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Cloudera Hybrid Data Platform Engineering

We help organizations run, modernize and extend Cloudera across data centers and public clouds, with Apache Iceberg, governed pipelines and AI workloads on one consistent platform.

Modernize Cloudera Without Starting Over

Many enterprises have years of investment in Cloudera clusters: HDFS data, Hive tables, Spark jobs, NiFi flows and Ranger policies that business processes depend on. Cloudera’s current direction is a hybrid data platform with the same experience in the data center and the cloud, an open lakehouse built on Apache Iceberg, and shared security and governance through SDX. Hanoi Technology helps teams move toward that model step by step, without a risky big-bang re-platforming.

Our engineers work with Cloudera on premises and in public cloud environments. We plan and execute upgrades, convert legacy Hive tables to Iceberg, rebuild fragile pipelines, tune Spark and Impala workloads, and set up governance that satisfies security teams. Where it makes sense, we also connect Cloudera with Snowflake, Databricks or cloud-native services through open table formats.

The Challenge

Common Cloudera Pain Points

Long-running Cloudera estates accumulate technical debt that slows every new initiative.

Aging Clusters and Upgrade Fear

Older CDH or HDP-era clusters are hard to upgrade because nobody is sure which jobs depend on which components. Teams postpone upgrades until support windows force a rushed migration.

Small Files and Slow Queries

Years of streaming ingestion and partition sprawl create millions of small files. Hive and Impala queries slow down, compaction jobs fail and storage costs grow without adding value.

Fixed Capacity in the Data Center

On-premises clusters are sized for peak loads, so they sit idle most of the month and still run out of capacity at quarter end. Buying hardware for spikes is slow and expensive.

Governance Spread Across Tools

Ranger policies, Atlas metadata and ad-hoc access scripts drift apart over time. Auditors ask who can see sensitive columns, and the honest answer takes weeks to assemble.

Business Value

What a Modern Cloudera Platform Gives You

Open Lakehouse on Apache Iceberg

Iceberg tables add ACID transactions, schema evolution, hidden partitioning and time travel. The same tables can be read by Spark, Impala, Hive and external engines.

True Hybrid Flexibility

Workloads run in the data center or in the cloud with a consistent experience. Data stays where regulations require while compute moves where it is cheapest.

Elastic Capacity for Peaks

Cloudera’s cloud bursting capability extends private capacity into public cloud for spikes. Planning hardware for the worst week of the year becomes unnecessary.

Centralized Security and Lineage

SDX applies shared security, governance and metadata across services. Access policies and lineage are defined once instead of per engine.

Lower Maintenance Overhead

Automated table optimization and fewer bespoke scripts reduce the effort spent on compaction and cleanup. Engineers spend more time building and less time firefighting.

A Foundation for Enterprise AI

Governed data, Cloudera AI and open interfaces let teams build machine learning and generative AI close to the data. Sensitive data does not have to be copied to a separate AI environment.

Evolution Beats Re-Platforming

Most Cloudera customers do not need to rip out their platform to modernize. Converting tables to Iceberg, rationalizing pipelines and adopting hybrid capacity in planned steps usually delivers faster value with far less risk than moving every workload to a new vendor at once.

Our Services

Hanoi Technology’s End-to-End Cloudera Services

We support Cloudera estates at every stage, from health checks to full modernization programs.

Platform Assessment and Health Check

We review cluster configuration, workloads, storage layout, security policies and support status. The result is a prioritized list of risks and quick wins, plus a modernization roadmap.

  • Workload and dependency inventory
  • Risk and quick-win report
  • Modernization roadmap

Upgrade and Migration Execution

We plan and run upgrades and migrations to current Cloudera releases, on premises or in the cloud. Dependency mapping, rehearsal runs and rollback plans keep business jobs running.

  • Dependency map and runbook
  • Rehearsal and cutover plan
  • Post-upgrade validation

Apache Iceberg Adoption

We convert priority Hive tables to Iceberg, redesign partitioning and set up table maintenance. Downstream jobs are tested against the new tables before switchover.

  • Table conversion plan
  • Partition and maintenance design
  • Query performance comparison

Pipeline Engineering With Spark, NiFi and Kafka

We rebuild brittle ingestion and transformation jobs with Spark, Cloudera DataFlow based on Apache NiFi, and Kafka streaming. Pipelines get testing, monitoring and clear ownership.

  • Refactored pipelines
  • Data quality checks
  • Monitoring and alerting

Security, Governance and Compliance

We consolidate Ranger policies, configure Atlas lineage and classifications, and implement column masking for sensitive fields. Access reviews become a report rather than a project.

  • Policy consolidation
  • Lineage and classification setup
  • Access review reports

Managed Platform Operations

Our team can operate your Cloudera environment day to day, handling patching, job failures, capacity planning and user requests. You get weekly written updates and clear escalation paths.

  • Operational runbooks
  • Capacity and cost reports
  • Weekly status updates

Our Approach

Our Cloudera Modernization Approach

We sequence changes so the business sees improvements early while risk stays controlled.

  1. 01

    Assess the Estate

    We collect cluster metrics, job histories, table statistics and policy exports. Interviews with platform owners and data consumers reveal which workloads are critical.

    Deliverables: Estate assessment report · Critical workload list

  2. 02

    Define the Target Architecture

    We design the target state for storage formats, compute placement, security and integration with other platforms. Decisions are recorded with trade-offs so they can be revisited.

    Deliverables: Target architecture document · Architecture decision records

  3. 03

    Pilot on a Representative Domain

    One domain is modernized end to end, including Iceberg conversion, pipeline refactoring and governance. The pilot proves performance and operational procedures.

