IBM Distinguished Engineer and CTO
How IBM Leverages Event-Driven Architecture with Apache Ignite for Core Application Modernization
Application modernization is essential for all organizations, regardless of industry. To offer clients next-generation experiences and compete with new entrants in that industry, organizations must modernize their core applications and take advantage of modern architectural patterns such as microservices and event-driven architectures.
Modernizing old and fragile applications can be very challenging, time-consuming, and risky. Big Bang approaches don’t provide business value quickly enough, require a significant investment, and are a non-starter. Incremental approaches are technically complex and require substantial engineering; you need to establish a modern target architecture and a co-existence architecture. You need to simplify and standardize the integration. You need to figure out how you modernize the data.
In my role at IBM, I’ve worked with many clients that face the same challenges. This session will describe an event-driven Book of Reference pattern we call the “Digital Core” that we have leveraged to address these challenges. The pattern unlocks data in core systems of record breaking down data silos. It handles both streaming and batch data, leverages an industry-aligned data model, and has a speed layer based on Apache Ignite, among other capabilities. The pattern enables incremental modernization or complete replacement of a core system of record. It abstracts away the systems of record and the challenges that go with them.
Lead Developer at BNP Paribas CIB
Apache Ignite as a Hybrid Transactional-Analytical Processing Solution at a Large Investment Bank
Today, at BNP Paribas, our Apache Ignite cluster is running successfully in production and is being used globally across all divisions of our corporate investment bank. Ignite uses 600 CPU cores and 9 TBs of RAM to handle a steadily increasing number of users, multiple complex hybrid transactional-analytical operations, and events that come from various data sources.
In this session, we share our experience in designing, building, and optimizing a hybrid transactional-analytical processing (HTAP) solution that is powered by Ignite and that enables BNP Paribas to make key business decisions in real time. We cover the following:
- The reasons that we chose Apache Ignite as a data analysis tool
- Best practices and tradeoffs for designing an HTAP solution that analyzes multidimensional historical and real-time datasets
- Tips and tricks for using Ignite compute, SQL, key-value, and streaming APIs to implement complex algorithms and operations, including trading strategies
- Optimization tactics for Ignite clusters with native persistence
Chief Architect at GridGain
Apache Ignite Storage Engine Architecture: Tradeoffs and a Retrospective
Apache Ignite native persistence storage engine follows a classic database approach that is based on ARIES architecture. However, Ignite developers needed to adjust the architecture to increase development velocity and facilitate memory-only storage.
After an overview of the storage engine, you will learn about the tradeoffs that Ignite developers made during development and about the reasons that drove the developers’ decisions. Also, you will learn about the difficulties that were encountered during the implementation of the chosen approach in Java and how the Ignite community overcame the difficulties.
This under-the-hood talk is for architects and engineers who want to learn more about ARIES and Apache Ignite architectures.