How to Calculate Peak EPS in QRadar with Writing Patterns Using
QRadar is a powerful security information and event management (SIEM) platform used by organizations to monitor and analyze their network traffic. One of the key metrics used to measure the performance of QRadar is the peak events per second (EPS) rate, which represents the maximum number of events that QRadar can process in a second. Calculating the peak EPS rate is important in optimizing your network security and ensuring that your QRadar system is running smoothly. In this guide, we’ll show you how to calculate the peak EPS rate in QRadar using writing patterns.
What are Writing Patterns?
Writing patterns are a way to optimize QRadar’s processing of events by reducing the number of false positives generated by rules. A writing pattern is a regular expression that matches a specific pattern of log data. By using writing patterns, you can create more specific and accurate rules that trigger only on relevant events, reducing the overall EPS rate.
Step 1: Identify Relevant Events
The first step in calculating the peak EPS rate in QRadar is to identify the events that are most relevant to your organization’s security. This will help you create more specific rules and writing patterns that filter out irrelevant events and reduce the overall EPS rate. You can start by analyzing your network traffic and identifying the types of events that are most common and relevant to your security posture.
Step 2: Create Writing Patterns
Once you have identified the most relevant events, you can start creating writing patterns that match those events. Writing patterns are created using regular expressions, which are a set of characters and symbols that define a pattern of text. For example, you could create a writing pattern that matches all login events from a specific IP address range.
Step 3: Test and Refine Writing Patterns
After creating your writing patterns, you should test them against your log data to ensure that they match the intended events and do not generate false positives. You can use the ‘Test Rule’ feature in QRadar to test your writing patterns against a sample of your log data. If your writing patterns are generating too many false positives, you should refine them to be more specific and accurate.
Step 4: Measure EPS Rate
Once you have refined your writing patterns and rules, you can measure the EPS rate in QRadar using the ‘Event Rate’ graph in the ‘System Activity’ dashboard. This graph shows the EPS rate over a specific time period, allowing you to identify the peak EPS rate. To calculate the peak EPS rate, you can use a simple calculator to find the highest point on the graph.
Step 5: Optimize Your Network Security
By using writing patterns and optimizing the peak EPS rate in QRadar, you can improve your network security by reducing the number of false positives and ensuring that your QRadar system is running smoothly. You can also use the information gathered from measuring the peak EPS rate to identify areas of your network that may be vulnerable and take steps to improve your security posture.
Conclusion
Calculating the peak EPS rate in QRadar with writing patterns is an important step in optimizing your network security. By identifying relevant events, creating accurate writing patterns, and measuring the EPS rate, you can improve your security posture and ensure that your QRadar system is running smoothly. Remember to test and refine your writing patterns to reduce the number of false positives and improve the accuracy of your rules. With these steps in mind, you can take your network security to the next level.
