Managed Kafka
A fully managed Kafka service, on your own infrastructure or hosted on ours. AceMQ operates every Kafka cluster the way your platform team would: we own monitoring, patching, upgrades, partition and capacity planning, and the pager. The engine stays open-source Apache Kafka: upstream as the Apache project releases it, or the Strimzi or Confluent Platform deployment you already run, not a proprietary rewrite. Run it in your own cloud account or data centre, or let us host a dedicated cluster for you. Either way the runbooks and topology documentation are yours, so you can take the platform back.
Support quotes answered within 1 hour, by a senior engineer.
Planning a build, upgrade or migration instead? See AceMQ Kafka consulting and services.
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What's Included
No add-on pricing for incidents. No per-ticket charges. One contract covers the whole surface.
We instrument what predicts incidents on each Kafka broker and Kafka cluster: consumer lag per group and partition, under-replicated and offline partitions, ISR churn, request and produce latency, controller and quorum health, disk and log-directory headroom. Then we take the pager, with alerts reaching an engineer who already knows your topology.
Kafka, JVM and client-library patching on a defined cadence, with CVE assessment against the versions you actually run. Where a cluster is on a Kafka line the Apache project no longer maintains, it stays covered rather than being forced onto an upgrade you have not scheduled.
A planned upgrade path instead of version drift: rolling broker upgrades with metadata-version staging, and the ZooKeeper-to-KRaft migration that Kafka 4.x requires, executed in your change windows with a rollback plan.
Partition counts, replication, retention and broker sizing reviewed against real throughput as the workload grows, with partition reassignment and rebalancing done before a hot broker becomes an incident. The reasoning is written down, not kept in someone's head.
The ecosystem around the brokers is where many streaming data outages start. Kafka Connect workers and connectors, Schema Registry compatibility, and MirrorMaker 2 replication for DR are operated under the same service, not left to the application teams.
On Kubernetes we operate Strimzi or your existing operator, persistent volumes, rack awareness and rolling restarts that keep the ISR healthy. On VMs, bare metal or air-gapped estates we run the same playbook with your tooling and change process.
Why AceMQ
Run managed Kafka in your own VPC or data centre (Stage 3) when data-residency and compliance rules keep the brokers in your account. Or have AceMQ host a dedicated cluster on our infrastructure (Stage 4) when you want endpoints and no cloud account, Kubernetes or on-call rota to run. Either way the operator is a Kafka specialist, not a generic hosting contract.
A senior Kafka engineer is assigned to your platform and stays on it. Incidents start with someone who knows your partition layout and consumer topology, not with a ticket queue.
Most Kafka incidents are client-side: commit strategy, poll loops, producer acks and retries. We work on your Kafka clients and applications alongside the brokers, because that is where lag and duplicates usually come from.
Because nothing in the engine is specific to AceMQ, your clients, topics and tooling stay portable. Runbooks, topology documentation and monitoring configuration are maintained as yours throughout. If you bring operations back in-house, or move a cluster between your infrastructure and ours, there is a current handover pack ready.
Cloud, Kubernetes, bare metal, hybrid, and air-gapped — including environments where you can't give us outbound network access.
The 4 stages
Each stage moves one more responsibility from your team to AceMQ: first diagnosis, then early warning, then running the cluster, then owning the platform it runs on. Stages 1 and 2 are AceMQ's Kafka support. Stages 3 and 4 are managed Kafka services, and they are what the rest of this page describes.
| Stage | Who holds the pager | What AceMQ does |
|---|---|---|
| Stage 1: Reactive support | You | A senior Kafka engineer responds to your tickets under the contracted SLA, with escalation, health checks and CVE alerts. Access to your environment is on request, while a ticket is worked. |
| Stage 2: Proactive support | You, with AceMQ raising problems early | Stage 1, plus monitoring and alerting through AceMQ's observability setup, so lag, under-replicated partitions and capacity trends reach an engineer and then you before users notice. |
| Stage 3: Managed on your infrastructure | AceMQ | AceMQ operates Kafka in your cloud account, Kubernetes cluster or data centre: monitoring, patching, upgrades, capacity, change execution and on-call. You keep the account, the data and the cloud bill. |
| Stage 4: Managed on AceMQ infrastructure | AceMQ | AceMQ hosts and operates a dedicated Kafka cluster on its own infrastructure. You get bootstrap endpoints, not a cluster, a cloud account or an on-call rota to run. |
Stage 3 and Stage 4 get the same operations. What differs is where the cluster runs and who owns the infrastructure underneath it. Tell us the workload and we will recommend a stage. Stages 1 and 2 are on the Kafka support page, linked under related reading.
The same four stages cover RabbitMQ and Redis too; the escalation-first option is set out in managed open-source operations.
Escalation Path
Every tier reaches a senior Kafka engineer. There is no tier-1 triage layer to get through.
P1 escalation path
A replay of one P1, from the first page to the written root-cause analysis
15-minute P1 response, 24/7.
