With accelerating digitization, business organizations are moving towards complex software systems. To ensure high availability, business organizations need to monitor the device’s performance regularly. Many businesses are shifting towards cloud architecture which is tougher to monitor. While customers may not care about which technology is used to provide services, their opinions will be shaped by how well the digital channels are performing.
If a service application is slow, customers can quickly shift to other digital platforms. There are many microservices provided by businesses via digital channels. Monitoring microservices with traditional tools is not feasible in this digital age. It is why CXOs should know the four golden signals of monitoring for monitoring complex software systems and business applications.
Understanding Golden Signals for Monitoring
The four golden signals for monitoring were first introduced by Google. Over the years, many business organizations adopted the four golden signals for better results. The four signals are traffic, latency, saturation, and errors respectively. Along with the four golden signals, there are two methods for monitoring. The two methods for monitoring with golden signals are listed below:
- USE (Utilization, Saturation, and Errors) is a monitoring method used for measuring the performance of any software system.
- RED (Rate, Errors, and Duration) is used by many business organizations for service monitoring. It focuses on increasing uptime and service availability.
Application performance monitoring is crucial for business organizations to ensure high service reliability. An SRE (Site Reliability Engineer) should also know about the golden signals to ensure high uptime of service applications.
What are the golden signals used for monitoring?
When a user visits a service application or website, it makes requests to the host server. The host server approves the request of the users that helps them in accessing the services via digital channels. Latency is defined as the time taken by the host server to approve the request of a real user. If latency is high, users may deviate to some other website or business application. For example, if your website is taking more time to load, users may get frustrated. Besides ensuring high service availability, one also must ensure the high performance of business applications or websites.
CXOs usually measure the average latency by considering all user requests. By doing so, you may not pay special attention to requests that are fulfilled in long durations. If 90% of requests are fulfilled quickly and, 10% are approved slowly, it can still hamper your service reliability. It is why a business organization should focus on high latency requests along with measuring average latency. Since legacy tools cannot measure the latency of all requests, business organizations are using AIOps for application performance monitoring. AIOps can handle the complexity of modern-day applications that are complex and higher in number.
Typically, one may think of traffic as the number of real site visitors. However, when talking about golden signals, traffic means the load users put on an application. All the users using an application are combined to measure the total load. There are many ways to measure the traffic on websites and service applications. For example, business organizations measure the HTTP requests per second to determine the load on the website. To fine-tune user experience, measuring the traffic is of utmost importance. Measuring traffic can let you know which applications/websites are working fine and which ones need work. Real-time user monitoring tools can help CXOs in measuring traffic for different software systems and service applications.
In layman’s terms, application performance monitoring is finding performance errors and fixing them before they affect the service availability. However, CXOs should know what exactly causes errors in the service applications. For example, if an HTTP request by the user returns ‘500 status’, it implies that there must be an internal service error. For each HTTP request, the right content should be returned to the user. If incorrect content is returned for an HTTP request, it can also be counted as an error. Errors should be identified in real-time and, AI for application monitoring is the only solution.
Saturation is defined as the percentage of an application or software system being used. For example, if the saturation of a web application is 100%, it implies the application is being used to its fullest. High saturation means performance degradation is likely to occur. 100% saturation can even result in device failure. Application performance monitoring tools should measure all metrics that can help you understand the state of your software systems and service applications.
Your saturation level should not be too high and too low. If your saturation level is less than 50%, it means you are spending much on applications that are not being used. Measuring the saturation is also important for slashing costs spent in running service applications and software systems. High observability can help a business organization know more about the saturation of web applications and software systems.
How AIOps Aids in Monitoring with Golden Signals?
Application performance monitoring has evolved over the years. It is hard to keep track of the golden signals due to the increased complexity of service applications. AIOps can help in determining real-time performance metrics via high-end data analytics. One can identify performance errors and saturation in real-time with AIOps.
IT teams can fix errors via the actionable insights offered by an AIOps based analytics platform. Not only you will boost service availability but also enhance the customer experience with AIOps. The best AIOps tools and products come with real-time service dashboards that help in tracking performance metrics. Incident management becomes easy with AIOps and, you can ensure high uptime of your business applications.
In a Nutshell
The global market of AIOps has already crossed the USD 12 billion mark in 2020. In the coming years, the AIOps industry will grow with a huge growth rate. It is time for business organizations to perform application performance monitoring with AIOps. Start using the golden signals for effective monitoring!