As enterprises continue to run critical analytics workloads on premises, developers and platform teams increasingly need deployments that go beyond service installation and focus on real workload validation. This blog shares the experience of deploying Cloudera on premises on Nutanix AHV using a step-by-step deployment guide and validating the environment with Project Axon, an end-to-end on-prem analytics use case that exercises ingestion, processing, analytics, and AI workflows across Cloudera services. Rather than focusing solely on infrastructure readiness, the deployment was validated using a realistic analytics use case spanning Cloudera Base, Cloudera Data Services, and enterprise security integrations. The goal was to ensure developers can build, run, and operate production-style pipelines without friction from the underlying platform.   Why does this matter? Nutanix AHV delivers a modern hyperconverged foundation with the following benefits: Simplified Operations – A single, unified platform for compute, storage, and networking Elastic Scaling – Independent scaling of Cloudera master and worker nodes based on workload demands Cost Efficiency – No additional hypervisor licensing overhead Enterprise Security – Integrated networking, isolation, and encryption capabilities Automation – API-driven VM lifecycle management through Prism Central These capabilities make Nutanix AHV an ideal substrate for Cloudera’s hybrid data platform.   Technical Stack Cloudera and Nutanix components:   Component Key Version Role RedHat Enterprise Linux (RHEL) 9.6 Operating System Cloudera Manager 7.13.2.0 Centralized cluster management Cloudera Runtime 7.3.2.0 Cloudera's core data runtime Cloudera Data Services (ECS) 1.5.5 SP2 Platform for Data Services Prism Central Version pc.7.5 Nutanix’s centralized management platform AOS (Acropolis OS) Version 7.5.1 Software-defined storage layer AHV version 11.0.1 Nutanix hypervisor for virtual machines You can also refer to the Nutanix Compatibility and Interoperability Matrix for the latest Cloudera support details and validated configurations here.    End-to-End Functional Validation Using Project Axon Using Project Axon, the deployment was validated across the full analytics lifecycle, covering secure ingestion, distributed processing, SQL analytics, and visualization on Cloudera running on Nutanix AHV. Specifically, the Bank Branch Performance Analytics use case from Project Axon was executed to validate real-world behavior across services: Data Ingestion: Apache NiFi ingested data from a dummy Python-based generator across multiple datasets and persisted it into HDFS/Ozone, validating secure and stable ingestion. Data Processing & Engineering: Spark 3.5.4–based Virtual Clusters were provisioned using Cloudera Data Engineering. Hadoop authentication was configured using keytabs, and Spark jobs were executed for data transformation and summarization, with Airflow pipelines orchestrating the workflows. Analytics & SQL: As part of this field validation, Hive and Impala Virtual Warehouses were enabled using Cloudera Data Warehouse, with interactive queries executed via Hue on data ingested by NiFi and processed by Cloudera Data Engineering Spark jobs. End-to-End Outcome: Analytics results were visualized using Cloudera Data Visualization by creating dashboards such as best-performing branches, revenue contribution per branch, and call center records analysis, confirming correct data flow across all layers. Cloudera AI Deployment Validation In addition to the Project Axon validation, Cloudera AI was deployed and validated on the Nutanix-backed Kubernetes environment. The AI Workbench was created successfully Hadoop authentication was configured Session lifecycle operations were validated using sample project templates Cloudera Agent Studio was deployed Enterprise Security A comprehensive security framework was implemented to meet enterprise compliance and governance requirements: Identity & Access: Integrated Active Directory as the centralized identity provider, DNS server, leveraging LDAP and Kerberos for secure authentication and principal management. Data Protection: Enabled AutoTLS across all Cloudera services to secure data in transit, and enforced fine-grained authorization using Ranger policies. Gateways : Enabled Knox for secure SSO-based access and configured Atlas for metadata and lineage management. Additional Deployment Considerations Based on field discussions and deployment experience, the following practices are recommended for production deployments on Nutanix AHV: For storage attached to HDFS DataNode VMs, using Nutanix Volume Groups (VGs) is recommended, as they behave similarly to VMware independent disks and remain preserved even if a VM is accidentally deleted, unlike standard vDisks. When leveraging Nutanix AOS replication, a commonly recommended approach is configuring HDFS replication factor (RF) as 2 together with AOS RF2 and enabling EC-X for storage efficiency and resiliency. VM affinity and anti-affinity policies, workload isolation, and spare capacity planning should be considered to support high availability and planned maintenance operations for physical nodes on Nutanix. For additional deployment guidelines and VM placement best practices, refer to the guide here. Conclusion This deployment field validates Cloudera on premises on Nutanix AHV for running end-to-end analytics with enterprise-grade security, scalability, and operational simplicity. By validating the environment with Project Axon, we tested not just service availability, but real developer and data engineering workflows, ensuring the platform is ready for production use. For teams looking to deploy or standardize on Cloudera on Nutanix, this work provides a trusted, validated blueprint backed by functional and operational testing. It also forms the foundation for Cloudera–Nutanix certification, giving customers, partners, and field teams a reference architecture for production-grade deployments.   ... View more