A response time, not a resolution time.
P1 opened, on-call engineer paged
Phone, email or Slack reaches the on-call senior engineer directly, whether the incident is in RabbitMQ, Kafka, Redis, PostgreSQL or Kubernetes. No web form, no tier-1 queue.
Senior engineer on your bridge
A senior engineer who already knows your environment joins a live bridge, so nobody has to re-explain your topology.
Specialists across the stack join
When an incident crosses components, the engineers who know each one join. For RabbitMQ, the path runs to the core team.
Written root-cause analysis
Root cause, the fix applied and the prevention steps, delivered after every P1.
Support In Practice
Kafka support, remediation and assessment work from AceMQ. Each card links to the full write-up: the cluster, what AceMQ diagnosed or changed, and the result.
European Hosting Provider
A five-node Kafka cluster serving 60,000 customers was timing out producers under load. The cause was topology, not capacity.
Apache Kafka
Docker
LinuxBanking Transaction Platform
Throughput fell from 320,000 to roughly 45,000 transactions per hour after Kafka was introduced. The platform needed 80,000 to prove it could scale.
Apache KafkaKRaftJMeter
European Online Trading Platform
Independent architecture and performance review of RabbitMQ, Kafka, and Redis for an online trading platform.
RabbitMQKafka
RedisGlobal Technology Enterprise
AceMQ developed a multi-technology compliance strategy covering CVE patching for Kafka alongside RabbitMQ and IBM MQ deployments, creating a unified vulnerability management approach across the entire enterprise messaging stack.
KafkaRabbitMQ
IBM MQPagoNXT (Financial Technology)
AceMQ provided ongoing support for PagoNXT's high-throughput payments infrastructure running Kafka and RabbitMQ at 2,500 transactions per second, including load testing validation and architecture optimization.
KafkaRabbitMQEnterprise Organizations
AceMQ's Kafka assessment service evaluates streaming architecture health, identifies operational risks, and provides a structured migration or modernization roadmap for enterprises running or evaluating Kafka.
KafkaSupport options
AceMQ offers Apache Kafka cover in four options, each handing more of the day-to-day work to AceMQ: 24/7 support and incident management for clusters your team runs, proactive monitoring that catches lag, ISR and CVE problems first, managed Kafka on your own infrastructure, and fully managed Kafka on a dedicated cluster hosted by AceMQ. Self-managed Kafka, Confluent Platform and Amazon MSK are covered.
You run it, we back you up
Best for: Teams that run Kafka themselves and need senior cover at 3am.
You run it, we watch it with you
Best for: Clusters where a rebalance storm or a shrinking ISR must be caught before users notice.
We run it in your cloud or data centre
Best for: Regulated estates that must keep Kafka brokers inside their own boundary.
We host it and run it, as a service
Best for: Teams that want Kafka endpoints without a cloud account, Kubernetes or a rota to run.
| Who does what | Stage 1 24/7 support | Stage 2 Proactive monitoring | Stage 3 Managed, your infrastructure | Stage 4 Fully managed by AceMQ |
|---|---|---|---|---|
| Who runs Kafka day to day? | Your team | Your team, with AceMQ reviews | AceMQ | AceMQ |
| Where does it run? | Your infrastructure | Your infrastructure | Your cloud account or data centre | AceMQ infrastructure |
| 24/7 incident response | 15-minute P1 response | 15-minute P1 response | 15-minute P1 response | 15-minute P1 response |
| Health checks and CVE alerts | On request | Scheduled | Included | Included |
| Patching and upgrades | Your team, AceMQ advises | Planned with AceMQ | Done by AceMQ | Done by AceMQ |
| Monitoring and on-call | Your team | Your team | AceMQ | AceMQ |
| Data, keys and accounts | Yours | Yours | Yours | Your data, hosted by AceMQ |
Every Stage can start as an ad hoc engagement or an annual partnership, and you can move up or down a Stage as your team changes.
One partner for Kafka
Support is one part of what AceMQ does for Kafka. The same engineers deliver consulting, health checks, migrations and end-of-life cover, and support the systems that usually run next to it.
Managed Kafka services mean someone else operates your Apache Kafka clusters: monitoring, on-call, patching, upgrades, capacity and incident response. A hosted service such as Amazon MSK, Confluent Cloud or Aiven runs Kafka in the provider's account and leaves topic design, clients and Connect with you. AceMQ offers two models. We operate Kafka on your own infrastructure, so the data and the account stay yours, or we host a dedicated cluster on ours. In both, a Kafka specialist owns the whole platform, clients and Connect included.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) offers fully managed Apache Kafka in MSK Provisioned or MSK Serverless clusters, with Amazon MSK Connect for connectors and MSK Replicator for replication to a cluster in another Region. Confluent Cloud offers a fully managed Kafka service across the major clouds. Both host Kafka in the provider's environment and manage the broker infrastructure; your topic design, clients, connectors and most incident causes remain your problem. AceMQ operates Kafka where it already runs, in your account, or hosts a dedicated cluster for you on AceMQ infrastructure, and in both cases takes responsibility for the whole platform including clients and Connect. Teams choose this when data residency, version control, a named engineer or avoiding lock-in matter. The trade-offs are compared in Managed Kafka options compared.
