Sold by: cloudimg
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This product has charges associated with it for seller support. Deploy a production-ready Hadoop cluster in minutes instead of days. Pre-configured HDFS, MapReduce, and YARN with 24/7 cloudimg support on multiple OS variants.
Overview
This is a repackaged open source software product wherein additional charges apply for cloudimg support services.
Hadoop Big Data Stack by cloudimg
Stop spending days manually installing and configuring Hadoop. This pre-configured AMI gives data engineering teams a production-ready Apache Hadoop cluster on AWS - with HDFS, MapReduce, and YARN running and optimized from first boot. Available on Alma Linux 8, Ubuntu 20.04, and Ubuntu 22.04, with 24/7 cloudimg support and a guaranteed 24-hour response SLA.
Who Is This For?
Data engineering teams and platform architects who need full control over their Hadoop infrastructure without the operational overhead of Amazon EMR's managed service model. Ideal for organizations building data lakes, running ETL pipelines, or processing large-scale analytics workloads where cluster-level customization and persistent infrastructure are required.
Why Choose This Hadoop AMI Over Alternatives?
- Full cluster control - Unlike managed services, you retain SSH access, custom configuration, and complete flexibility over Hadoop versions and ecosystem components
- Multi-OS support - Choose from Alma Linux 8, Ubuntu 20.04, or Ubuntu 22.04 to match your organization's standards
- Pre-tuned JVM and storage - Hadoop configuration optimized for EC2 instance storage patterns, reducing time spent on performance tuning
- Cluster expansion with support - Launch additional nodes and cloudimg assists with multi-node configuration and HDFS rebalancing
- 24/7 UK-based support - Guaranteed 24-hour response SLA with average one-hour response for critical issues
Key Components
HDFS Distributed Storage - Reliable file storage across cluster nodes with block replication for redundancy. Petabyte-scale capacity with high-throughput reads, write-once-read-many optimization, and rack awareness for data locality.NameNode manages metadata; DataNodes store blocks.
MapReduce Processing - Parallel data processing framework distributing work across nodes. Map phase splits tasks, Reduce phase aggregates results. Includes fault recovery for failed tasks, data locality optimization, and job history tracking.
YARN Resource Management - Cluster resource scheduler with dynamic allocation, container-based execution, queue management, and ApplicationMaster coordination. Supports multiple processing frameworks beyond MapReduce.
Real-World Use Case: E-Commerce Clickstream Processing
An e-commerce platform ingesting500GB per day of clickstream events can use this AMI to build a processing pipeline: raw event logs land in HDFS via Flume, MapReduce jobs run hourly to sessionize user journeys and compute conversion funnels, and processed data loads into a data warehouse via Sqoop for business intelligence dashboards. The entire pipeline runs on a cluster of storage-optimized EC2 instances with YARN managing job scheduling and resource allocation.
Pre-Configured Integration
- HDFS NameNode and DataNode services configured for startup via systemd
- YARN ResourceManager and NodeManager ready
- SSH access on port 22
- Java runtime optimized for Hadoop workloads
- Configuration files in standard locations
- Log aggregation enabled
- Cluster configuration templates included
Monitoring and Management
- YARN ResourceManager web UI on port 8088
- HDFS NameNode web UI on port 9870
- JMX metrics available for integration with monitoring tools
- systemd service management for all Hadoop daemons
Ecosystem Compatibility
Works with Apache Hive for SQL queries, Pig for data flow scripting, HBase for NoSQL workloads, Spark for in-memory processing, Sqoop for database import/export, Flume for log collection, and Oozie for workflow scheduling.
Fault Tolerance and Reliability
Automatic failure detection and recovery. Block replication prevents data loss. Task retries on node failures. Speculative execution for slow tasks. NameNode high availability configurable for multi-node deployments. Checkpoint and journal nodes protect metadata.
Performance Optimization
Data locality reduces network transfer. Compression support includes Snappy, LZO, and Gzip. Combiner functions reduce shuffle data volume. Rack awareness enables optimal data placement across EC2 availability zones.
