2022-06-13 –, Maschinenhaus
Learn how the Data Infrastructure team at Brandwatch rearchitected a group of their current Solr clusters and took a new approach in an unconventional manner. By splitting up the reads and writes, experimenting with Solr plugins, using S3, an application written in Rust and adopting the Solr Operator to spin up a cluster on Kubernetes, we were able to achieve our goal of having a cloud-based cluster which comfortably serves 26bn+ documents.
You'll understand the whys of our approach, things we discovered, what we have planned, and why rearchitecting things can be a difficult and strenuous task.
The Search track is presented by OpenSource Connections
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Currently a Senior Data Infrastructure Engineer at Brandwatch in Brighton, UK, having joined fresh out of University several years ago. Working in the Data Infrastructure team is all about making Brandwatch's data safe, reliable and available. Using techs such as Solr, Kafka, HBase, Airflow, Postgres and Kubernetes. I developed an interest in Solr early on in my career and that has been my main focus working in this team. Over the last couple of years I began my journey in contributing to the open-source community submitting a few small patches for Solr.
I take a keen interest in anything Solr, Python and monitoring, having spent a good time elevating our monitoring stack here at Brandwatch, overhauling our entire monitoring stack for Solr. More recently, I've lead a project to take a cluster from the data center to host in AWS in a cost-effective manner and have better scalability.
Outside of work I take interest in classical music, being trained in Piano and Flute, sewing, D&D and video games.