- Apache Ignite architecture in depth such as data distributing technics (DHT), Rendezvous hashing, durable memory architecture, various cluster topologies, Ignite native persistence, Baseline topology and much more.
- Apache Ignite proven use-cases as a memory-centric distributed database, caching and computing platforms.
- Getting started with Apache Ignite by using different tools and technics.
- Caching strategies by examples and how to use Apache Ignite for improving application performance including Hibernate L2 cache, MyBatis, Memoization and Web session clustering.
- Using Spring Data and JPA (Hibernate OGM) with Apache Ignite for developing high-performance web applications.
- Ignite query (SQL, API, Text and Scan queries) capabilities in depth.
- Using Spark RDD and Data frames for improving performance on processing fast data.
- Developing and executing distributed computations in a parallel fashion to gain high performance, low latency, and linear scalability.
- Developing distributed Microservices in fault-tolerant fashion.
- Processing events & streaming data for IoT projects, integrate Apache Ignite with other frameworks like Kafka, Storm, Camel, etc.
- Real-time data Replication between Ignite clusters through Kafka.
- Configuring, management and monitoring Ignite cluster with built-in and 3rd party tools.