A comprehensive technical handbook covering Azure HDInsight, Microsoft's managed Hadoop, Spark, and big data analytics service. This guide covers cluster architecture, Spark and Hive workloads, Kafka and Storm integration, enterprise security with ESP, monitoring, cost optimization, migration strategies, and production deployment best practices.
Chapters
Provisioning and Configuring HDInsight Clusters
20 min read
Storage Abstraction: Azure Data Lake Storage Gen2
18 min read
Deep Dive into Apache Spark on HDInsight
25 min read
Optimizing Hive Queries and Data Warehousing
22 min read
Streaming Data Pipelines with Apache Kafka
25 min read
Real-Time Processing with Apache Storm
20 min read
Enterprise Security and Kerberos Authentication
25 min read
Role-Based Access Control with Apache Ranger
20 min read
Data Governance with Apache Atlas
18 min read
Performance Tuning and Cluster Sizing
22 min read
Monitoring, Logging, and Diagnostics
15 min read
Cost Optimization and Resource Management
15 min read
Managing High Availability and Disaster Recovery
20 min read
Automating Deployments with ARM Templates and Terraform
25 min read
Migrating On-Premises Hadoop to Azure HDInsight
20 min read
Integrating HDInsight with Azure Synapse Analytics
18 min read
CI/CD Pipelines for Big Data Workloads
20 min read
Production Deployment Best Practices
20 min read
Career Roadmap and Future Trends in Big Data
15 min read