01
Emergency Incident Response
NameNode down, a re-replication storm saturating the network, or YARN queues frozen. A senior engineer joins a live bridge within 15 minutes.
Apache Hadoop Support
24/7 Apache Hadoop Support with a 15-Minute Emergency SLA
Last reviewed by Scott Sternloff
AceMQ keeps HDFS and YARN clusters running in production — NameNode heap exhaustion from small-file sprawl, re-replication storms after disk failures, and Kerberos tickets expiring mid-job. We also plan honest migrations off Hadoop when that's the right call. Every ticket reaches a named senior engineer.
Support quotes answered within 1 hour, by a senior engineer.
- min emergency SLA
- 15
- across Americas, EMEA, APAC
- 24/7
- enterprise customers
- 160+
- countries served
- 26+
Planning a build, upgrade or migration instead? See AceMQ Apache Hadoop consulting and services.
Customers
Partners
Incident Triage
Apache Hadoop problems we fix every week
These are real symptoms from real Apache Hadoop production environments — and the first thing our engineers check when one comes in.
| Symptom you're seeing | What we check first | Typical resolution |
|---|---|---|
| NameNode heap climbing steadily toward OOM | Small-file count via `hdfs dfsadmin -report` and fsimage size. Every file and block consumes roughly 150 bytes of NameNode heap, and small-file sprawl is the classic HDFS heap killer. | 1–3 hours |
| Cluster stuck in a re-replication storm after disk failures | DataNode disk health and under-replicated block count. A failed disk on a densely packed DataNode can trigger cluster-wide re-replication that saturates network bandwidth for hours. | 2–4 hours |
| YARN jobs stuck pending despite idle capacity elsewhere | Fair or capacity scheduler queue configuration. A queue with a low max-capacity cap starves jobs even when the cluster overall has plenty of free resources. | 1–2 hours |
| NameNode HA failover doesn't complete cleanly | ZKFC logs and fencing method configuration. A failed fencing script leaves the old active NameNode in an ambiguous state with both NameNodes contending for the role. | 2–4 hours |
| Cluster-wide slowdown right after a large restart | Block report timing across DataNodes for a block report storm — every DataNode reporting its full block inventory to the NameNode simultaneously overwhelms it after a coordinated restart. | 1–3 hours |
| Jobs fail mid-run with authentication errors on a secured cluster | Kerberos ticket TTL against actual job runtime. Long-running jobs outlive the default ticket lifetime when renewal isn't configured. | Under 2 hours |
| Running an end-of-life Cloudera or Hortonworks distribution | Current CVE exposure and available upgrade or migration paths. Vendor consolidation left many clusters stranded on releases that no longer receive patches. | Same day |
| Evaluating whether to modernize off Hadoop entirely | Current workload mix — batch ETL, ML, or ad hoc query — against lakehouse and cloud-native alternatives. The case for migration is usually falling further behind on patches, not raw performance. | Same day |
Resolution times reflect typical Apache Hadoop engagements under an active AceMQ support contract. Every P1 closes with a written root-cause analysis.
What's Included
Everything in your Apache Hadoop support contract
No add-on pricing for incidents. No per-ticket charges. One contract covers the whole surface.
- 02
Root Cause Analysis
Every P1 closes with a written RCA: what failed, why, the fix applied, and the configuration change that prevents recurrence.
- 03
HDFS & YARN Performance Tuning
Scheduler queue configuration, NameNode heap and small-file remediation, and block placement policy tuned against your actual cluster shape.
- 04
Security & Kerberos Hardening
Ticket lifetime and renewal configuration, keytab management, and secure cluster hardening for regulated environments that can't run unsecured.
- 05
CVE & EOL Patch Advisory
Proactive advisory for clusters running end-of-life Cloudera or Hortonworks distributions, including backported mitigations where official fixes no longer exist.
