Apache Kafka consulting & services
Last reviewed by Tyler Eastridge
AceMQ's Kafka consultants are engineers who have run mission-critical, real-time data streaming platforms at scale across financial services, telecom, and manufacturing: architecture, fault tolerance, cluster health and migrations for self-managed, MSK and Confluent Kafka. We staff every engagement with a named senior engineer — no ticket queues, no junior triage.
Without rebuilding your cluster or replatforming to a vendor distribution
Get a Kafka health check 15-minute emergency SLA, 24/7 Prefer to e-mail? info@acemq.com
Consumer group lag
topic orders · 6 partitions · group billing-svc · illustrative
p3 is hot: one key carries most of the writesWrites spread across all six partitions
skewed partition keypartition key fixed
c2 owns the two busiest partitionsBusy partitions on different consumers
range assignorcooperative-sticky assignor
Commits keep pace on p0, p1, p4 and p5Every partition within one poll of the log end
no rebalance in the last hourno rebalance in the last hour
Illustrative data, not a customer cluster.
Customers
Partners
The problem
These are the situations that bring teams to us. Pick one to see what we do first.
What we do first
Read lag per partition, not per group, because a group average hides the one partition that never drains. Then trace it to the cause: producer batching, consumer poll and commit settings, or partition assignment.
Where it leadsKafka health checkWhat we do first
Line up every rebalance against consumer logs and settings (session timeout, max.poll.interval.ms, the assignor) to find the trigger, then move the group to cooperative rebalancing where the client supports it.
Where it leadsThe Kafka operations guideWhat we do first
Size partition counts from measured throughput per partition and the consumer parallelism you need. Then plan the change carefully: Kafka can add partitions but never remove them, and adding them moves keys.
Where it leadsKafka health checkWhat we do first
Look at topology before capacity: replication factor, controller placement and connection load. In one five-node cluster the cause was the controller leader, not the broker count.
Where it leadsRead the case studyWhat we do first
Own the cutover: plan the ZooKeeper to KRaft migration, rehearse it, and run it with your team, keeping a rollback point until the migration is finalised. Kafka 4.0 removed ZooKeeper mode, so the deferral has an end date.
Where it leadsThe Kafka migration guideWhat we do first
Test it under failure instead of trusting the configuration: stop brokers and consumers mid-transaction, then check the output topics for duplicates and gaps.
Where it leadsKafka health checkWhat we do first
Write runbooks for the failure modes in your topology and make changes with your engineers rather than around them, so the knowledge stays after we leave.
Where it leads24/7 Kafka supportWhat we do first
Compare the bill with the workload it carries (partitions, retention, throughput and egress), then choose between right-sizing, running Kafka on your own infrastructure, or an independent support contract.
Where it leadsManaged Kafka options comparedOur services
Every engagement is staffed by a senior Apache Kafka engineer — no juniors, no ticket queues.
We design Kafka deployments that handle millions of messages per second with the durability, ordering, and replay guarantees your use case demands.
From simple producer/consumer patterns to complex event-driven architectures — we build pipelines that are reliable, observable, and easy to operate.
Saturating brokers or seeing consumer lag accumulate? Our engineers have optimized Kafka clusters from 10K to 10M messages/second and know where the bottlenecks hide.
Moving from a legacy message broker or between Kafka distributions? We plan and execute migrations with zero message loss and minimal downtime.
Whether you're migrating to managed Kafka or running multi-region deployments, we plan and execute with full operational continuity.
Also from AceMQ:
How it works
We map topics, partitions, consumer groups, replication and retention against what the workload actually needs — then show you where the headroom and the hot spots are.
1–2 weeks
Prioritised findings with the reasoning attached, sized so you can take it to your own engineering leadership without translation.
Within a week
We make the changes with your engineers rather than around them, so the knowledge stays after we leave. Every change is reversible and staged.
Scoped per engagement
Runbooks for the failure modes specific to your topology, plus 24/7 support with a 15-minute emergency SLA if you want it.
Ongoing
A senior engineer, not an SDR. No sales sequence attached.
Customer success
See how enterprises trust AceMQ for their most critical Apache Kafka workloads.
European Hosting Provider
A five-node Kafka cluster serving 60,000 customers was timing out producers under load. The cause was topology, not capacity.
Banking 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.
Global Automotive Manufacturer
Replacing fragile SQL-trigger-based ingestion with a reliable event-driven architecture for plant-floor data movement and low-latency operations.
European Online Trading Platform
Independent architecture and performance review of RabbitMQ, Kafka, and Redis for an online trading platform.
American National Insurance
American National Insurance chose a standalone Debezium + RabbitMQ architecture for SQL Server change data capture after judging Kafka too complex to run for the job, keeping operations lean and routing flexible.
Global 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.
PagoNXT (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.
Enterprise 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.
24/7 Support
Direct access to senior engineers — 15-minute emergency response, no ticket routing, no junior triage.
15 MIN SLA24/7 Apache Kafka Support
Named senior engineers on your account — 15-minute emergency response, no ticket routing, no junior triage.