Support is an SLA over a cluster your team runs: you hold the pager and call us when something breaks. Managed services means we run it: monitoring, patching, upgrades, capacity and on-call are ours. Teams with a capable platform team usually want support (Stages 1 and 2); teams that want Kafka to stop being their problem want managed services (Stages 3 and 4).
Stage 1 is reactive support: you run Kafka and raise tickets to a specialist under an SLA. Stage 2 is proactive support: you still run and own the cluster, and AceMQ adds monitoring and alerting through its observability setup so problems surface early. Stage 3 is managed Kafka on your infrastructure: AceMQ operates the cluster in your account and holds the pager. Stage 4 is managed Kafka on AceMQ infrastructure: AceMQ hosts and operates a dedicated cluster for you. The pager changes hands at Stage 3.
Yes. At Stage 4 AceMQ hosts and operates a dedicated Kafka cluster on its own infrastructure, so you get bootstrap endpoints without a cloud account, Kubernetes cluster or on-call rota to run. Monitoring, patching, upgrades, capacity and incident response are the same as when we run Kafka in your account, with the same emergency response. If compliance or data-residency rules require the cluster to stay in your account, we operate it there instead at Stage 3.
Four things. Where the cluster runs, and whether you can choose between your account and the provider's. Whether the provider owns clients, Kafka Connect, Schema Registry and MirrorMaker 2 as well as the brokers, since that is where many incidents start. Who holds the pager, and how fast a senior engineer responds. And what exit looks like: runbooks and topology documentation that are yours, not a rebuild. AceMQ is a Kafka managed service provider that offers both hosting models and keeps those four answers in writing.
Yes. Most estates we take over are inherited. We start with an assessment of version and patch position, topology, partition and replication layout, consumer groups, Connect and monitoring gaps, remediate the active risks, and only then take the pager.
Yes. KRaft (Kafka Raft) keeps cluster metadata in a quorum of Kafka controllers instead of a separate Apache ZooKeeper ensemble, so there is one system to secure, monitor and upgrade. Apache Kafka 4.x removed ZooKeeper, so every ZooKeeper-based cluster needs a KRaft migration before it can move to 4.x. We plan and execute it, including the controller quorum design, the migration phases and the version gates, inside your change windows.
They stay covered while you plan the upgrade. The Apache project fixes bugs only on its most recent releases. For security patches on older lines, AceMQ's OSSeva platform backports CVE fixes to Apache Kafka 2.8.x through 3.7.x.
Emergencies such as brokers down, offline partitions or a consumer group that cannot stabilise get a 15-minute first response from a senior engineer, 24/7. Because we already run the platform, most of those incidents are caught by our monitoring before your team notices.
Self-managed Kafka gives you full control of versions, configuration, data residency and cost, but your team carries the pager and the upgrades. A hosted managed service such as Amazon MSK, MSK Serverless or Confluent Cloud removes broker operations but moves the cluster into a provider account and still leaves topic design, clients and Kafka Connect with you. An operated managed service keeps the control of self-managed Kafka and hands the operations to a specialist, and a dedicated cluster hosted by AceMQ hands over the infrastructure too. The deciding questions are where the data must live, who should hold the pager, and how predictable the streaming load is.
Yes. We operate Apache Kafka in your own Google Cloud project, Azure subscription or AWS account, on virtual machines or Kubernetes, and on premises. The hosted alternatives are Google Cloud Managed Service for Apache Kafka and Confluent Cloud on Google Cloud, and Amazon MSK on AWS. We help teams compare those with running Kafka in their own account or on a dedicated cluster hosted by AceMQ, and we support clusters on any of them.
The same real-time streaming workloads Kafka is used for anywhere: event-driven microservices, change data capture into a data platform, log and metrics pipelines, payments and order streams, IoT telemetry, and feeding stream processing in Kafka Streams or Flink. Managed operations matter most where the stream is business-critical and the team building on it should not also be running it.
Yes. AceMQ works on Kafka in two ways: ad hoc engagements for a defined piece of work, such as a health check, an upgrade or an incident, or an annual partner engagement that covers 24/7 support, proactive reviews and named engineers. Many teams start ad hoc and move to an annual partnership once the first engagement is done.
Every AceMQ proposal is tailored to your requirements: your Kafka environment, the SLA you need, the hours of cover and the scope of work. We do not send generic quotes or publish a price list, because two estates of the same size rarely need the same thing. Request a quote and AceMQ replies within 1 hour.
Let's talk
Reactive cover, proactive reviews, or AceMQ running Kafka for you on your infrastructure or ours. A senior engineer scopes it with you, and quote requests are answered within 1 hour.
Production incident right now?Email a Kafka Architect
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