How metric monitoring increases server uptime?
Everyone despises waiting for an application to load—or when an application fails to load. And if this occurs with your application, you will lose not only business but also brand value. Most applications are now available online. As a result, servers play an important role in keeping apps operating.
Server performance is directly related to application performance. As a result, monitoring and improving server performance is critical. There are various aspects to server performance. This post will look at various metrics that help analyze server performance and how we may enhance them. Then we’ll talk about how crucial server performance monitoring is and how to get started.
A measure of a server’s performance, in general, is called server performance. Yet what constitutes “well”? Every server is created, set up, and used for a certain purpose. For instance, mail servers are used to manage and distribute emails, and database servers are in charge of storing, processing, and interacting with data, and so forth. When a server delivers the requested service at the requested time, it is said to be operating effectively.
The measuring of server performance combines various parameters. You must first measure various server performance metrics before judgment regarding a server’s performance. Let’s now examine some of the most crucial server performance metrics and discuss ways to enhance them.
What are metrics, monitoring, and alerting?
A monitoring system’s foundation comprises the interconnected ideas of metrics, monitoring, and alerting. They can assist you in understanding use or behavioral trends and the effects of your changes by giving you visibility into the state of your systems. These systems can alert an operator to see if the metrics are outside the expected ranges and can help surface information to find potential causes.
Why do we need to collect metrics, and what are they?
Metrics are the unedited measurements of resource consumption or activity that can be seen and gathered across your systems. These could be operating system-provided low-level use statistics or higher-level data linked to a component’s precise functionality or task, such as requests fulfilled per second or participation in a pool of web servers. Other metrics are given as a rate that reflects the “busyness” of a component. Some metrics are presented in proportion to a total capacity.
The metrics that your operating system has already made available to reflect underlying physical resources are frequently the simplest to start with. Disk space, CPU load, swap utilization, and other statistics are already available, have instant value, and can be sent to a monitoring system with little further effort. Numerous web servers, database servers, and other pieces of software also have independent metrics that can be forwarded.
You might need to add code or interfaces to other components, particularly your apps, to expose the metrics that are important to you. Adding instrumentation to your services is another name for gathering and making available metrics.
Metrics are helpful because they shed light on the operation and condition of your systems, particularly when they are studied collectively. They are the essential components that your monitoring system uses to provide a comprehensive picture of your surroundings, automate reactions to changes, and notify people as necessary. Metrics are the fundamental quantities used to analyze historical patterns, compare various variables, and track changes in output, consumption, or mistake rates.
Server Performance Metrics
The number of requests a server can handle in a specific period is known as throughput. A second is typically used as the unit of time in throughput calculations. But depending on the use case, this may change. The throughput of a server is 100, for instance, if it handles 100 requests in a second. It might, however, occasionally be unable to determine throughput every second. You can utilize average throughput in these circumstances. The ratio of the total number of requests processed over some time is known as average throughput.
The average throughput would be 30,000 requests/10 minutes, or 50 requests per second if 30,000 requests were processed in 10 minutes.
By lowering latency, throughput can be improved. Network delay is one of the most prevalent types of latency that reduces throughput. It would help if you investigated the root of the high delay. Hardware, memory, routing, etc., could all be involved. The moment the problem generating the excessive delay is resolved, throughput will rise naturally.
What Does Server CPU Usage Mean?
The system has a task for everything that occurs on the server. This task is divided into processes that the server runs. Different processes can have varying levels of complexity and varying completion times. And as a result, the CPU needs some time to complete the task. In other words, the procedure is being carried out via the CPU. The percentage of time the CPU is used to execute tasks is known as CPU use.
CPU utilization is the duration of time that the CPU is in use. Typically, CPU consumption is calculated as a percentage. As a result, CPU consumption can be described as the proportion of time the CPU is employed to fulfill its tasks.
The following list includes some typical causes of excessive CPU usage:
processes that need a lot of CPU power
Some programs demand a lot of CPU power. The CPU use will undoubtedly increase if you try to run a high-end video game on a PC with poor specifications. Similarly, several processes may need a lot of CPU power to function. One of the causes could be one of these processes or a group of processes that collectively require a lot of CPU. High CPU consumption on servers might result from running several services to keep the server operating, simulations, etc.
System processes and application processes are the two main divisions of processes. The processes required to keep your system operating are known as system processes. Application processes are the ones you’d employ for a particular objective. These processes use up CPU resources when they continue to run in the background.
Even after the application window is closed, numerous application processes continue to operate in the background. This is less likely to occur on a server because they are regularly maintained and cleaned to ensure that they include only the processes they require, but it is still conceivable.
Malware (Malicious Software) is a term for programs used by bad actors to attack your system or take unauthorized actions. Malware doesn’t use many CPU resources at first to hide, but after it starts acting maliciously, it uses a lot of CPU. The malware started moving all sensitive data from the server to cloud storage one day after it had been introduced into the server a week earlier, according to the incident I saw. Therefore, this malware didn’t consume much CPU power while configuring itself and locating crucial data. However, once it had discovered everything it required, data transfer caused a significant increase in CPU consumption.
Additionally, the following are some typical techniques for optimizing CPU usage:
- Start the server again. This ends the majority of pointless processes.
- Find unneeded startup and background processes, and halt or disable them.
- Protect yourself from malware.
Why Should You Monitor Server CPU Usage?
High-level tasks a server may need to execute include tasks from the user and system. When a user requests a service or data from the server, it is the user’s job. Let’s say you use YouTube to search. The videos related to your search must be fetched by YouTube’s server, which must then provide in response to your request. CPU time is used in this data transmission.
A server’s duties extend beyond simply serving requests from users. The operating system and web services are being executed on its CPU. However, servers can also be used to execute some scripts that process data. Ansible playbook execution is a typical illustration. These playbooks can carry out actions even when the user is not present.
Why should you monitor Server memory usage?
Memory usage is another important and useful server uptime metric.
Keep in mind that if the server’s memory usage goes up for some reason and you don’t notice it, the server may stop working, and the services may stop.
Setting up and managing production infrastructure requires collecting metrics, monitoring tools, and configuring alarms. Knowing what is going on in your systems, what resources want attention, and what is causing slowness or outage is vital information. Even though developing and implementing a monitoring system may be challenging, it is an investment that may help your team prioritize their work, hand over control to an automated system, and understand how your infrastructure and software impact your stability and performance.
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