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.
Emergency RabbitMQ Support
Last reviewed by Scott Sternloff
If RabbitMQ is down, split-brained or out of disk, call +1 305-204-2607. Under a support contract a senior AceMQ engineer is on your incident within 15 minutes, 24/7; without one, a new emergency engagement starts the same day. The same engineers then find the root cause and hand you the change that stops it recurring, so the incident is not repeated.
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Named by the RabbitMQ Core Team
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.
See AceMQ listed on rabbitmq.comIs This You?
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
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.
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.
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.
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.
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.
A written diagnostic runbook specific to your topology, so the next incident is handled the same way regardless of who is on call.
Scope
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.
Unacked message growth, prefetch misconfiguration, slow or stalled consumers, and acknowledgement patterns that quietly hold messages in memory without ever completing.
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.
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.
Links that restart on cluster topology change, unidirectional message flow, upstream connection churn, and federation behavior across unreliable WAN links.
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
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.
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
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
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
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
Emergency RabbitMQ support means a senior engineer on your incident within 15 minutes under a support contract, 24/7, working from the broker's own state rather than from guesses. The first hour decides whether the rest of the incident is spent fixing the cluster or recovering from a restart that destroyed the evidence. These are the situations we are called for most, and the first move in each.
| First check | Do not | What AceMQ does | |
|---|---|---|---|
| Split brain (network partition) | rabbitmqctl cluster_status on every node, comparing running nodes and the partitions list | Restart nodes at random before logs and status are saved | Decides which side holds the state worth keeping, brings the other side back in, and sets the partition-handling strategy that prevents a repeat |
| Full disk or disk alarm | rabbitmq-diagnostics alarms, then what is using the volume: queue data, logs or dumps | Delete files from the data directory by hand | Frees or extends space safely, finds the queue or consumer fault that filled it, and clears the alarm so publishers resume |
| Memory alarm | rabbitmq-diagnostics memory_breakdown | Restart the node to clear it | Finds the queue and consumer pattern driving memory, then corrects prefetch and flow control |
| Quorum queue without a majority | rabbitmq-queues quorum_status for the queue, and which members are up | Delete and redeclare the queue | Restores the missing members and checks what was lost |
A split brain happens when nodes lose contact with each other and each side carries on. With the default partition handling the cluster stays partitioned until a person acts, and writes may continue on both sides. Recovery means choosing the partition whose state is trustworthy, stopping the nodes on the other side and starting them again so they rejoin. That choice is the hard part, because it decides which messages survive. Prevention on RabbitMQ 4.2 and earlier is a partition-handling strategy such as pause-minority on an odd number of nodes; on 4.3 and later that setting no longer exists, and the Raft-based metadata store and quorum queues need a majority to accept writes.
When free disk space falls below the configured limit, RabbitMQ blocks publishers to protect itself, so applications see connections stall while the broker looks healthy. Lowering the limit clears the alarm and leaves the node free to fill the disk completely. The useful questions are what filled it, whether it is a backlog because consumers stopped, and how much headroom the volume has at peak. We answer those during the incident and leave you alerts that fire well before the limit.
You do not need a contract to call. Without one, a new emergency engagement starts the same day. A support contract means the next emergency is answered in 15 minutes, and managed RabbitMQ services are the step up for teams that would rather not hold the pager at all.
For the monitoring and alert thresholds that catch these early, see RabbitMQ troubleshooting: 12 production issues and how to fix them
Customer Success
See how enterprises trust AceMQ for their most critical RabbitMQ workloads.
Global Automotive Manufacturer
Replacing fragile SQL-trigger-based ingestion with a reliable event-driven architecture for plant-floor data movement and low-latency operations.
Fortune 500 Financial Services Company
Improving RabbitMQ reliability, queue behavior, and operational guidance for a payment system processing over 200 production changes weekly.
Global Aviation Technology Provider
Troubleshooting cluster failover, partition handling, and quorum queue issues in a high-stakes aviation operational environment.
State-Run Virtual Education Platform
Standardizing RabbitMQ deployment and training staff while migrating infrastructure from VMware to Nutanix.
International Payment Exchange Service
Reducing manual error-queue operations by improving retry handling, dead-lettering, and downstream flow management across RabbitMQ, BizTalk, and D365.
Fortune 500 Software Company
Migration to supported RabbitMQ versions with managed services, standardization, compliance posture, and Tanzu commercial licensing.
Global Telecom Leader
Resolving weekly RabbitMQ crashes, optimizing for 300,000+ connected devices, and architecting horizontal scaling strategy.
Fortune 500 Industrial Conglomerate
Enterprise-grade RabbitMQ support with code-level remediation and patch management for regulated production environments.
FAQ
Save the evidence before you restart anything: run rabbitmqctl cluster_status on every node, copy the logs, and note which side your applications are connected to. Then decide which partition holds the state you want to keep, because that decides which messages survive. If you cannot make that call confidently, phone us on +1 305-204-2607 and we will work it with your engineers. Under a support contract we are on the incident within 15 minutes.
Run rabbitmq-diagnostics alarms to confirm a disk alarm is active. RabbitMQ blocks publishers while it is set, which is why producers hang with no error from the broker. Find out what is using the volume before you act. A growing backlog means consumers have stopped, which needs fixing or the disk fills again. Do not delete files from the data directory by hand. Extend the volume or free space safely, and let the alarm clear.
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.
Let's talk
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.
Send us a message and we'll follow up within 1 hour — or book a free 30-min consultation directly.
305-204-2607info@acemq.comPrefer to talk now? Call us directly or use the consultation tab to find a time that works.