- 06
Migration Off Hadoop
Honest assessment of whether to modernize onto a lakehouse or cloud-native platform, and execution of that migration when it's the right call — not a sales pitch either way.
Why AceMQ
What you get that you don't get elsewhere
Named Engineers Who Still Know Hadoop Internals
Classic Hadoop expertise is scarce and getting scarcer. The same senior engineers stay on your account and actually know HDFS block placement and YARN scheduler internals, not just how to run kubectl against something newer.
No Tier-1 Triage Layer
You reach a senior Hadoop engineer directly by phone, email, or Slack. No help desk, no escalation approval process standing between you and a fix.
Honest Exit-Path Guidance
We support both keeping Hadoop running and planning a migration off it — and we'll tell you plainly which one actually makes sense for your workload instead of defaulting to whichever we happen to sell.
EOL Distribution Support
We support Hadoop clusters running distributions that no longer receive vendor patches, including bug workarounds and backported mitigations for regulated environments that can't upgrade on the community's timeline.
Genuine Follow-the-Sun Coverage
Engineers across 26+ countries and every time zone. Your 3am NameNode failover is someone's mid-afternoon — no overnight skeleton crew.
Full-Stack, Not Just HDFS
Hadoop problems are frequently OS, network, or disk problems wearing an HDFS error message. We diagnose across the whole stack, including the hardware layer where legacy clusters often show their age.
We support Apache Hadoop wherever it's deployed
Cloud, Kubernetes, bare metal, hybrid, and air-gapped — including environments where you can't give us outbound network access.
- On-premise & bare metal
- Cloudera CDP
- Legacy Hortonworks HDP
- Amazon EMR (Hadoop)
- Google Dataproc
- Azure HDInsight
- Kerberized secure clusters
- HDFS & YARN
- Hybrid cloud
- Air-gapped deployments
Escalation Path
Your first hour of an Apache Hadoop outage
Every tier reaches a senior Apache Hadoop engineer. There is no tier-1 triage layer to get through.
- 15 minfirst responseEmergencyProduction down, messages not flowing, queue manager failure
- 1 hourfirst responseCriticalSevere degradation, high error rates, approaching capacity
- 4 hoursfirst responseHighPerformance issues, configuration problems, non-critical failures
- Next Dayfirst responseStandardQuestions, guidance, best practices, non-urgent improvements
P1 escalation path
A replay of one P1, from the first page to the written root-cause analysis
T+Elapsed15:00
15-minute P1 response, 24/7.
A response time, not a resolution time.
- T+00:00Paged
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.
- T+15:00Live
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.
- T+30:00If needed
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.
- AfterEvery P1
Written root-cause analysis
Root cause, the fix applied and the prevention steps, delivered after every P1.
Pricing
What does AceMQ Apache Hadoop support cost?
AceMQ Apache Hadoop support contracts typically run $24,000–72,000 a year, depending on SLA level, scope (number of clusters or nodes, and environments) and deployment (self-managed, cloud-managed or Kubernetes).
| What moves the price | How it changes the contract |
|---|---|
| SLA level | Business-hours cover costs less than 24/7 cover with a 15-minute emergency response. |
| Scope | More clusters or nodes, and more environments, make a larger contract. |
| Deployment | Self-managed, cloud-managed and Kubernetes estates need different amounts of hands-on work. |
Covering several technologies under one contract, for example RabbitMQ, Kafka and Redis, earns an aggressive discount.
Support In Practice
Apache Hadoop problems we've already solved
Hadoop support and remediation work from AceMQ. Each card links to the full write-up: the cluster, what AceMQ diagnosed or changed, and the result.
Apache Spark Executor OOM and Partition Skew Remediation
Telecommunications Operator
Fixing nightly jobs where a handful of skewed keys concentrate data onto a few executors and drive repeated out-of-memory failures.
Apache Spark
Apache HadoopDelta LakeYARNApache Hadoop Cluster Exit Assessment
Regional Utility Operator
Establishing what is actually running on a Hadoop cluster, what it costs to keep, and what a defensible migration sequence and timeline look like.
