Continuous monitoring is a technique that has made it possible for DevOps teams to monitor applications even when they are not looking at the monitors, mainly due to many tools that provide modern features for the observability process. This article will explain the concept of continuous monitoring, then explore three monitoring tools and their use cases.
Exploring Continuous Monitoring
The idea of monitoring applications is not new. Zabbix, one of the oldest monitoring systems, was released in 2001. One year later, Nagios was released. These applications, designed to monitor systems, infrastructure, and networks in Unix environments, are still being developed today.
Since the advent of Zabbix, numerous monitoring tools have emerged, capable of things that would have been seen as unimaginable 20 years ago. Some functionalities, such as pipeline integrations and security tools, enable alerts to help teams track the outcome of builds and vulnerabilities in real-time. And now, we can also apply machine learning to identify patterns in the logs and generate more intelligent and preventative alerts.
The evolution of software development goes hand-in-hand with the development of monitoring systems. New architectures and distributed systems require more detailed information about how applications work. Monitoring tools have evolved to support this demand by introducing resources that make it easier to monitor the status of applications, thereby making the work of DevOps teams less arduous.
What Can Be Monitored Continuously?
It is important to highlight what each monitoring tool can monitor before discussing the options in more detail. Your application is running somewhere – which could be a container, an image, or even directly on a local operating system. And the operation of this environment directly affects your application, making it essential to monitor the system, server, and infrastructure used to host the application.
It is also important to monitor data related to access to your application. Most of the time, network monitoring is fundamental to identifying the source of access and determining how the application responds to its requests.
Last but not least, there's application monitoring, which provides information about your application's performance, including errors, latency, logs, metrics, traces, and other features discussed. Let's look at three tools for continuous monitoring now that you know what to monitor.
Three Continuous Monitoring Tools to Try
Grafana
Grafana allows you to monitor your applications and infrastructure (including Docker, Kubernetes, VMWare, and more) with customizable dashboards. In addition, Grafana Labs has a list of plugins that enable you to scale observability and integrations that improve metrics, logs, and traces. Grafana is highly customizable and works with many data structures. You can even unify data from different places to achieve observability without linking to your database's sources.
It can integrate with other observability tools and you can use integrations with clouds like Amazon and Azure to monitor infrastructure costs. If you are looking for a solution for diversified applications that you will need to integrate with a set of other services, this may be an excellent option to try.
Sematext
This tool has features for infrastructure monitoring, log management, APM, and even real user monitoring functionality. The latter analyzes user session data to provide information that you can use to improve your application and the user experience.
Sematext also adds value by identifying what affects your Apdex score, detecting anomalies, and setting up alerts for page load times to keep developers aware of what needs to be improved to boost customer satisfaction. If you monitor the website and use A/B testing, this can be a powerful feature.
ChaosSearch
This continuous monitoring tool functions like a data indexing tool that groups multiple data sources to form an environment (much like a data lake) where you can look up information about the application. In addition to application monitoring, it improves security, log, and SQL analytics by applying machine learning to work with large amounts of data without increasing response time.
ChaosSearch automatically detects data schemata and does not require the data to be transformed before analysis, providing a modern approach to working with data without worrying about keeping it available so that it can be searched and examined for insights. If you are looking for a new way to scrutinize your application, or if your application handles large amounts of data, you should give this tool a shot.
Conclusion
The list of continuous monitoring tools on the market is extensive, and choosing one is not an easy task. To find the one that's right for you, decide which three (or so) application features are the most important to monitor. Then, start looking for monitoring tools that address those areas. Doing so will help you narrow down the list of tools to try out.
Be sure also to consider the cost. Setting a monitoring budget will help with your decision, but try not to use cost as the deciding factor. Most tools offer a free trial, so take the time to test them out and find the monitoring tool that best suits your needs.
