How Synthetic Monitoring eliminates eye-on-glass Monitoring
What Exactly is Synthetic Monitoring?
Synthetic monitoring is a type of monitoring that applies user-mimicked actions to test the availability and performance of an application. It is an advanced monitoring approach to ensure the functionality, reliability, and stability of applications, as it allows organizations to proactively identify and fix issues before they affect real users.
Still confused? Let me simplify this even further…
When using applications, users may perform different actions as per their needs. Using synthetic monitoring, we can simulate similar user actions with a system. The data generated from the simulated actions or transactions are then analyzed to evaluate how the system behaves. For example, synthetic monitoring could be used to determine whether a website achieves desired page load, response time, and uptime. Further, it can be used to simulate user traffic to test the availability and performance of web-based applications, websites, and servers
So what are some of the questions addressed by synthetic monitoring?
- How is the application performing at this moment?
• Is the application currently up?
• If there is a latency or failure, where exactly is it?
• Are transactions working fine?
• Are the expected functionalities of the applications working fine?
• Are the third-party components still operating?
How does Synthetic Monitoring work?
Usually, the working of synthetic monitoring can be explained using the following steps:
• Support Engineers or DevOps Engineers or SREs write automation scripts that issue requests to a website, application, or system
• The scripts are executed to simulate user actions or transactions
• Monitoring software collects data about the transactions
• The data collected by synthetic monitoring tools are analyzed to assess whether the system meets performance or availability requirements
Synthetic monitoring can also be performed manually by triggering transactions or performing user actions. However, that approach is difficult to scale and requires time and effort.
Synthetic monitoring in AIOPS
AIOps, or artificial intelligence for IT operations, is a set of technologies and practices that use machine learning, artificial intelligence, and data analytics to improve the management and monitoring of IT systems. In an AIOps environment, synthetic monitoring data can be combined with other types of data, such as log data and real user monitoring data, to provide a more comprehensive view of the health and performance of IT systems. This data can then be used to automate various IT operations tasks, such as incident management, problem resolution, and capacity planning.
Let us move beyond theory by using an example
A leading FMCG company called Aqua Purifier is a multi-national organization into manufactures and distributes water purifiers. They have a home-grown web application called “Aquantory” hosted in the AWS cloud. Aquantory is used to control, store, and keep track of inventory items. Let’s consider a use case where the Sales Manager wanted to view the available inventory of the “UV Water Purifier” products. The Sales Manager would perform the following tasks:
1. Login to Aquantory — Lands into the Home page
2. Clicks the Inventory menu — Takes him to the Inventory screen
3. Clicks the Product Category and select “UV Water Purifier”. Then clicks the “Show Inventory” button — New screen loads with the list of products in the “UV Water Purifier” category and their respective inventory details
4. Clicks download report — Inventory excel sheet gets downloaded on his desktop
With Synthetic monitoring, all the above steps can be automated via scripts and the system will be able to collect the data to validate the functionality and performance of each step. Thus the manual effort of validating the entire flow at regular intervals is eliminated and the Ops team will be notified even before the Sales manager reports an issue.
The above transaction has an issue while loading the inventory, which notifies the support engineer that the “View Inventory” functionality has an issue. At each step, the response time is captured to help the engineer observe the user experience side of things and optimize wherever required.
In Conclusion:
Synthetic monitoring is an important component of any AIOps platform, as it helps a support team to proactively identify and fix issues leading to improved reliability and stability. Thus, synthetic monitoring acts as the first line of defense, reduces downtime, and also eliminates eye-on-glass monitoring.
