Cassandra Performance Monitoring Tool

Improve database performance through proactive Cassandra monitoring

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Monitor Cassandra DBs

Track Key Metrics

View Performance Metrics

Set Alerts

Unify Dashboards

Proactively monitor your Cassandra database

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Cassandra monitoring requires a proactive approach to avoid performance issues, including bottlenecks and slowdowns, which could affect end users. But with Cassandra signature node replication, it can be difficult to pinpoint and troubleshoot issues. To ensure functionality and high availability at scale, you need a robust Cassandra monitoring tool to address slowdowns and head off cluster failure.

SolarWinds^® Server & Application Monitor (SAM) is designed to help you drill down into individual Cassandra nodes to find and resolve the root causes of performance issues.

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Fully functional for 30 days

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Track essential Cassandra performance metrics

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Effective Cassandra monitoring revolves around continuously monitoring a wide range of Cassandra performance metrics. These metrics measure different elements of the database and can help reveal issues that could impact overall performance and slowdowns.

SolarWinds Server & Application Monitor keeps track of important Cassandra performance metrics, including Cassandra JMX metrics, by aggregating them and creating clear visual representations, so DBAs can get to the bottom of any potential Cassandra database problems fast. SAM is built to monitor metrics tied to:

Throughput
Latency
Disk usage
Garbage collection
Errors and overruns

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Easily view key Cassandra performance metrics

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Cassandra monitoring metrics are only useful if you can make sense of them. SolarWinds SAM can help you view and more easily understand key Cassandra metrics. Using SAM, you can set the parameters you need to monitor a Cassandra server (even if installed on a Linux or Unix system), check system health by viewing network statistics and node status on commands and responses to help you ensure monitored components are functioning as expected, and monitor crucial Cassandra server metrics like latency, disk usage, thread pool tasks, and key and row cache values.

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Fully functional for 30 days

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Set intelligent alerts to stay on top of critical issues

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SolarWinds Server & Application Monitor offers robust, customizable monitoring and alerting of Cassandra databases. Never miss an action item that could affect end users or degrade system health. Head off Cassandra performance problems with alerts on relevant metrics, including ongoing hint activity or increased latency, before issues compound. If you want to reduce alert fatigue, SAM makes it easier to focus on the metrics that matter to you and set critical alerts for only high-level cluster failures.

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Fully functional for 30 days

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Unify your Cassandra monitoring dashboards

DBAs have a lot on their plates without needing to navigate different dashboards for different servers. That’s why SolarWinds SAM makes it easy to track performance across virtual and physical servers, by using the agentless, scalable architecture available in SAM’s Cassandra monitoring tools. With SAM, you can use a single tool to monitor Cassandra performance alongside other vendor solutions for a centralized view to help bring more admin tasks under one roof.

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Get More on Cassandra Monitoring

Do you find yourself asking…

What is Apache Cassandra?
Why are Cassandra monitoring tools important?
How to monitor Cassandra
How to check Cassandra performance metrics
How does the Cassandra monitoring tool in SAM work?

Apache Cassandra is an open-source, distributed database system known for its fault tolerance and scalability. It first began as a project at big IT corporations. Since then, Cassandra has transformed into a free Apache project and has matured into a widely adopted system.

While Cassandra can be used by any organization, it’s specifically built for organizations that regularly handle large volumes of data—including data spread over many commodity servers. In fact, Cassandra is designed to provide high levels of availability over a global distribution, enabling applications to write data to whatever node they want in a cluster. As a result, you often see Cassandra being used in high-traffic cloud apps.

Cassandra is a NoSQL database. NoSQL (non-relational) databases usually store data in the JSON format and attributes are usually stored in separate documents. They’re designed to manage unstructured data, and they can use horizontal scalability to manage large amounts of data.

The Cassandra architecture differs from some other popular databases. Its servers are arranged in a ring topology to give servers equal responsibility, as opposed to having certain servers in the cluster act as “primary” or “secondary.” Each server hosts replica copies of an application’s data, which means if one server goes down for whatever reason, another server can easily take over. Cassandra’s evenly distributed system means there’s no failover in a Cassandra cluster.

Because Cassandra is a Java application, it runs in a Java Virtual Machine (JVM). The result is Cassandra JMX metrics (Java Management Extensions) are often used to collect metrics during Cassandra monitoring.

For your Cassandra database to be able to serve your applications, it needs to be reliable and high performing. The best way to keep it this way is through Cassandra monitoring that keeps track of performance metrics tied to your Cassandra server.

When your database can’t receive or send requests efficiently and has a low-performing throughput, you’re more likely to see bottlenecks in your most critical applications. No amount of coding can keep your application running smoothly if your database itself isn’t performing up to par.

Key performance metrics to track through your Cassandra monitoring are:

Latency: Latency measures the amount of time it takes to fulfill a request. Read and write latency metrics can indicate developing problems or changes in usage that may result in needing to reoptimize your database to maintain performance. Consistency level and replication factor are particularly important to keep an eye on when it comes to latency.
Throughput: Throughput is one of the most important metrics in Cassandra monitoring. Track read and write requests to better understand cluster performance and how clients are engaging with the Cassandra database. When you understand how the database is being used, you are better equipped to make targeted optimizations for database performance.
Disk Usage: By monitoring disk usage, DBAs can get insight into how much space your database is using on each node in a cluster. They can then use this information to help ensure efficient disk space use and to help prevent resource shortages.
Errors and Overruns: Tracking error count can help DBAs stay on top of critical situations that require action, such as if a Cassandra cluster suddenly loses the ability to handle the incoming flow of requests and queries. Errors vary in severity, but it’s worth focusing on timeout exceptions and unavailable exceptions.
Garbage Collection: Because Cassandra is Java-based, the database uses standard Java garbage collection processes to free up memory. DBAs need to monitor the latency of garbage collection processes to make sure you always have enough memory.

