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Apache Hadoop Consulting & Support

Apache Hadoop Consulting & Support for Enterprises

Many enterprises are still running Hadoop in production. AceMQ engineers keep those clusters stable and secure, and for teams ready to move, plan the migration to a modern lakehouse. We staff every engagement with a named senior engineer and tell you honestly whether to maintain or modernize.

Without a big-bang migration off the cluster

11+ Senior SMEs<15min Emergency SLA130+ Customers26+ Countries Served

AceMQ is trusted by global brands Including

The Problem

Why teams call us about Apache Hadoop

The NameNode heap is full of small file metadata and restarts take longer every quarter
YARN queues were configured years ago and no longer reflect who needs the capacity
Kerberos keytabs are managed by hand and tickets expire at inconvenient moments
Vendor support for the distribution has ended and the cluster runs an unsupported version
Nobody left in the organisation knows how the Oozie scheduling actually fits together
Data nodes are failing and replacement hardware for that generation is hard to source
HDFS is at capacity and nobody can say which datasets are still read
The renewal quote for commercial Hadoop support now exceeds the value of the workloads it protects
Our Services

Apache Hadoop Consulting & Support

Every engagement is staffed by a senior Apache Hadoop engineer — no juniors, no ticket queues.

01

Cluster Hardening & Capacity Planning

For enterprises still running Hadoop in production, we keep the cluster stable, secure, and sized correctly for current load — without pretending it isn't aging infrastructure.

  • HDFS NameNode capacity planning and federation design for large metadata volumes
  • YARN resource pool and queue configuration for multi-tenant job scheduling
  • Rack awareness and replication factor tuning for storage efficiency and fault tolerance
  • DataNode disk failure monitoring and decommissioning runbooks
02

Migration Off Hadoop to a Modern Lakehouse

This is the conversation most Hadoop prospects actually want to have. We plan and execute migrations from HDFS/Hive to Databricks, Spark on cloud object storage, or another modern platform — with a realistic timeline, not a marketing one.

  • Workload inventory and prioritization: which jobs move first, which get retired
  • HDFS to cloud object storage (S3, ADLS, GCS) data migration with checksums and validation
  • Hive metastore to Unity Catalog or Glue Catalog migration and schema conversion
  • Parallel-run validation and legacy cluster decommission planning
03

Security Hardening for Regulated Environments

Enterprises in financial services and healthcare that are staying on Hadoop for now need Kerberos and encryption done right — not a checkbox implementation that breaks job scheduling.

  • Kerberos authentication setup and principal/keytab management across the cluster
  • Apache Ranger or Sentry authorization policy design for fine-grained access control
  • Encryption at rest (HDFS transparent encryption) and in transit (TLS) configuration
  • Audit logging and compliance reporting for regulated data access
04

Managed Hadoop Operations

Ongoing operational coverage for clusters running end-of-life or aging distributions — someone has to keep YARN scheduling and HDFS replication healthy while you plan the exit.

  • 24/7 monitoring for NameNode health, under-replicated blocks, and YARN queue starvation
  • Upgrade planning off end-of-life Cloudera/Hortonworks (CDH/HDP) distributions
  • Capacity and cost assessment for aging on-prem hardware nearing refresh cycles
  • Disaster recovery architecture: HDFS snapshot policy and cross-cluster replication with DistCp
05

Hadoop Health Check & Assessment

A structured assessment of your Hadoop cluster's health, security posture, and migration readiness, with a clear recommendation on maintain vs. modernize.

  • Cluster utilization and capacity review against current and projected workload
  • Security posture audit: Kerberos configuration, authorization policy, and encryption coverage
  • Distribution end-of-life and support status review (Cloudera, Hortonworks, legacy MapR)
  • Migration readiness assessment scoring workloads by complexity and modernization priority

24/7 Apache Hadoop Support

15 MIN SLA

Named senior engineers on your account — 15-minute emergency response, no ticket routing, no junior triage.

  • 15-minute emergency response SLA
  • Named engineer, zero cold-start
  • Proactive CVE & health monitoring
  • Quarterly deployment reviews
View support plans
How It Works

What actually happens next

11–2 weeks

Cluster and inventory review

We look at NameNode and HDFS health, small file volume, YARN queue usage against real demand, Kerberos and security posture, and which datasets and jobs are still genuinely in use.

2Within a week

Written findings and plan

What must be fixed to keep the cluster safe to run, what is worth migrating, and what can simply be retired. An honest maintain-or-modernise recommendation your leadership can act on.

3Scoped per engagement

Implementation alongside your team

Stabilisation first — the things that would otherwise cause an incident — then migration in tranches by dataset and workload, with the old cluster serving until each tranche is verified.

4Ongoing

Handover and optional cover

Runbooks for NameNode recovery, node replacement and Kerberos renewal, plus 24/7 support with a 15-minute emergency SLA if you want it.

A senior engineer, not an SDR. No sales sequence attached.
Customer Success

Real Apache Hadoop Results

See how enterprises trust AceMQ for their most critical Apache Hadoop workloads.

All use cases
📡Remediation

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 SparkApache HadoopDelta Lake+1
Read case study
💳Consulting

Apache 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 HadoopYARN+1
Read case study
🌐Consulting

Apache Hadoop to Lakehouse Migration

National Insurance Carrier

Moving off an aging Hadoop cluster to object storage and open table formats, with Hive, MapReduce, and Oozie workloads translated rather than lifted.