Getting Started
- Launch the AMI on your chosen EC2 instance type
- SSH into the instance on port 22
- Verify Hadoop services are running via systemd
- Access HDFS web UI on port 9870 and YARN on port 8088
- Run sample MapReduce jobs from /usr/local/hadoop/share/hadoop
- For multi-node clusters, launch additional instances and contact cloudimg support for cluster formation assistance
Book a Free Cluster Planning Session
Supported Versions
Multiple Apache Hadoop versions available across Alma Linux 8, Ubuntu 20.04, and Ubuntu 22.04.
Highlights
- 24/7 UK-based support with guaranteed 24-hour response SLA and average one-hour response for critical issues. cloudimg assists with HDFS configuration, MapReduce job optimization, YARN tuning, cluster expansion, and troubleshooting. Full OS and Hadoop support included. Book a free cluster planning consultation to size your deployment before purchase.
- Multi-OS Hadoop deployment in minutes - choose from Alma Linux 8, Ubuntu 20.04, or Ubuntu 22.04 with pre-configured HDFS, MapReduce, and YARN ready from first boot. Cluster configuration templates included. JVM and storage settings optimized for EC2 instance types. Unlike managed services, you retain full SSH access and complete cluster control for custom configurations.
- Petabyte-scale architecture with fault tolerance - HDFS block replication prevents data loss, YARN dynamically allocates resources across nodes, and MapReduce retries failed tasks automatically. Scale horizontally by adding EC2 nodes. Monitor via built-in web UIs (YARN port 8088, HDFS port 9870). Compatible with Hive, Spark, HBase, Pig, Sqoop, Flume, and Oozie.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Rhel 8
Deployed on AWS
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Pricing
Free trial
Try this product free for 7 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Description | Cost/hour |
|---|---|---|
m5.large Recommended | m5.large | $0.10 |
t3.micro | t3.micro instance type | $0.06 |
t2.micro | t2.micro instance type | $0.06 |
p2.xlarge | p2.xlarge instance type | $0.15 |
t3a.xlarge | t3a.xlarge instance type | $0.15 |
r4.xlarge | r4.xlarge instance type | $0.15 |
p2.8xlarge | p2.8xlarge instance type | $0.28 |
trn1.32xlarge | trn1.32xlarge instance type | $0.28 |
r5ad.4xlarge | r5ad.4xlarge instance type | $0.28 |
r7i.24xlarge | r7i.24xlarge instance type | $0.28 |
Vendor refund policy
Refunds available on request.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Security patches applied 28-04-2026 (kernel + base OS package upgrades via dnf upgrade --refresh).
Additional details
Usage instructions
Please visit the User Guide for this product on the cloudimg website.
Resources
Vendor resources
Support
Vendor support
cloudimg Support - 24/7/365
Contact: support@cloudimg.co.uk
Response Times:
- Guaranteed 24-hour response SLA for all tickets
- Average one-hour response for critical issues
- UK-based support team
Coverage Includes:
- HDFS configuration and troubleshooting
- MapReduce job optimization and debugging
- YARN tuning and resource allocation
- Multi-node cluster expansion and formation
- Performance optimization and bottleneck analysis
- Operating system support (Alma Linux 8, Ubuntu 20.04, Ubuntu 22.04)
- Apache Hadoop version guidance
Cluster Planning Consultation: Need help before you deploy? Contact support@cloudimg.co.uk to schedule a free 30-minute cluster planning session covering EC2 instance type selection, cluster topology design, and workload sizing.
Recommended Instance Types: For HDFS DataNodes, consider storage-optimized instances (e.g., d2, d3, i3 families) for high-throughput storage. For compute-heavy MapReduce workloads, compute-optimized instances (e.g., c5, c6i families) provide better processing performance. NameNode and ResourceManager roles benefit from memory-optimized instances (e.g., r5, r6i families). Minimum requirements and specific sizing depend on your data volume and processing needs - contact cloudimg support for personalized guidance.
Ports to Open: Ensure your security group allows SSH (port 22), YARN ResourceManager UI (port 8088), and HDFS NameNode UI (port 9870). For multi-node clusters, additional inter-node communication ports are required - cloudimg support provides cluster-specific security group configurations.
Getting Help: For any issues including deployment, configuration, performance, or refund requests, email support@cloudimg.co.uk with your instance ID and a description of the issue.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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