Making Dropwizard Metrics Accessible via CQL in Apache Cassandra

Metrics are a vital part of complex distributed storage systems, such as Apache Cassandra. It's important for an operator and a user to have access to metrics at the OS, JVM, and application levels to have full control over the data that is being processed and to prevent emergencies before they occur.

To make metrics accessible, Cassandra heavily relies on the open-source Dropwizard Metrics library, which acts as a skeleton for both metrics representation and storage. Metrics representations are provided as Histogram, Timer, Meter, Gauge, etc. classes for metric types, while storage uses MetricRegistry. The Dropwizard library makes it easy to expose the database internals through various APIs, like JMX or REST, in addition to the sidecar pattern. Apache Casandra has a vibrant ecosystem in this regard, for example, you can write your java-agent to export all data from the registry to the collectd Unix daemon. In conjunction, Cassandra's virtual tables, which are a relatively recent development by the project's standards (available since 4.0), have only a fraction of all the metrics so far, so don't give a full view of internal processes and need to be improved to rectify this.

Data Modeling in Cassandra and Astra DB

What does it take to build an efficient and sound data model for Apache Cassandra and DataStax Astra DB? Where would one start? Are there any data modeling rules to follow? Can it be done consistently time and time again? The answers to these and many other questions can be found in the Cassandra data modeling methodology.

In this post, we present a high-level overview of the data modeling methodology for Cassandra and Astra DB, and share over half a dozen complete data modeling examples from various real-life domains. We apply the methodology to create Cassandra and Astra DB data models for IoT, messaging data, digital library, investment portfolio, time series, shopping cart, and order management. We even provide our datasets and queries for you to try.

Reaper 3.0 for Apache Cassandra Is Available

The K8ssandra team is pleased to announce the release of Reaper 3.1. Let’s dive into the features and improvements that 3.0 recently introduced (along with some notable removals) and how the newest update to 3.1 builds on that.

JDK11 Support

Starting with 3.1.0, Reaper can now compile and run with jdk11. Note that jdk8 is still supported at runtime.