Course Outline

Fundamentals of NiFi and Data Flow for Government

  • Concepts and challenges related to data in motion versus data at rest
  • NiFi architecture: cores, flow controller, provenance, and bulletin
  • Key components: processors, connections, controllers, and provenance

Big Data Context and Integration for Government

  • The role of NiFi in big data ecosystems (Hadoop, Kafka, cloud storage)
  • Overview of HDFS, MapReduce, and modern alternatives
  • Use cases: stream ingestion, log shipping, event pipelines

Installation, Configuration & Cluster Setup for Government

  • Installing NiFi on single node and in cluster mode
  • Cluster configuration: node roles, ZooKeeper, and load balancing
  • Orchestrating NiFi deployments using Ansible, Docker, or Helm

Designing and Managing Dataflows for Government

  • Routing, filtering, splitting, and merging flows
  • Processor configuration (InvokeHTTP, QueryRecord, PutDatabaseRecord, etc.)
  • Handling schema, enrichment, and transformation operations
  • Error handling, retry relationships, and backpressure management

Integration Scenarios for Government

  • Connecting to databases, messaging systems, and REST APIs
  • Streaming data to analytics systems: Kafka, Elasticsearch, or cloud storage
  • Integrating with Splunk, Prometheus, or logging pipelines

Monitoring, Recovery & Provenance for Government

  • Using the NiFi UI, metrics, and provenance visualizer
  • Designing autonomous recovery and graceful failure handling mechanisms
  • Backup, flow versioning, and change management practices

Performance Tuning & Optimization for Government

  • Tuning JVM, heap, thread pools, and clustering parameters
  • Optimizing flow design to minimize bottlenecks
  • Implementing resource isolation, flow prioritization, and throughput control

Best Practices & Governance for Government

  • Flow documentation, naming standards, and modular design principles
  • Security measures: TLS, authentication, access control, and data encryption
  • Change control processes, versioning, role-based access, and audit trails

Troubleshooting & Incident Response for Government

  • Common issues: deadlocks, memory leaks, processor errors
  • Log analysis, error diagnostics, and root cause investigation techniques
  • Recovery strategies and flow rollback procedures

Hands-on Lab: Realistic Data Pipeline Implementation for Government

  • Building an end-to-end data flow: ingestion, transformation, and delivery
  • Implementing error handling, backpressure management, and scaling solutions
  • Conducting performance testing and tuning the pipeline

Summary and Next Steps for Government

Requirements

  • Experience with Linux command line operations
  • Fundamental knowledge of networking and data systems
  • Familiarity with data streaming or ETL (Extract, Transform, Load) concepts

Audience for Government

  • System administrators
  • Data engineers
  • Developers
  • DevOps professionals
 21 Hours

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