Today, it’s perfectly normal for businesses to continuously monitor software applications and IT infrastructure to ensure uninterrupted customer service.
Active and passive monitoring are the two popular methods enterprises use for infrastructure and application performance monitoring (APM). As the names indicate, these two approaches to monitoring are very different.
This article explains the differences between active and passive monitoring methods, along with their use cases, data volumes, and control over the data. Additionally, we’ll look at the advantages and drawbacks of these two methods.
This article is comprehensive, so to help you out, I’ve summed up the major points here. Keep reading after the table to get more details.
Feature |
Active Monitoring |
Passive Monitoring |
Nature of data used |
Uses synthetic data |
Uses real data |
Data volume |
Smaller data volume is used |
Larger data volume is used |
Use cases |
QoS testing, issue identification, evaluating new hardware, benchmarking performance. |
Infrastructure health and status monitoring, usage pattern identification, providing personalized user experiences, IDS. |
Your control over the data |
Can control data such as how many traffic packets, size, period, etc. |
Less control over the data |
Issue identification |
Proactive |
Reactive |
Storage requirements |
Fewer storage requirements due to smaller data volume |
Higher and scalable storage devices are required |
Compute requirements |
Less compute intensive because of lower data volume and complexity |
Since the data volume is high and complex, data processing and analysis can be compute-intensive |
Privacy issues |
No privacy issues as synthetic data is used |
Need to address privacy issues related to real data captures |
Data complexity |
Synthetically generated data is less complex than passive monitoring |
Various types of data are captured. Hence, the complexity is higher. |
Nature of issues That can be identified |
Cannot identify intermittent issues as tests are carried out over a specific period. |
Intermittent and complex problems can be identified. |
Active monitoring refers to proactively monitoring the performance of:
Active monitoring will be based on the results of synthetically generated data. For example, during active network monitoring, test network packets are ingested to simulate the actual network behavior. This helps observe the measurements of various performance parameters. During the process, extra traffic is created to predict the potential performance.
Synthetic journeys are created through active monitoring of applications and services. These journeys use test accounts to mimic critical user journeys throughout the application. Active monitoring is also called ‘synthetic monitoring', as it does not use real data.
(Related reading: network monitoring, network configuration & baselining network behavior using ML.)
In contrast, passive monitoring uses real data to measure and analyze the performance of networks, applications, and infrastructure. Using special devices and software, passive monitoring provides a holistic and in-depth view of real performance.
For example, in passive network monitoring:
Unlike active monitoring, passive monitoring uses a large volume of data and does not add additional data to the normal network flow.
(Learn about real user monitoring, aka RUM, or take a free tour of Splunk RUM.)
There are several use cases for the two methods based on the nature of the data used and the analysis approach. We will discuss them next.
Active monitoring is best suited in the following scenarios, as it uses a predictive approach.
Passive monitoring is best suited for the following scenarios, as it uses actual data to monitor performance.
Both methods utilize user data to continuously monitor the system under investigation. However, the data volume and the control over the data significantly differ in each method.
Lower data requirements and usage. The data used in active monitoring is comparably lower than passive monitoring, as it involves specific and targeted tests during a specific period. Hence, data is more focused and related to specific performance metrics being tested, such as:
Thus, you can tweak the amount and various aspects of the traffic you send in. You only need a little of it to get significant measurements.
Environmental control. Another factor is that active monitoring offers more control over the generating data and the simulation environment. For example, you can determine the period of execution, if it is network monitoring, the packet size, the types, and so on.
In contrast, passive monitoring continuously captures data, producing more data for analysis. In fact, data can be collected over a 24/7 period via passive monitoring. This data can be generated from various sources, commonly:
All this added data means that storage requirements are higher, and any analysis can be more complex than active monitoring. Important to remember, with passive monitoring, you’ll have less control over the generated data than active monitoring.
Both methods bring several advantages for organizations.
Helps proactively identify underlying issues. Active monitoring simulates user journeys and network behaviors continuously, even before users use the system during usage times. Therefore, it helps identify problems before they impact real users. (In contrast passive monitoring is a reactive approach, as it identifies issues after they impact the real users.)
Eliminates privacy issues. Active monitoring does not use real data for analysis. Thus, there’s no concern over protecting user data privacy.
Can be used for load testing. IT teams can build standardized load testing scenarios to test the system performance under varying loads. It helps identify potential performance issues that cannot be identified using packet capture.
Provides detailed insights. Since passive monitoring uses so much real-time data, you can get very in-depth information on usage patterns. Mature organizations even feed that data into machine learning models for classification and clustering tasks with higher accuracy.
Identifies complex problems. Passive monitoring helps identify issues that happen intermittently, which would otherwise go undetected through active monitoring.
Costs less than active monitoring. Passive monitoring is easier to set up than active monitoring. No resources are required for synthetic traffic generation. Thus, it can be more cost-efficient, especially for large enterprises.
Identify security issues before they could occur. Large-scale real-time traffic analysis helps detect potential security breaches.
Despite the above advantages, both methods have cons. You must consider them when leveraging these methods.
As mentioned in this article, active and passive monitoring mainly differ from the data used for testing various performance metrics. Both approaches have different advantages over the others due to the nature of the data and the monitoring approach used. While there are several advantages, these approaches come with several cons, as described in the article. You may also need to consider them before incorporating these methods into your organization.
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This posting does not necessarily represent Splunk's position, strategies or opinion.
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