Apache Hadoop
Apache HiveApache SparkYARNApache Hadoop NameNode Heap Remediation
Global Logistics Operator
Relieving NameNode heap pressure and long GC pauses caused by small-file sprawl across HDFS, before the cluster loses its metadata service.
Apache HadoopApache HiveApache SparkYARNApache Hadoop YARN Scheduler Support
Public Sector Agency
Named-engineer support for YARN queue starvation, container allocation failures, and NodeManager instability on production Hadoop clusters.
Apache HadoopYARNApache SparkApache Hive
Apache NiFi Content Repository Remediation
Regional Utility Operator
Recovering NiFi nodes where the content repository has filled because a backpressured downstream processor has no queue limits in front of it.
Apache NiFi
Apache KafkaApache HadoopApache Spark Shuffle and Spill Tuning
National Retail Bank
Reducing shuffle write volume and disk spill on nightly batch jobs so the processing window fits inside the reporting deadline.
Apache SparkApache HadoopYARNApache Hive
Support options
Four tiers of Apache Hadoop support.
AceMQ offers Apache Hadoop support in four tiers, 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 finds small-file, replication and Kerberos problems first, managed Hadoop on your own infrastructure, and fully managed Hadoop on AceMQ infrastructure. Apache Hadoop and the Cloudera and Hortonworks distributions are covered, as are the current release and the five end-of-life release lines before it.
- Tier 1
Apache Hadoop 24/7 Support & Incident Management
You run it, we back you up
- 15-minute P1 response, 24/7, from an engineer who knows HDFS and YARN internals
- Triage across NameNode, DataNodes, ZKFC, YARN and Kerberos
- Cover for clusters on Cloudera, Hortonworks and Apache releases
Best for: Platform teams that run Hadoop themselves and need senior escalation cover for a cluster few people still understand.
- Tier 2
Apache Hadoop 24/7 Support with Proactive Monitoring
You run it, we watch it with you
- NameNode heap, fsimage and small-file growth reviews
- Under-replicated block, DataNode disk and failover rehearsal checks
- YARN queue and Kerberos renewal reviews against real job runtimes
Best for: Teams that want the heap warning or the failed failover found in a review, not in an outage.
- Tier 3
Managed Apache Hadoop on Your Infrastructure
We run it in your cloud or data centre
- AceMQ holds the pager for HDFS, YARN and the services on top
- Patching, workarounds and backported mitigations for end-of-life distributions
- Capacity planning for hardware that is hard to source
Best for: Regulated estates that must keep Hadoop in their own data centre or air-gapped network.
- Tier 4
Fully Managed Apache Hadoop on AceMQ Infrastructure
We host it and run it, as a service
- Hosted and operated by AceMQ, sized to your workload
- HDFS, YARN and Kerberos operations included
- 24/7 on-call with the same 15-minute emergency response
Best for: Teams that want to keep Hadoop workloads running without hardware refreshes or a Hadoop operations team.
| Who does what | Tier 1 24/7 support | Tier 2 Proactive monitoring | Tier 3 Managed, your infrastructure | Tier 4 Fully managed by AceMQ |
|---|---|---|---|---|
| Who runs Apache Hadoop 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 Tier can start as an ad hoc engagement or an annual partnership, and you can move up or down a Tier as your team changes.
One partner for Apache Hadoop
Everything else AceMQ does for Apache Hadoop.
Support is one part of what AceMQ does for Apache Hadoop. The same engineers deliver consulting, health checks, migrations and end-of-life cover, and support the systems that usually run next to it.