Response targets
24/7 · named senior engineer
Emergency
Production down, messages not flowing, queue manager failure
Critical
Severe degradation, high error rates, approaching capacity
High
Performance issues, configuration problems, non-critical failures
Standard
Questions, guidance, best practices, non-urgent improvements
Beyond SLAs — the model behind senior-only, zero-cold-start expert access.
Every ticket is handled by a senior SME assigned to your account — not a pool of anonymous agents. Zero cold-start. No re-explaining your environment.
Any ticket can be escalated to a live session with your named engineer via calendar booking. No gatekeeping, no approval required — direct access, always.
Quarterly health checks on your deployment plus shared intelligence from 50+ support customers — we surface risks before they reach production.
Proactive alerts on critical bugs and CVEs affecting your exact version, with version compliance monitoring so you're never caught off guard.
Dedicated support for vendor license negotiations and compliance audits, plus bi-annual security reviews focused on your specific deployment.
Why AceMQ
No junior triage, no ticket queues, no offshore routing — direct access to the named engineer who knows your environment.
Our engineers hold deep, hands-on Kafka expertise from open-source community deployments to Confluent enterprise platforms at financial services scale.
We stay engaged on incidents until the root cause is documented and the cluster is fully stable — not just until the alerting clears.
Structured broker configuration, topic design, consumer lag, and security posture reviews — with a prioritized remediation report after each one.
Named engineer on your account. When your Kafka cluster goes down, you call us directly — no ticket, no triage, no cold-start.
50+ technologies
Apache Kafka rarely fails in isolation. AceMQ covers the infrastructure around it, so one team owns the whole path instead of pointing at each other.
Message Brokers & Event Streaming
Databases & Caching
Search & Analytics
Lakehouse & Compute
Observability & Monitoring
Data Integration & Orchestration
Cloud & Containers
Guides, comparisons and research
The guides and comparisons our engineers write from production Kafka work.
Related services:
FAQs
Common questions about Apache Kafka consulting, support, and migrations.
Still have questions about Apache Kafka? Email an Expert
Our Kafka consulting covers cluster architecture design, broker sizing, streaming pipeline development, performance tuning, security hardening, and migration planning. Every engagement is staffed by a named senior engineer with production-proven Kafka expertise across open-source and enterprise platforms like Confluent.
Yes. We provide full-lifecycle Kafka professional services for open-source Apache Kafka — the same expert-level guidance we give enterprise platform users. This includes emergency troubleshooting, break/fix remediation, healthcheck reviews, and version upgrades.
A Kafka healthcheck is a structured review of your cluster covering broker configuration, topic design, replication factors, consumer group lag, security posture, and monitoring gaps. We deliver a written report with prioritized remediation steps. Most teams run healthchecks quarterly or after major changes.
We work across all major distributions: open-source Apache Kafka, Confluent Platform and Cloud, Amazon MSK, Azure Event Hubs (Kafka protocol), and Aiven for Kafka. We recommend the right platform for your requirements, not the one with the largest margin.
Yes. We design and develop stateful stream processing applications with Kafka Streams and ksqlDB, including state store optimization, interactive queries, exactly-once semantics, and Schema Registry integration.
Independent Kafka support generally runs about $24,000 to $72,000 per year. The low end covers a small cluster (three to six brokers) on a business-hours SLA; a contractual 24/7 response SLA on a larger estate sits at the high end. Confluent prices support by custom quote bundled with Confluent Platform, or by consumption on Confluent Cloud (metered in eCKUs plus throughput, storage and egress). The number most estates miss is people: even a partial engineer dedicated to Kafka runs $50,000 or more per year fully loaded, which is usually the argument for a contract rather than against one. AceMQ quotes against your broker count and SLA, not a seat count.
Independent support vendors, including AceMQ, cover open-source Apache Kafka, Amazon MSK, Strimzi on Kubernetes and Confluent Platform itself, without requiring a migration to a vendor distribution. Confluent supports its own distribution and proprietary components (Control Center, its connectors, ksqlDB); if your estate depends on those, staying with the vendor is the safer call. If you run community Kafka or a cloud-managed service and want a named engineer under a response SLA, an independent contract is usually cheaper and does not bundle features you do not use.
Yes. Managed Kafka services from AceMQ run your clusters on your own infrastructure, in your cloud account or data centre, with AceMQ owning monitoring, patching, upgrades, capacity and on-call under a 15-minute emergency SLA. Nothing moves to a provider account, which is the difference from Amazon MSK or Confluent Cloud.
We start with consumer lag metrics and under-replicated partition counts to isolate the problem layer, then move to immediate stabilization, root cause analysis, and documented post-incident review. We stay engaged until the cluster is fully recovered — not just until the metrics look green.
Let's talk
Whether you need emergency support, a healthcheck, a migration partner, or ongoing managed support — AceMQ staffs every engagement with a named senior Kafka engineer. Quote requests answered within 1 hour.
Production incident right now?Email an Apache Kafka Architect
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.
