Even since its early days when Apache Cassandra was first developed at Facebook, the distributed database system has offered the flexibility, scalability, and reliability that database and DevOps teams require in today’s rapidly changing world. As more organizations adopt Cassandra as a key component of their database infrastructure, there’s even more of a need to offer a database performance monitoring solution that can provide the necessary insight into key metrics to optimize your Cassandra environment.
Beyond metrics, there are several other elements that contribute to your Cassandra performance. In this blog post, I’ll highlight what you can do to ensure that your Cassandra workloads are operating at peak efficiency.
1. Monitor the Top Metrics for Cassandra Performance
When it comes to optimizing Cassandra performance, you need visibility into key metrics to understand which part of your environment may be causing problems. Is your garbage collection faltering? Has your read/write rate dropped? Are you compactions elevated?
With any database, there are hundreds — if not thousands — different metrics that you can track. At times, these all serve their purpose, but if you are looking for the top metrics to monitor for your Cassandra environment, here is where you can start.
Among numerous database types, latency gives the first indication if your environment faces performance issues. Within Cassandra, read/write latency tells you how long it takes to execute a query.
Whether it’s by cluster or node, breaking down the amount of disk being used across your Cassandra environment can indicate whether you need to add more capacity to ensure your performance doesn’t falter because you ran out of disk space.
Because Cassandra is a Java application, garbage collection serves as an important component of your performance. If you are unfamiliar, garbage collection refers to the process to remove data that is no longer used. It frees up memory, which positively impacts performance. However, if you fail to execute garbage collection, your performance can come to a rapid halt until you free up memory.
Heap size, which is part of the garbage collection process, helps you determine how much data should be removed at a time. Of course, it’s tempting to set this as high as you can, given your RAM. However, this can have a negative impact on performance, specifically on your OS page cache. Cassandra calculates a default heap size, which may work depending on your needs and your hardware.
Other key Cassandra metrics that are important to monitor include those related to:
2. Use Alerts and Recommendations
Metrics are a key component of your strategy to optimize performance. Take it up a notch with alerts and recommendations. Leveraging alerts, you can receive an indication of where your Cassandra environment needs attention before it compromises your performance to your end users.
In addition, recommendations take it one step further to provide insight into how you can prevent alerts from triggering again in the future, as well as modifying parts of your Cassandra environment to optimize performance.
Often times, an underlying problem is just that: an issue that has yet to bubble to the surface and create a notable impact that causes alarm. Because of this, by the time you detect it, it might be too late, as you already see a dip in performance. Recommendations change this and help you tackle the problem before it brings your environment to a halt.
3. Find a Comprehensive Database Monitoring Solution
As a distributed system, it can be difficult to find a database monitoring solution that monitors all the key data that you need to know. Digging deep into key database metrics like memory, latency, and load continues to be important, but it’s more important to track metrics unique to Cassandra, including garbage collection, heap size and usage, and gossip storage.
Having insight into these key metrics can ensure that your Cassandra system gives you the flexibility, scalability, and reliability that you desire. A monitoring system that offers in-depth metrics across your Cassandra environment can transform your operations, ensuring optimal operations of your nodes and clusters.