9 Steps for Building a Highly Available Time-Series Solution with ScyllaDB and KairosDB

Building a highly available time-series solution involves using KairosDB and ScyllaDB to efficiently manage and scale data storage and retrieval. KairosDB acts as a front-end framework for ingesting and retrieving sensor information or metrics, while ScyllaDB serves as a high-performance backend database capable of indefinitely scaling to store vast amounts of time-series data. The integration of Collectd helps push ScyllaDB metrics into KairosDB, which then stores the data on a separate ScyllaDB cluster. This setup eliminates issues related to siloed monitoring and scaling by allowing the ScyllaDB storage layer to expand infinitely. The process involves configuring KairosDB to work with ScyllaDB, ensuring SELinux is disabled on the monitored ScyllaDB cluster, and using tools like Cassandra-stress to generate traffic, which can then be monitored using KairosDB's web UI or REST-API for executing queries and visualizing metrics.