This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing?
In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
Now, deploying Hazelcast-powered applications in a cloud-native way becomes even easier with the introduction of Hazelcast Cloud Enterprise, a fully-managed service built on the Enterprise edition of Hazelcast IMDG. Can't attend the live times? You should still register! We'll be sending out the recording after the webinar to all registrants.
HUK-COBURG is Germany’s largest motor vehicle insurance company for private households, with around 12 million customers. It is based in Coburg, Germany, and has over 10,000 employees. It offers vehicle, liability, accident, household, home, life, legal protection, and private health insurance. Their IT department has about 800 employees, divided among three main teams: operations, development and architecture, and company organization. These teams are responsible for building software solutions that help the company drive business initiatives. Some projects include their public-facing websites, mobile apps, and their insurance premium calculator. The latter use case gathers data from transponders in vehicles to track data like velocity so that the company can calculate premiums based on safe driving
HUK-COBURG was undergoing a digital transformation initiative to leverage technology to give them a competitive advantage. The initiative entailed improving customer satisfaction as well as reducing the cost of maintaining the data infrastructure. They also needed a better way to improve system reliability, as they expect to run 24×7 systems. The business teams required an upgrade to the data flows and processes, so it was up to the architecture team to propose new solutions to meet the business teams’ needs.
In one part of their infrastructure, they were reading telematics data to calculate insurance premiums for their customers. But data accesses to the mainframe were costly due to the complicated path in which the data was routed. Access required going through multiple firewalls and validation systems. In addition, there were times that the connection was unavailable, which hampered their ability to serve their customers. Their new premium pricing initiative, which relied on the telematics data, continued to grow rapidly since they were moving many existing customers to that pricing program. They anticipated tripling the customer count to the hundreds of thousands, so the current latency and unavailability would soon become huge problems.
They knew they would save a significant amount of time and cost if they could cache some of the data retrieved from the mainframe. They also knew this could represent a resiliency pattern where the required data would always be available in the cache even if the connection to the mainframe was unavailable.
HUK-COBURG had an existing solution based on another in-memory technology, which was deployed on a per-service basis. Since they were not able to deploy it as a centralized cluster, it did not meet their needs, and they began exploring other technologies.
They started their technology exploration like most companies, by running internet searches to first identify the leading technologies. When searching for “caching frameworks,” they got results that included Hazelcast and other caching technologies. HUK-COBURG evaluated those technologies and found Hazelcast to be the most powerful. They then searched for training sessions and workshops on Hazelcast, and they attended a training session in Stuttgart that helped them get up to speed on Hazelcast. The compelling offerings from Hazelcast helped them to justify the move forward to procure a license from Hazelcast. Their first implementation solved their immediate requirements around performance and availability. As their centralized cache, Hazelcast eliminated the unnecessarily slow network accesses to their mainframe so they could serve many more customers at once. And the fact that Hazelcast is designed for 24×7 operation, with its high availability features, ensured that data was always available to customers.
As a result of the Hazelcast implementation, everything they process now runs faster. For example, some telematics data formerly took about 500 milliseconds to retrieve, but now takes less than 50 milliseconds. This 10X improvement is crucial for giving them the performance headroom to service their growing customer base, while providing the great experience that today’s consumers demand.
The goal of reliability was also achieved, as their Hazelcast implementation has run for over a year with zero downtime. High availability is also a key metric for all of HUK-COBURG’s systems, and Hazelcast is able to keep them running without unnecessary administrative overhead.
The feature-richness of the Hazelcast product makes it useful for a number of applications. Its use was expanded as a content cache to boost performance for mobile apps, websites, and some internal apps. It is currently used in seven different projects, including their health care app, Meine Gesundheit (“My Health”).
Contact us now to learn more about how our in-memory computing platform can help you leverage data in ways that immediately produce insight and actions.