Apache HadoopApache SparkDelta Lake+1
Read case study
⚡Assessment

Apache 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 HadoopApache HiveApache Spark+1
Read case study
🌐Remediation

Apache 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 Spark+1
Read case study
🛡️Support

Apache 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 Spark+1
Read case study
⚡Remediation

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 NiFiApache KafkaApache Hadoop
Read case study
24/7 Support

Apache Hadoop Support When It Matters Most

Direct access to senior engineers — 15-minute emergency response, no ticket routing, no junior triage.

15 min

Emergency

1 hour

Critical

4 hours

High

Next Day

Standard

How Our Support Actually Works

Beyond SLAs — the model behind senior-only, zero-cold-start expert access.

Named Engineers on Your Account

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.

Live Escalation on Any Ticket

Any ticket can be escalated to a live session with your named engineer via calendar booking. No gatekeeping, no approval required — direct access, always.

Proactive Risk Mitigation

Quarterly health checks on your deployment plus shared intelligence from 50+ support customers — we surface risks before they reach production.

Critical Bug & CVE Intelligence

Proactive alerts on critical bugs and CVEs affecting your exact version, with version compliance monitoring so you're never caught off guard.

Licensing & Security Edge

Dedicated support for vendor license negotiations and compliance audits, plus bi-annual security reviews focused on your specific deployment.

Direct Product Roadmap Access

As the only vendor directly connected to the core engineering teams, AceMQ delivers exclusive early insights, strategic upgrade planning, and curated release summaries — tailored to your environment.

49+ Platforms Supported

We Support Your Entire Tech Stack

Apache Hadoop rarely fails in isolation. AceMQ covers the full surrounding infrastructure — so one team owns the whole path instead of pointing at each other.

Message Brokers & Event Streaming

RabbitMQApache KafkaActiveMQIBM MQAmazon SQSAzure Service BusGoogle Pub/SubRedpandaApache Pulsar

Databases & Caching

RedisMongoDBPostgreSQLMySQLApache CassandraMemcached

Search & Analytics

ElasticsearchOpenSearchELK StackClickHouseApache Druid

Lakehouse & Compute

DatabricksSnowflakeStarburstApache SparkApache HadoopApache Flink

Observability & Monitoring

PrometheusGrafanaDatadogNew RelicSplunk

Data Integration & Orchestration

Apache AirflowApache NiFiAirbytePentaho

Cloud & Containers

KubernetesDockerAWS LambdaAzure Functions

API Management & Integration

KongApigeeMuleSoftWSO2

VMware Tanzu

Tanzu RabbitMQGreenPlumGemFireSpringValkeyPostgres
View Support Plans
Why AceMQ

The engineer model
that actually holds.

No junior triage, no ticket queues, no offshore routing — direct access to the named engineer who knows your environment.

11+

Senior SMEs

<15min

Emergency SLA

130+

Customers

26+

Countries Served

Production-Proven Hadoop Expertise

Our engineers hold deep, hands-on Hadoop expertise from HDFS/YARN cluster operations to Kerberos-hardened deployments at regulated-industry scale.

Break/Fix Through Root Cause

We stay engaged on cluster incidents until the root cause is documented and NameNode/YARN health is fully stable — not just until the alerting clears.

Healthcheck & Quarterly Reviews

Structured capacity, security, and modernization-readiness reviews — with a prioritized remediation report after each one.

15-Min Emergency Response

Named engineer on your account. When NameNode health degrades or a job queue stalls, you call us directly — no ticket, no triage.

FAQs

Apache Hadoop Questions Answered

Common questions about Apache Hadoop consulting, support, and migrations.

Both. We keep production HDFS/YARN clusters stable, secure, and capacity-planned for enterprises that aren't ready to move. But for most teams that call us, the real question is when and how to migrate off Hadoop — and we'll give you a straight answer, not a sales pitch either way.

We start with a workload inventory to prioritize what moves first, then handle HDFS-to-cloud-object-storage data migration, Hive metastore conversion to Unity Catalog or Glue, and parallel-run validation before the legacy cluster is decommissioned. Most enterprises target Databricks or Spark on cloud storage as the destination.

Yes. We implement Kerberos authentication, Ranger or Sentry authorization policies, and encryption at rest and in transit, and we build an upgrade or migration plan for clusters running distributions that are no longer receiving vendor patches.

A structured assessment of cluster utilization, security posture (Kerberos, authorization, encryption coverage), and distribution end-of-life status, scored against migration readiness. We deliver a written report with a clear maintain-vs-modernize recommendation.

We design snapshot policies and cross-cluster replication using DistCp, sized for your actual RPO/RTO requirements, and document the recovery runbook so a NameNode or DataNode failure doesn't become a data loss event while you plan your modernization timeline.

We start with NameNode health metrics and under-replicated block counts to isolate the failure layer, then move to stabilization and a documented root cause. We stay engaged until the cluster is fully recovered, and we'll flag whether the incident is a symptom of a bigger modernization conversation worth having.

Still have questions about Apache Hadoop?

Email an Expert

Ready to Stabilize or Modernize Your Hadoop Environment?

Whether you need emergency support, a security hardening engagement, a migration partner, or ongoing managed operations while you plan your exit — AceMQ staffs every engagement with a named senior Hadoop engineer. Get a quote in 24 hours.

Email an Apache Hadoop Architect
Get in Touch

Talk to an Apache Hadoop Expert

Send us a message and we'll follow up within one business day — or book a free 30-min consultation directly.

305-204-2607
info@acemq.com
66 W. Flagler St. 9th Floor
Miami, FL 33130

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