    Deliverables: Pilot domain in production · Measured before-and-after results

  4. 04

    Scale in Waves

    Remaining workloads move in planned waves grouped by dependency and risk. Each wave has rehearsal, validation and a rollback plan.

    Deliverables: Wave plan and schedule · Wave validation reports

  5. 05

    Operate and Optimize

    We tune cost and performance, retire unused jobs and tables, and hand over runbooks. Ongoing support can continue as a managed service.

    Deliverables: Optimization backlog · Handover and training

Use Cases

Cloudera Use Cases We Support

Cloudera is strongest where data volume, regulation and hybrid requirements meet.

Regulated Data That Must Stay On Premises

A bank keeps customer transaction data in its own data center while running seasonal analytics in the cloud. Shared governance ensures the same masking rules apply in both locations.

Telecom Network Analytics

Streaming network events flow through Kafka and NiFi into Iceberg tables. Engineers query recent and historical data together to investigate outages and capacity issues.

Manufacturing Sensor Data

Sensor readings from production lines land in the lakehouse for quality analysis and predictive maintenance models. Edge flows filter noise before data reaches the central platform.

Hive to Iceberg Modernization

A data team converts its most queried Hive tables to Iceberg to eliminate small-file problems. Reports that once timed out now finish within normal business windows.

Quarter-End Capacity Bursting

Finance and risk workloads spike at quarter end. Burst capacity in the cloud absorbs the peak without buying hardware that sits idle the rest of the quarter.

Sharing Data With Other Platforms

Analysts on Snowflake or Databricks read governed Iceberg tables managed in Cloudera without duplicate copies. Each team keeps its preferred tools while the data stays consistent.

Technology

Technologies in Our Cloudera Work

We work across the open-source engines and services that make up the Cloudera ecosystem.

  • Cloudera Data Platform
  • Apache Iceberg
  • Apache Spark
  • Apache Impala
  • Apache Hive
  • Apache NiFi
  • Cloudera DataFlow
  • Apache Kafka
  • Apache Ranger
  • Apache Atlas
  • Apache Ozone
  • Cloudera AI
  • Apache Airflow
  • Kubernetes
  • AWS
  • Microsoft Azure

Platforms

Deliver Cloudera on Your Preferred Platform

Why Hanoi Technology

Why Organizations Choose Hanoi Technology

Senior, Cross-Functional Teams

Strategy, data, AI, cloud and engineering specialists work as one team, so nothing is lost between hand-offs.

Proven Delivery

More than 50 projects delivered for clients in North America, Europe and Asia-Pacific.

Radical Transparency

A written update every week and a demo of working software every sprint, so you always know where things stand.

Cost-Effective Global Delivery

Experienced engineers from our Hanoi delivery hub, with working-hour overlap for every major time zone.

−25%operational costs

Success Story · Logistics

Route optimization and fleet visibility for a regional logistics company

A regional delivery company handling thousands of shipments a day was planning routes and dispatching by hand. We built dynamic route optimization, a fleet dashboard and a driver app.

Read the Full Story

More Success Stories

Explore All Success Stories

Resources

Featured Resources

Industry trends and practical guidance to help you get more value from data, AI and technology.

Get a Clear Plan for Your Cloudera Estate

Book a free consultation to talk through your clusters, upgrade timelines and modernization goals. We reply within 24 hours and can suggest a practical first step.

Cloudera FAQ

Is Hanoi Technology a Cloudera partner?

We do not claim official partner status with Cloudera. We are an independent engineering team that works with Cloudera environments: assessing, upgrading, modernizing and operating them. Your licenses and vendor support remain with Cloudera. Our role is the hands-on engineering around the platform, including pipelines, table design, governance configuration and integration with other tools in your stack.

Should we stay on Cloudera or move to another platform?

There is no single answer. Cloudera is a strong fit when you need consistent on-premises and cloud deployments, strict data residency, or heavy use of open-source engines. Other platforms may suit cloud-only teams that want fully managed services. We assess workload profiles, regulatory constraints, skills and total cost before recommending anything, and open formats like Iceberg often let you combine platforms rather than choose just one.

How risky is a Cloudera upgrade?

Risk comes mainly from unknown dependencies: jobs that rely on deprecated components, custom scripts or specific library versions. We reduce that risk by building a dependency map from job histories and configuration, rehearsing the upgrade in a non-production environment, defining validation tests for critical jobs and keeping a rollback plan ready. With that preparation, most of the uncertainty is removed before cutover weekend.

What does converting Hive tables to Apache Iceberg involve?

We select tables based on query volume and pain points, choose between in-place migration and rewriting data, redesign partitioning using Iceberg’s hidden partitioning, and set up maintenance such as compaction and snapshot expiry. Downstream jobs and reports are tested against the new tables before switchover. Conversion is usually done in batches so each step is easy to validate and reverse if needed.

What drives the cost of a Cloudera modernization project?

Scope is driven by the number of clusters and workloads, data volumes, the state of existing pipelines, security requirements and the degree of integration with other systems. Upgrades with good documentation are faster than estates where knowledge has left the company. We start with an assessment that produces a phased estimate, and you can engage us as a project team, a dedicated team or for managed operations.

Can you support our Cloudera platform after the project?

Yes. We offer managed operations covering monitoring, job failure triage, patching, capacity planning and user access requests. Work is tracked transparently and you receive weekly written progress updates. Many clients start with a modernization project and then move to a smaller ongoing team that keeps the platform healthy and continues optimization work.