Logging vs. Monitoring: How They Differ and Why You Need Both

Are you torn between ‘Monitoring’ and 'Logging'? If you are responsible for deploying and maintaining an application, these are two basic approaches to ensuring that your application consistently meets performance and availability requirements. On the one hand, you have application performance management, also known as APM or 'application performance monitoring'. On the other hand, there is log analysis and management, often referred to as 'logging'. You may be tempted to believe that you can rely on only one of these methods to maintain the health and performance of your application. However, this is not so. To understand why, let's look at the differences and similarities between AWS cloud monitoring and logging, and why it is necessary to have both in place to achieve the highest level of visibility.

What is logging and why is it important?

Logging refers to the systematic management of log data generated by applications and infrastructure.

Logging applications can be divided into various smaller tasks, such as:

• Log collection or log shipping:- This step involves collecting log data from various sources and transferring it to a central repository.
• Log Retention and Archiving:- This involves defining and implementing an appropriate strategy to preserve log files over an extended period of time while adhering to deletion policies after the retention period ends.
• Log data quality control:- This phase in- volves fixing issues such as missing entries, inconsistent timestamps, redundant logs, and other data quality concerns to ensure the reliability of the log data.
• Security and privacy compliance:- It is important to ensure the security and privacy of logs, especially when they contain sensitive information subject to regulations such as GDPR (General Data Protection Regulation).
• Log enrichment:- Log enrichment involves enhancing log data with additional relevant information. For example, this may include adding geographic data based on IP addresses to make logs more informative.
• Log Analysis:- Log analysis is the process of deriving meaningful insights from log data using specialized log analyzers. Although some may consider it more closely related to monitoring than logging, it plays an important role in understanding system behavior and identifying issues.

The scope of your logging activities will vary depending on several factors. These factors include the amount of logs you see, the geographic dispersion of your infrastructure (highly dispersed infrastructure creates challenges in collecting logs, such as hybrid setups where log data is stored across on-premises and cloud-based environments) and specific types of logs. Not all services generate the same amount of log data; For example, a cloud-based serverless computing environment generates minimal log data, whereas an on-premises data center typically generates a substantial amount of data.

What is monitoring and why is it important?

Monitoring is the practice of ensuring that an application remains accessible and responsive to user requests within an acceptable time frame. It involves both art and science, covering various aspects of application performance. Although monitoring can have broad purposes such as optimizing code and reducing infrastructure costs.

Monitoring tools play a vital role in achieving these objectives by continuously keeping an eye on key metrics. These metrics include whether an application or service is running, its response time, and resource usage such as memory, network bandwidth, and CPU usage.

Monitoring employs different techniques and strategies depending on the equipment and facilities in use. Some of these approaches include:

• Real User Monitoring (RUM):- RUM relies on real user data to evaluate the health of an application. It examines users' interactions with a website or application, analyzing factors such as page load time, AJAX requests, Apdex scores, and frontend application crashes. RUM is also known as end-user experience monitoring (EUM) or digital experience monitoring (DEM) and is a key component of application performance monitoring.
• Synthetic monitoring:- This method involves using scripted interactions to simulate user actions and monitor application behavior.
• Network Monitoring:- Network monitoring assesses the availability and performance of applications by analyzing network traffic.
• Distributed Tracing:- Distributed tracing focuses on monitoring the execution of an application at the code level rather than just the underlying infrastructure.

Considering the diversity of monitoring techniques available, it is best to view monitoring as a comprehensive strategy for managing application performance and availability rather than a specific method.

Logging vs. Monitoring

So then, what is the difference between logging and monitoring?

Logging and monitoring have different roles, each serving a unique purpose in managing applications. Monitoring primarily focuses on overseeing application performance, while logging revolves around handling the data contained within the logs. This distinction is important because it ensures that when you need to troubleshoot or optimize your applications, you have the tools and comprehensive data needed to gain an accurate understanding of the availability and performance of your infrastructure and your applications.

As a result, logging and monitoring are closely interconnected as log data serves as an important data source for application monitoring. Although logs are not the exclusive source of valuable application metrics for your monitoring tools (other data such as stack traces can also be valuable), logs generated by applications, servers, network infrastructure, and more provide detailed insight into an application's performance. 

Although you may use different tools for these tasks, having both logging and monitoring capabilities within a single platform streamlines the process of addressing critical issues, making it faster and more straightforward. One such tool that provides this holistic functionality is BigBell. It supports both logging and monitoring, giving you the comprehensive capabilities you need for efficient management. It is important to note that logging serves a broader purpose beyond supporting performance monitoring.

In addition to troubleshooting and performance monitoring, well-maintained logs serve other purposes such as:

• Increase response to data breaches and resolve security incidents
• Ensure adherence to security policies, regulations and compliance audits
• Get information about online user behavior

To meet security and compliance requirements, you may consider establishing an organization-wide or department-specific cloud monitoring and logging policy. These policies streamline decision-making about what to monitor, where to store logs, retention periods, storage for auditing purposes, encryption, and more.

Conclusion: 

It is important to emphasize the importance of integrating both logging and monitoring into your system management practices. Without properly managed logs, which provide a comprehensive dataset for application monitoring tools, you will face a significant gap in your monitoring capabilities. Furthermore, this deficiency can lead to a number of issues beyond the scope of application performance monitoring, including potential non-compliance due to ineffective log data management. Conversely, in the absence of AWS cloud monitoring, your log data becomes a puzzle without a solution. You will not have the ability to understand how your application is working, nor will you have the means to efficiently diagnose and fix recurring problems.

If you're looking for an integrated solution for both monitoring and logging, consider exploring Bigbell, our cloud-based monitoring tool. BigBell excels at monitoring logs and correlating them with performance metrics, ensuring optimal application performance and minimizing downtime.