When it comes to checking any of these metrics, the best strategy is to use a Cassandra performance monitoring tool like SolarWinds SAM, which checks the metrics for you and gives you the information you need in a clear, aggregated form.

Apache Cassandra is an open-source, distributed database system known for its fault tolerance and scalability. It first began as a project at big IT corporations. Since then, Cassandra has transformed into a free Apache project and has matured into a widely adopted system.
While Cassandra can be used by any organization, it’s specifically built for organizations that regularly handle large volumes of data—including data spread over many commodity servers. In fact, Cassandra is designed to provide high levels of availability over a global distribution, enabling applications to write data to whatever node they want in a cluster. As a result, you often see Cassandra being used in high-traffic cloud apps.
Cassandra is a NoSQL database. NoSQL (non-relational) databases usually store data in the JSON format and attributes are usually stored in separate documents. They’re designed to manage unstructured data, and they can use horizontal scalability to manage large amounts of data.
The Cassandra architecture differs from some other popular databases. Its servers are arranged in a ring topology to give servers equal responsibility, as opposed to having certain servers in the cluster act as “primary” or “secondary.” Each server hosts replica copies of an application’s data, which means if one server goes down for whatever reason, another server can easily take over. Cassandra’s evenly distributed system means there’s no failover in a Cassandra cluster.
Because Cassandra is a Java application, it runs in a Java Virtual Machine (JVM). The result is Cassandra JMX metrics (Java Management Extensions) are often used to collect metrics during Cassandra monitoring.
Cassandra performance monitoring tools are important because the monitoring process is integral to maintaining your database performance. However, conducting Cassandra monitoring manually be challenging. These challenges include:
Specific architecture: Apache Cassandra’s identical-node architecture can make performance issue diagnosis tricky.
Unique metrics: Do you have sufficient insights into key metrics like latency, throughput, and error rates?
Scalable monitoring: At this scale, you need a robust Apache Cassandra monitoring tool to conduct wide-view, accurate assessments.
While Cassandra databases have many advantages when it comes to their ability to store and process large amounts of data, Cassandra clusters with a lot of nodes can increase the complexity of your data infrastructure. It is only through comprehensive Cassandra monitoring you can maintain optimal performance and mitigate potential bottlenecks or capacity issues.
Locating and mitigating those bottlenecks, slowdowns, critical resource limitations, and more depends on continuously monitoring Cassandra performance metrics. Even though built-in Cassandra features can take care of some elements of monitoring, Cassandra tools are still necessary to ensure you get the level of continuous and in-depth monitoring you need to optimize your database health and performance.
Cassandra monitoring tools are important because they can go beyond simply collecting and monitoring the Cassandra JMX metrics to collect even more critical Cassandra performance metrics and aggregate them to give database administrators (DBAs) the information they need when they need it.
For your Cassandra database to be able to serve your applications, it needs to be reliable and high performing. The best way to keep it this way is through Cassandra monitoring that keeps track of performance metrics tied to your Cassandra server.
When your database can’t receive or send requests efficiently and has a low-performing throughput, you’re more likely to see bottlenecks in your most critical applications. No amount of coding can keep your application running smoothly if your database itself isn’t performing up to par.
Key performance metrics to track through your Cassandra monitoring are:
Latency: Latency measures the amount of time it takes to fulfill a request. Read and write latency metrics can indicate developing problems or changes in usage that may result in needing to reoptimize your database to maintain performance. Consistency level and replication factor are particularly important to keep an eye on when it comes to latency.
Throughput: Throughput is one of the most important metrics in Cassandra monitoring. Track read and write requests to better understand cluster performance and how clients are engaging with the Cassandra database. When you understand how the database is being used, you are better equipped to make targeted optimizations for database performance.
Disk Usage: By monitoring disk usage, DBAs can get insight into how much space your database is using on each node in a cluster. They can then use this information to help ensure efficient disk space use and to help prevent resource shortages.
Errors and Overruns: Tracking error count can help DBAs stay on top of critical situations that require action, such as if a Cassandra cluster suddenly loses the ability to handle the incoming flow of requests and queries. Errors vary in severity, but it’s worth focusing on timeout exceptions and unavailable exceptions.
Garbage Collection: Because Cassandra is Java-based, the database uses standard Java garbage collection processes to free up memory. DBAs need to monitor the latency of garbage collection processes to make sure you always have enough memory.
When it comes to checking any of these metrics, the best strategy is to use a Cassandra performance monitoring tool like SolarWinds SAM, which checks the metrics for you and gives you the information you need in a clear, aggregated form.

Get the insights you need for effective Cassandra monitoring

Server & Application Monitor

Proactively track key performance metrics.
Set alerts for thresholds appropriate to your Cassandra server.
Avoid damaging slowdowns and bottlenecks.

Starts at

SAM, an Orion module, is built on the SolarWinds Platform

Download Free Trial Email Link to Trial

Fully functional for 30 days

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