- ConsultingApache Hadoop consulting and services
- MigrationApache Hadoop migration
- LifecycleEnd-of-life software support
- Enterprise supportOpen source support across your whole stack
- GuideApache Hadoop guide
Support for the rest of your stack
Messaging & Streaming
- RabbitMQ supportMessaging & Streaming
- Apache Kafka supportMessaging & Streaming
- IBM MQ supportMessaging & Streaming
- ActiveMQ supportMessaging & Streaming
- Azure Service Bus supportMessaging & Streaming
- Amazon SQS supportMessaging & Streaming
- Google Cloud Pub/Sub supportMessaging & Streaming
- Redpanda supportMessaging & Streaming
- Apache Pulsar supportMessaging & Streaming
- Message Queuing supportMessaging & Streaming
Databases & Caching
Search & Analytics
Lakehouse & Compute
Observability & Monitoring
Data Integration
Cloud & Containers
API Management
See support for all 51 technologiesShow fewer
Related services
What does AceMQ Apache Hadoop support include?
Our Hadoop support covers 24/7 emergency incident response with a 15-minute SLA, root cause analysis on every P1, HDFS and YARN performance tuning, Kerberos and security hardening, CVE and EOL patch advisory, and migration planning off Hadoop when that's the right call. Every ticket reaches a named senior engineer with no tier-1 triage layer.
Do you support end-of-life Cloudera or Hortonworks distributions?
Yes. Many enterprises are stranded on distributions that no longer receive vendor patches after the Cloudera-Hortonworks consolidation. We support these clusters with bug workarounds and backported mitigations, and we'll also give you an honest read on whether a migration is worth planning now versus later.
Can you help us migrate off Hadoop entirely?
Yes, and we start with an honest assessment rather than a sales pitch. We look at your actual workload mix against lakehouse or cloud-native alternatives, and if a Hadoop cluster is fixable and a migration would be expensive theatre, we'll say so. When migration is the right call, we plan and execute it.
What causes NameNode heap exhaustion?
Almost always small-file sprawl. Every file and block in HDFS consumes roughly 150 bytes of NameNode heap regardless of file size, so a cluster accumulating millions of small files eventually runs the NameNode out of memory even though total data volume looks modest. We diagnose and remediate this as a standard part of support.
Do you support Kerberized, secured Hadoop clusters?
Yes. Secure cluster support — ticket lifetime tuning, keytab management, and renewal configuration for long-running jobs — is a core part of our Hadoop support, since most regulated enterprises running Hadoop are running it Kerberized.
How fast do you respond to a Hadoop production outage?
P1 emergencies — NameNode down, a cluster-wide re-replication storm, YARN queues frozen — get a 15-minute first response with a senior engineer joining a live bridge. P2 critical issues are 1 hour, P3 high-priority 4 hours, and P4 standard questions next business day. These are contractual targets.
Can we work with AceMQ on Apache Hadoop without a long contract?
Yes. AceMQ works on Apache Hadoop 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.
How much does AceMQ Apache Hadoop support or consulting cost?
Every AceMQ proposal is tailored to your requirements: your Apache Hadoop environment, the SLA you need, the hours of cover and the scope of work. Most contracts run $24,000–72,000 a year, depending on the SLA, the scope and how Apache Hadoop is deployed, with aggressive discounts when several technologies share one contract. Request a quote and AceMQ replies within 1 hour.
Let's talk
A Cluster Nobody Understands Anymore Is Still Your Problem
Reactive cover, proactive reviews, or AceMQ running Apache Hadoop for you on your infrastructure or ours. A senior engineer scopes it with you, and quote requests are answered within 1 hour.
A senior Apache Hadoop engineer, not a sales queueQuote requests answered within 1 hourAd hoc engagements or an annual partnership
Production incident right now?Email an Apache Hadoop Architect
Get in Touch
Talk to an Apache Hadoop Expert
Send us a message and we'll follow up within 1 hour — or book a free 30-min consultation directly.
305-204-2607info@acemq.com66 W. Flagler St. 9th Floor
Miami, FL 33130
Miami, FL 33130
Prefer to talk now? Call us directly or use the consultation tab to find a time that works.