April 7, 2022 | Episode 207

Scaling an Apache Kafka Based Architecture at Therapie Clinic

  • Transcript
  • Notes

Scaling Apache Kafka® can be tricky, let alone scaling a team. When he was first hired, Domenico Fioravanti of Therapie Clinic was given the challenging task of assembling a sizable tech team from scratch, while simultaneously building a scalable and decoupled architecture from the ground up. In addition, he wanted to deliver value to the company from day one. One way that Domenico ultimately accomplished these goals was by focusing on managed solutions in order to avoid large investments in engineering know-how. Another way was to deliver quickly to production by using the existing knowledge of his team.

Domenico's biggest initial priority was to make a real-time reporting dashboard that collated data generated by third-party systems, such as call centers and front-of-house software solutions that managed bookings and transactions. (Before Domenico's arrival, all reporting had been done by aggregating data from different sources through an expensive, manual, error-prone, and slow process—which tended to result in late and incomplete insights.)

Establishing an initial stack with AWS and a BI/analytics tool only took a month and required minimal DevOps resources, but Domenico's team ended up wanting to leverage their efforts to free up third-party data for more than just the reporting/data insights use case.

So they began considering Apache Kafka® as a central repository for their data. For Kafka itself, they investigated Amazon MSK vs. Confluent, carefully weighing setup and time costs, maintenance costs, limitations, security, availability, risks, migration costs, Kafka updates frequency, observability, and errors and troubleshooting needs.

Domenico's team settled on Confluent Cloud and built the following stack:

  • AWS AppSync, a managed GraphQL layer to interact with and abstract third-party APIs (data sources)
  • AWS Lambdas for extracting data and producing to Kafka topics
  • Kafka topics for the raw as well as transformed data
  • Kafka Streams for data transformation
  • Kafka Redshift sink connector for loading data
  • ​​AWS Redshift as the destination cloud data warehouse 
  • Looker for business intelligence and big data analytics 

This stack allowed the company's data to be consumed by multiple teams in a scalable way. Eventually, DynamoDB was added and by the end of a year, along with a scalable architecture, Domenico had successfully grown his staff to 45 members on six teams.


Continue Listening

Episode 208April 12, 2022 | 10 min

Confluent Platform 7.1: New Features + Updates

Confluent Platform 7.1 expands upon its already innovative features, adding improvements in key areas that benefit data consistency, allow for increased speed and scale, and enhance resilience and reliability. Following the standard for every Confluent release, Confluent Platform 7.1 is built on the most recent version of Apache Kafka 3.1, including KIP-768: extend SASL/OAUTHBEARER with support for OIDC, KIP-773: Differentiate consistently metric latency measured in mills and nanos, as well as KIP-775: Custom partitioners in foreign-key-joins.

Episode 209April 13, 2022 | 38 min

Monitoring Extreme-Scale Apache Kafka Using eBPF at New Relic

New Relic runs one of the larger Apache Kafka installations in the world, ingesting circa 125 petabytes a month, or approximately three billion data points per minute. Anton Rodriguez is the chief architect of the system, responsible for hundreds of clusters and thousands of clients, some of them implemented in non-standard technologies. In addition to the large volume of servers, he works with many teams, which must all work together when issues arise.

Episode 210April 21, 2022 | 51 min

Using Event-Driven Design with Apache Kafka Streaming Applications ft. Bobby Calderwood

In this episode, Bobby Calderwood, founder of Evident Systems and creator of oNote explains event modeling—a converse approach to the reductive data model system. Event model system is enabled by tools like Apache Kafka, which effectively saves every bit of activity generated by the data system.

Got questions?

If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.

Email Us

Never miss an episode!

Confluent Cloud is a fully managed Apache Kafka service available on all three major clouds. Try it for free today.

Try it for free