Webinars for Developers
GridGain® webinars present information on a variety of in-memory computing topics, and are often co-hosted with other in-memory computing customers or thought leaders. Topics include in-depth analyses and recommendations for common issues faced by in-memory computing developers, enterprise architects, CIO/CTOs, and other enterprise decision-makers. Different approaches for implementing solutions are reviewed, including solutions using the GridGain in-memory computing platform and Apache® Ignite™. The webinars cover enterprise use cases such as high-frequency trading, omnichannel customer engagement, the Internet of Things (IoT), financial services, application performance and scaling, fast data, and more.
All GridGain webinars are archived and available for free online.
The latest Apache Ignite release includes many new features, such as expanded thin client support, improved cluster monitoring, and enhanced cluster self-tuning. Join Vladimir as he discusses and demonstrates the key improvements that Apache Ignite 2.10 offers:
Spring is a popular framework, and Apache Ignite is a fast layer for data storage. Adding Ignite enables you to manage http sessions, cache-application data, and so on. During this 1.5 hour session, Semyon uses the Spring framework to create a simple web application and demonstrates how Apache Ignite can empower the application. He walks you through steps such as the following:
Apache Ignite’s ANSI-99 SQL support provides application developers a classical SQL database experience while enabling in-memory speeds at a petabyte scale for a variety of workloads.
The latest release of the GridGain in-memory computing platform features enhanced support for the platform’s multi-tier database engine, that scales up and out across memory and disk. The changes enable customers to leverage the disk tier of the database engine to query much larger data sets, reduce cost of ownership, and secure sensitive or personal data at rest.
GridGain Nebula, a managed services offering (MSO) for Apache Ignite and GridGain, can offload the management of your in-memory computing environment to provide maximum reliability at a fraction of the cost of staffing an internal team.
Typically, operations exceed fifty percent of the cost of an IT system’s life cycle. By developing applications that can be easily managed, developers can significantly reduce the cost of ownership. Manageability is especially important for distributed applications because they are especially complex and often mission-critical.
Kafka with Debezium and GridGain connectors enables change data capture (CDC) based synchronization between third-party databases and GridGain clusters. Synchronization that is based CDC does not require coding; all it requires is to prepare configuration files for each of the points.
The GridGain Operator for Kubernetes enables you to deploy and manage Apache Ignite and GridGain clusters efficiently. The automation that Kubernetes and the Operator provide simplifies provisioning and minimizes the operational and management burden.
During this webinar, we review various approaches to storing and using authentication data in distributed applications. Moving from the simplest to the most complex models, we consider the pros and cons of each approach. We give special attention to one of the most popular approaches to distributed sessions—single sign-on.
Apache Ignite can scale horizontally to accommodate the data that your applications and services generate. However, in practice, most of us cannot scale out a cluster instantly.
Serverless computing allows you to design and build scalable cloud-native applications without thinking about infrastructure provisioning and orchestration. With Apache Ignite, you can bootstrap an in-memory cluster in the cloud and access data 100-1000x faster than with disk-based databases.
This webinar will introduce you to the role of the networking layer in distributed systems with Apache Ignite as an example. You will gain practical insights and learn how to maximize the performance and reliability of your applications running on distributed systems.
Join this webinar to get started with an Apache Ignite as a Digital Integration Hub for real-time data access across data sources and applications.
Debugging distributed-system applications can be more complex than debugging traditional monolithic applications. As API calls jump across nodes in the cluster, it can be tricky to follow the execution just by analyzing application logs. Tracing adds a useful tool to the root-cause-analysis toolbox.
Apache Ignite is an excellent tool for external RDBMS, NoSQL or Hadoop database acceleration and offloading. The Ignite in-memory computing platform can power real-time applications that need to process terabytes of data with in-memory speed.
Join us for this webinar to learn about the various Ignite deployment options for database acceleration including:
Join us for a special webinar presented by Branimir Angelov, Co-Founder and CTO of Kubo, Software Architecture Consultant in Obecto, and Member of the Comrade Cooperative.
Many machine learning (ML) and deep learning (DL) platforms are slow in production environments. It can sometimes take hours or days to update ML models. This is a result of having the ML processing run on a different system from the operational transactions system in order to avoid a performance degradation.