tell whether you lost messages
Throughput fell off a cliff and nothing in your application changed
You've opened tickets with a vendor who keeps asking for logs and never reaches a conclusion
Outcomes
Where you are now, and where you end up
Concrete state changes, not deliverable counts. This is what actually differs about your RabbitMQ estate when the engagement closes.
Before
Recurring memory alarms cleared by restarting nodes on a runbook nobody wrote down.
After
The specific queue and consumer pattern driving memory growth is identified, with a corrected prefetch and flow-control configuration that holds under peak load.
Before
A backlog of unacknowledged messages that grows during business hours and never fully drains.
After
Consumer acknowledgement behavior and prefetch sizing corrected, backlog drained, and an alert that fires on unacked growth before it becomes visible to users.
Before
Quorum queues silently running with fewer members than configured after past node replacements.
After
Full member sets restored, the replacement procedure that lost them corrected, and a check that surfaces under-replicated queues automatically.
Before
Nobody on the team can say with confidence whether the last partition event lost messages.
After
A documented partition-handling strategy, verified publisher confirms, and a reconciliation method that answers the question definitively.
Before
Incidents diagnosed by whoever is available, with knowledge leaving when they do.
After
A written diagnostic runbook specific to your topology, so the next incident is handled the same way regardless of who is on call.
Scope
What's covered
Memory & Disk Alarms
Memory high-watermark tuning, paging behavior, disk free-space limits, and the queue or consumer pattern actually driving growth. We find what fills the broker, not just how to clear the alarm.
Backlogs & Consumer Lag
Unacked message growth, prefetch misconfiguration, slow or stalled consumers, and acknowledgement patterns that quietly hold messages in memory without ever completing.
Clustering & Partitions
Network partition handling strategy, split-brain recovery, node discovery failures, and Erlang distribution issues — including the case where a security agent silently blocks the Erlang binaries the CLI depends on.
Quorum & Classic Queues
Under-replicated quorum queues, member loss after node replacement, quorum queue creation failures at high message counts, and classic mirrored queue behavior on versions where it still applies.
Federation & Shovel
Links that restart on cluster topology change, unidirectional message flow, upstream connection churn, and federation behavior across unreliable WAN links.
Performance & Throughput
Publisher confirm latency, channel churn, connection storms, message size effects, and the interaction between prefetch, concurrency, and consumer processing time that governs real throughput.
The Engagement
How it actually runs
Every phase has a defined duration and a concrete artifact handed over at the end of it. You always know what stage you're in and what you've received.
Phase 1First 24 hours
Rapid Triage
A senior engineer gets read access to your cluster, metrics, and logs. We establish what changed, what the actual failure signature is, and whether you are currently at risk of another incident — before proposing anything.
You receive
Current-state risk assessment with anything urgent flagged immediately
Confirmed failure signature, separated from downstream symptoms
Interim mitigation if you are still exposed
Phase 22–5 days
Deep Diagnosis
We reproduce or trace the failure through broker internals — queue and channel state, Erlang process and memory breakdown, flow control, disk and network behavior, and the client-side acknowledgement pattern. Most RabbitMQ problems are not broker bugs; they are configuration and client behavior interacting badly under load.
You receive
Root cause established with supporting evidence, not a hypothesis
Contributing factors ranked by impact
Reproduction steps where the failure can be reproduced safely
Phase 31–2 weeks
Remediation
We implement the fix with you — configuration changes, topology corrections, client library changes, or an upgrade where the cause is a known defect. Changes are staged and validated rather than applied directly to production.
You receive
Applied and validated fix, with rollback plan
Before/after metrics demonstrating the change worked
Client-side recommendations where the fix belongs in application code
Phase 41 week
Prevention & Handover
We close by making sure this class of failure surfaces early next time. That means the monitoring and alerting gaps that let it reach production get closed, and your team gets a written runbook for the specific topology you run.
You receive
Written root-cause analysis document
Monitoring and alert rules covering the failure mode
Diagnostic runbook specific to your cluster topology
Live handover session with your on-call team
Customer Success
Real RabbitMQ Results
See how enterprises trust AceMQ for their most critical RabbitMQ workloads.
Support is an ongoing contract with an SLA for incidents as they happen. Troubleshooting is a scoped engagement aimed at one persistent or recurring problem you have not been able to resolve — typically something that has been open for weeks and survived several attempted fixes. Many customers start with a troubleshooting engagement to clear a specific issue, then move onto a support contract to keep it from recurring.
For an active production incident, we can have a senior engineer engaged within 15 minutes under a support contract, or same-day for a new emergency engagement. For a persistent non-urgent problem, engagements typically start within a few business days. Tell us the severity when you contact us and we will be direct about what we can commit to.
At minimum, read access to the management API or metrics, broker logs, and configuration. Interactive access to a live session with your engineers is significantly faster than an asynchronous log exchange. We work regularly in restricted and air-gapped environments where direct access is impossible, and can guide your team through the diagnostic steps instead — it takes longer, but it works.
That happens often, and we will tell you. RabbitMQ symptoms frequently originate in storage latency, network policy, JVM or client library behavior, Kubernetes scheduling, or a security agent interfering with the Erlang runtime. We diagnose across the full stack because that is where the cause usually lives, and we would rather hand you an accurate answer about your storage layer than a plausible one about your broker.
Both, and the fix is included. We implement remediation with your team rather than delivering a report and leaving. Where the correct fix belongs in your application code, we specify exactly what needs to change and why, and review it with your developers — we just will not merge to your application repositories on your behalf.
Yes. Many regulated environments cannot upgrade on the community's timeline, and that is a normal enterprise constraint rather than a disqualifier. We troubleshoot RabbitMQ from 3.8.x to 4.x, apply workarounds where upstream fixes are not available for your version, and will tell you honestly when a specific problem genuinely cannot be resolved without upgrading.
A written root-cause analysis, the applied and validated fix with before-and-after metrics, monitoring and alert rules that would have caught the issue earlier, and a diagnostic runbook written for your specific topology. The runbook matters most: it means the next incident of this class gets handled consistently, whoever is on call.
Stop Restarting Nodes and Hoping
Bring us the RabbitMQ problem that keeps coming back. A senior engineer will tell you what is actually causing it — and what specifically to change so it stops.
Get in Touch
Talk to a RabbitMQ Expert
Send us a message and we'll follow up within one business day — or book a free 30-min consultation directly.