In this log management guide, we will cover all the aspects of log management and talk about the benefits of using logging tools to improve security, troubleshoot issues, and monitor your system.
What Is Log Management?
Log management is a popular topic not only among system administrators and DevOps but also among developers. This is because the use of log management is widespread across many IT segments and job roles, and we will discuss why and how. So, what exactly falls under log management?
According to Wikipedia, we can divide log management into six segments:
● Log collection
● Centralized log aggregation
● Long-term log storage and retention
● Log rotation
● Log analysis
● Log search and reporting
This log management guide will go through each part of the log management process and explain it in more detail.
The first step in log management is to determine how to collect log data and where to store it. Your logs are aggregating data from different parts of the IT environment: operating system, firewalls, servers, switches, routers, etc. When it comes to storage, security systems such as firewalls and intrusion detection systems are the most demanding in terms of data volume they produce. Those systems typically generate dozens of EPS (events per second), which calls for a log collector that can handle the corresponding amount of logs.
If you use logging tools for log collection, you will be able to configure what kind of information you want to collect. The best practice is to customize each device’s log collection settings to leave out redundant data and ensure that you gather all relevant information. This is the minimalist approach that improves performance and efficiency. The other way to approach log collection is to go with a maximalist strategy and collect every possible piece of information so it could later be sorted and analyzed by a log management tool. There are many downsides to this approach, but they can be narrowed down to two: cost and efficiency. It costs a lot to store a large amount of data, and you will also need more workforce to perform this task. When talking about efficiency, having extremely large data sets stored online will reduce overall performance.
Centralized Log Aggregation
Centralized log aggregation is the process of aggregating all logs in one place, no matter their source. As mentioned before, the volume of data is one of the greatest challenges in this process, but there are other major issues to consider. For example, there is the veracity issue. Like any gathered information, log data may not be accurate. Even if your log management system can handle large volumes of data, what matters is how fast this data is generated. Logging tools should be able to keep up with this speed, which is why the EPS of a tool is something you should consider when choosing one.
Finally, there is no single unified format logs come in, which poses a challenge when aggregating logs from various sources. The process of normalization takes all received logs and transforms them into a common output so the information within logs can be analyzed more easily.
Long-term Log Storage and Retention
The next step in log management is long-term log storage and retention. The main question to ask in this step is how long do you need to store logs for. While it would be the easiest to store logs for an unlimited period of time so you could retrieve old data if you needed to, storing this much data would be too costly, the safest way to go about this is to follow industry’s best practices and regulations, storing log data for at least one year in case there is a need for investigation.
When storing logs, you can choose to store it in a brick and mortar storage by backing up data physically on tape or discs or to store it in the cloud. This decision often comes along with a company’s decision to undergo a digital transformation and migrate its resources online. There is an interesting article by Gunter Ollmann that discusses log retention in cloud SIEMS and the future of security operations.
Log rotation helps address problems in the previous step by automatically renaming, resizing, moving, or deleting log files that are too large or too old. You can choose a time interval after which the log will be deleted, compressed to save space, or emailed to another location. This way, new storage space opens up for more recent log files. If you are already using our product or want to know how log rotation is performed in Graylog, here is the guide to log indexing and rotation for optimized archival in Graylog.
Log analysis is arguably one of the most important parts of log management because collecting and storing log data doesn’t make any sense if you are not to make use of it. Logging tools automate and simplify the process of log data analysis, providing advanced ways to present your findings. Analytics reporting uses charts, plots, and other visuals to emphasize the correlations and similarities between events and data, making it easier to detect issues and track down their causes.
The top use cases for log analysis include compliance, security, troubleshooting, and performance improvement, but this is just a portion of what log analysis can be used for. We are going to discuss some of these aspects in more detail later on.
Log Search and Reporting
Logging tools facilitate log search and reporting by having a centralized aggregating approach and advanced search options. Taken into account how large log files can be, it is not hard to understand why search features have a huge impact on log management quality. Advanced search lets you look into both structured and unstructured logs and gather information about certain events that help determine the root cause. Logging tools come equipped with the means for data mining, digging through volumes of log data to discover patterns that would remain hidden otherwise. This improves log reporting, which is the final summary of the conducted search and analysis, providing numbers and visual attributes that tell the story about your log data. This is especially useful if you have to present your findings to someone who doesn’t have a technical background and you want them to understand the importance of the data fully.
