DataStax

The <a href="https://www.arbeitsagentur.de/en/welcome">Bundesagentur für Arbeit</a>—Germany’s Federal Employment Agency (FEA)—is tasked with collecting, analyzing, and managing the data of German citizens, and storing it in accordance with the highest possible privacy standards.&nbsp;

Beyond that, the agency also needs to monitor data from mission-critical information systems to make sure networks, servers, and other infrastructure is operating as designed.

Due to the constantly growing number of records the agency has under its control, the FEA—which employs 100,000 people—recently realized that relational databases could no longer cut it. In particular, searching for records across fragmented databases presented a significant challenge.

So, the IT department started looking for a new solution that would enable administrators to monitor applications and business processes in real time—and while operating at scale. The right solution would also enable them to continuously optimize their applications and take immediate action to prevent bottlenecks from occurring in the first place.&nbsp;

With 2,000 developers and nearly 1,000 infrastructure managers on the payroll, the FEA needed a solution that supported high data ingest rates while also improving performance.&nbsp;

At the same time, the solution needed to be highly secure, highly available, and future-proof so that the agency didn’t have to migrate to a new system in a few years time.

<h2>A solution is found: Apache Cassandra and DataStax</h2>

After doing its due diligence and surveying the market, the FEA ultimately decided that open source <a href="https://www.datastax.com/resources/definitions/what-is-apache-cassandra">Apache Cassandra™</a>, a NoSQL database, was best suited for FEA’s use case. Flexible by design, Cassandra could also scale to support the agency’s ever-increasing data volumes while increasing performance and availability, with no single point of failure.

While Cassandra was a good start, it didn’t solve all of FEA’s problems. So the agency decided to invest in <a href="https://www.datastax.com/products/datastax-enterprise">DataStax Enterprise (DSE)</a>, adding Grafana (for visualizations) and <a href="https://www.datastax.com/products/datastax-enterprise/dse-search">DSE Search</a> (to support complex, long, and nested search queries) to the mix for good measure. Due to the essential nature of its work, the FEA was also drawn to <a href="https://support.datastax.com/hc/en-us">DataStax’s robust support offerings</a>.

Thanks to their decision, the FEA was able to overcome the limitations of relational databases—delivering more value to stakeholders along the way. They’ve eliminated infrastructure monitoring latencies and have the scalability they need to thrive today—and well into the future.

“The DataStax solution provides our IT staff with the agility and responsiveness they need to monitor large amounts of data,” explains Matthias Sessler, FEA’s lead architect for database services. “Together with high scalability, we have laid the technological foundation for the future.”

To learn more about the Federal Employment Agency’s journey to DataStax and what they’ve experienced on the other side, <a href="https://www.datastax.com/resources/case-study/datastax-enterprise-ensures-future-proof-monitoring-germanys-federal">read the full case study</a>.

How Germany’s Federal Employment Agency Uses DataStax Enterprise to Future-Proof Monitoring

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A solution is found: Apache Cassandra and DataStax

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