Real-time data has moved from a “nice to have” to the backbone of fraud detection, recommendation engines, and operational AI. If your goal is to learn Apache Flink the way production teams actually use it, this Apache Flink Course is built for engineers who need more than theory: you’ll build, break, and fix real streaming pipelines using the DataStream API, Table/SQL API, and modern connectors, guided by trainers who work with production Flink clusters. By the end, you’ll hold a portfolio, ready project and a certification that proves it.
Prerequisites
- Working knowledge of Java or Scala (Python users can follow along using PyFlink examples)
- Basic SQL skills for the Table API and Flink SQL modules
- Familiarity with distributed systems concepts such as partitioning, replication, and fault tolerance is helpful but not mandatory
- Exposure to Linux command-line basics
- No prior Apache Flink Training or Kafka experience is required – the course starts from fundamentals before moving into advanced, production-grade patterns
Course Objectives
- Understand Flink’s runtime architecture, including JobManager, TaskManager, and the disaggregated state model introduced in Flink 2.x
- Build and deploy streaming and batch pipelines using the unified DataStream and Table APIs
- Implement event-time processing, watermarks, and windowing for out-of-order data
- Design fault-tolerant applications using checkpoints, savepoints, and state backends
- Integrate Flink with Kafka, JDBC sources, object storage, and Paimon/Iceberg table formats
- Write and optimize Flink SQL queries, including materialized tables and changelog operations
- Deploy, monitor, and tune Flink jobs on Kubernetes using the Flink Kubernetes Operator
- Explore emerging patterns such as ML_PREDICT-based inference in SQL and event-driven Flink Agents
- Prepare for and pass the Apache Flink certification exam with confidence
- Get the intensity of an Apache Flink Bootcamp – live labs, real datasets, and instructor feedback in every session
What You Will Learn
- Core stream processing concepts: unbounded vs. bounded data, latency vs. throughput trade-offs
- Flink architecture: JobGraph, ExecutionGraph, slots, parallelism, and resource management
- DataStream API programming: sources, transformations, sinks, and custom functions
- Event time, processing time, watermark strategies, and windowing (tumbling, sliding, session)
- State management: keyed state, operator state, and the disaggregated state backend for large-scale workloads
- Checkpointing, savepoints, and exactly-once processing guarantees
- Flink SQL and the Table API, including materialized tables and changelog conversion operators
- Kafka integration, including dynamic Kafka sources for multi-cluster topologies
- Batch and stream unification, and migration considerations from the deprecated DataSet API
- Deployment on Kubernetes, blue-green deployment strategies, and production monitoring
- Performance tuning: backpressure diagnosis, adaptive partition selection, and resource optimization
- An introduction to AI-driven stream processing, including in-SQL model inference and agentic Flink workflows
Who Should Enroll in This Course?
These Apache Flink Classes are designed for professionals who work with data at scale and want real-time processing skills. It’s a strong fit for:
- Data engineers building or maintaining streaming pipelines
- Big data developers working with Hadoop, Spark, or Kafka ecosystems
- Software engineers transitioning into data engineering roles
- Data architects designing real-time analytics platforms
- DevOps and platform engineers responsible for deploying and scaling Flink clusters
- Analytics and BI professionals who want to work closer to live data
- Computer science graduates and career switchers aiming for streaming or big data roles
Skills You Will Gain
By the end of this course, you’ll be able to:
- Design and implement production-grade stream processing pipelines
- Write efficient Flink SQL for real-time analytics and materialized views
- Manage application state reliably at scale
- Debug and tune Flink jobs for latency, throughput, and resource efficiency
- Integrate Flink into a broader data stack involving Kafka, cloud storage, and table formats
- Deploy and operate Flink applications on Kubernetes with confidence
- Communicate streaming architecture decisions to technical and non-technical stakeholders
Tools Covered
- Apache Flink (DataStream API, Table API, Flink SQL)
- Apache Kafka
- Apache Paimon / Apache Iceberg (open table formats)
- Flink Kubernetes Operator
- Docker and Kubernetes
- Apache Hadoop (HDFS) for storage integration
- Grafana and Prometheus for monitoring
- IntelliJ IDEA / VS Code for development
Career Outcomes
Real-time data skills are in high demand as organizations move from batch reporting to live decision-making, and this training prepares you for roles including:
- Data Engineer
- Big Data Engineer
- Real-Time/Streaming Data Engineer
- Data Platform Engineer
- Data Architect
- Site Reliability Engineer (Streaming Systems)
- Analytics Engineer
| Job Role | Experience Level | India | USA |
|---|---|---|---|
| Data Engineer | Entry Level (0-2 years) | ₹5-9 LPA | $75K-$105K/year |
| Big Data Engineer | Entry to Mid-Level (1-3 years) | ₹6-12 LPA | $85K-$120K/year |
| Data Engineer | Mid-Level (3-6 years) | ₹10-20 LPA | $105K-$145K/year |
| Streaming Data Engineer | Mid-Level (3-6 years) | ₹10-22 LPA | $110K-$155K/year |
| Senior Data Engineer | Senior (6-10 years) | ₹18-30+ LPA | $140K-$180K+/year |
| Senior Big Data / Streaming Engineer | Senior (8+ years) | ₹22-35+ LPA | $150K-$200K+/year |
Why Choose kodestree?
kodestree delivers this Apache Flink Online Training to big data professionals worldwide, and the program is built around what hiring teams actually test for in 2026. Here’s what sets it apart:
- Live, instructor-led sessions with trainers who work on production Flink systems
- Hands-on labs covering Flink 2.x features, not just legacy concepts
- Real-world capstone project for your portfolio
- Flexible weekday and weekend batches
- Lifetime access to recordings and course material
- Dedicated doubt-resolution support during and after the course
- Resume and interview preparation support
- Globally recognized course completion certificate