Why Log Management?
Why is log management important? There are many advantages to using a systematic approach to your logs, and these are some of the most important ones:
● Unified storage
● System monitoring and alerts
● Improved security
● Better troubleshooting
● Log file parsing
● Data analytics
One of the main advantages of log management lies in unified storage, which we discussed when we talked about centralized log aggregation. Having all logs in one place makes any analysis much simpler, but the true advantage of unified storage is enhancing your system security. Since this is the field where the time between when a threat first occurs and when you take action can make all the difference, storing important log information together speeds up the whole process. Centralized logging also means having standardized log data, which also saves time when looking for information across logs from different sources.
System Monitoring and Alerts
Logging tools provide customizable real-time alerts that enable you to react as soon as a problem occurs, which is essential in cases of security breach and intrusion where every second can mean more damage to the system by the attacker. This means shifting your SIEM from reactive to proactive and leveling up your threat-hunting abilities.
Monitoring settings can be adjusted to track a custom selection of events, which is useful for security and troubleshooting. You can change these filters to get notified only about high priority events so you don’t get bombarded with notifications, emails, and/or text messages. This is another benefit of log management monitoring - there are several channels for messaging you can choose from to make sure you don’t miss any important events.
For more information on system monitoring and how to get the best out of it, you can read about the benefits of monitoring event logs.
Thanks to the 24/7 real-time system monitoring and alerts, your IT environment will be better secured against hacker attacks. By carefully choosing which events to log, you can tighten up security even more. For instance, The Windows Security Log is amongst hackers’ favorite attack targets because they try to cover their tracks and hide their presence by altering this log. By logging and monitoring login and logout events within the Windows Security Log, you can detect any suspicious behavior before it is too late.
To get the most out of log management in terms of securing your system, make sure to check out these security logging best practices.
Log management gives you better control of your IT environment and a better insight into the processes that take place on your machines and peripherals. One of the most common uses of event logs for detecting problems is for network troubleshooting. Real-time alerts significantly reduce the time needed to detect and address a problem, but the real power of logging tools lies in log analytics. A large amount of data stored in logs is subject to customized search and analysis, which makes it easier to recreate the timeline of problematic events, discover connections with other events, and pinpoint the source of the issue.
Log File Parsing
Parsing is the process of dividing data into smaller pieces of information for easier storage and manipulation. Since every log file consists of various pieces of data, the goal of log file parsing is to recognize similar structures and allow for grouping the information by those structures. For instance, identifying all timestamps within a log file and gathering logs from a certain timeframe, or tracking one user’s activity only.
With the rise of data science, companies are starting to understand that the data they store may contain valuable information. Data analytics encompasses several processes such as cleansing and transforming data with the goal to create a data model that can predict certain behavior, help make business decisions, or provide new information. For example, analyzing customer logs of a business could predict certain behavior (for example: customers are more likely to make a purchase on Friday), help make a business decision (deciding to target a different type of audience in the next marketing campaign), or provide new information (for example: most buyers are females aged 20-40).
If you are interested in a more in-depth overview of data analytics, here is a great article on log analysis use cases, best practices, and more.
How Are Log Management Tools Used?
While it is possible to perform all aforementioned steps of log management on one’s own, it is a time-consuming process that requires a lot of customization and planning. Handling log management without logging tools is similar to programming from scratch instead of utilizing existing libraries and scripts - doable, but wasteful in terms of time and resources. On the other hand, if you truly have a need for logging without tools, there are some good tutorials out there, such as the in-depth Python logging tutorial.
Log management tools encompass all parts of the log management process allowing you to have control of the way it is performed. Since no two systems are 100% alike, every log management tool lets you choose the way you want to store your log data. One of the greatest advantages is the advanced level of analytics and visualization that gives users a better insight into their data.