Data logging is always accompanied by storage problems. So, how can businesses optimize costs and retain access to the logs at the same time? Let’s fill in the gaps on the importance of log data analysis and the benefits it can provide.

A log stores information about the state of the application (program). Logs can exist in the form of records in a regular text file, records in a database, records on a remote web service, and even emails to a specific address about certain states of application. What specific information needs to be recorded is determined by the developers. This can be a daily monitoring report, so that errors are responded to and eliminated as quickly as possible.

Log files are raw data that needs to be processed. The quality of processing determines the quality of statistics. The site’s log files contain all the necessary information about people who visit the site or how the site responds to their actions.

The choice of log analysis tools depends on the complexity of the project. If you are creating a simple three-page business card site or console application for your own needs on your local computer, then creating a complex logging system can take longer than creating the project itself. In such cases, it would make sense to log only error messages or reasons for site crashes. But if you are working on a complex project in a team with other developers, then competent storage of data logs is a must.

Logging analysis provides multiple possibilities for any business. Here are some important facts you need to remember:

• Logging data is the heart and soul of SIEM (security information and event management). The more log sources send data to SIEM, the more can be achieved by this system.
• Raw logs by themselves rarely contain information that is easy to understand.
• Security experts are limited in time and ability to monitor every operation in the system.
• With the help of logs, specialists see only information such as “Connection from host A to host B”.
• The analyst needs information in order to make an informed assessment of any safety-related event.
• To obtain complete information from the logs, a correlation process is required.

Log data analysis helps in the following cases:

• Complying with internal safety policies as well as external guidance and auditing
• Understanding and responding to information security threats
• Diagnosing systems, computers, or networks for bugs
• Understanding the behavior of your users

A properly configured logging system can determine the ease of maintenance of the entire infrastructure, responsiveness to errors, and the time spent on fixing issues. Logging analysis will disclose loads of valuable information on security, errors, site/app functioning, and user behavior.

Security/Compliance

Safety and compliance issues are some of the main impulses for conducting log analysis. Security issues can be disastrous for any organization, sometimes leading to the end of a company. So any investment you make in safety usually pays off. Log analysis comes in handy for detecting data leaks, for instance. Businesses have to be prepared to act quickly and decisively when safety problems occur. Another important use of log files analysis is to help organizations carry out forensic research in connection with investigations.

Many people think that security controls provide all of the necessary information to maintain security. In reality, they often lack the proper context to separate false positives from real attacks. An attack from a misconfigured system is easier to detect than a real attack, as successful attacks rarely look like real ones. Real attackers go to great lengths to avoid detection. Excluding the most primitive attacks, most attackers will try to delete or correct log entries in order to cover their tracks. They know that you tend to trust your logs as they are a reliable source of information which is critical for any investigation of computer interference. Attackers usually try to delete or correct log entries in order to cover their tracks. After all, it is a source of information that you can trust and which is critical for any investigation of computer interference.

Debugging

The most obvious reason to conduct log analysis is debugging.

When supporting solutions that have been installed by a large number of users on various systems, it is essential to receive detailed information about the issues encountered in time. Even with an enormous investment in error prevention, it is never obvious whether everything will work well. If the system collapses, you will need access to data to identify the problem. Thus, you will be able to see what went wrong, when it went wrong, and find a way to fix it.

Logging data helps developers to create and maintain the application’s operation. It helps find errors in the code, what causes them, and ways to eliminate them. Any developer may face situations when some application component malfunctions, produces the wrong result, or stops working altogether. Using logs will help in such circumstances. The time it takes to find problem areas in our code will be reduced significantly, and developers will be able to solve problems faster.

Valuable SEO Insights

A log file is the main source of information about visitor behavior on your website. When someone visits the site, a log file records, for example, which keywords they used to find your resource, which pages they visited, how long they stayed there, etc. Each call to the site is recorded by the server and a record about it remains in the log file. From these records, you can learn a lot about your visitors.

Analysis of logging data is necessary to make SEO promotion as effective as possible. Logs contain:

• IP from which requests to the site were received
• date, time of entry and location of visitors to your resource
• method of requesting a specific URL
• browser type
• response codes for each page, etc.

Having correctly analyzed the logs, you can solve several problems related to your site’s SEO at once. It allows you to:

• detect problems with indexing in real time
• determine if redirects are working correctly
• find out how search bots crawl the site

Thanks to the information received from log data analysis, you will be able to supplement and clarify the work plan for the technical optimization of the site. First of all, it concerns the priority of actions.

Keeping up with performance on a large network requires constant vigilance. Poor performance can occur unexpectedly at any time. Network monitoring platforms such as log analysis tools enable you to identify performance issues before they occur. Using specialized software to analyze log files can make it easier to process large amounts of information.

Modern log file analysis tools offer many possibilities. In addition to the traditional collection and storage of logs, they can intercept the network activity of devices and users both before the occurrence of an unwanted event, and immediately after it. To detect security incidents, new technologies of behavioral and content analysis are used, as well as the correlation of events received from different sources and intercepted network traffic.

If you run a big company, you will need the following:

• Log Management: centralized collection, storage and management of logs and event log data obtained from various sources;
• All-In-One SIEM: All-in-one products that include logs management and logs analysis functionality;
• Risk Management: Information risk management devices;
• Scalable SIEM products: They are used in distributed networks that generate a large number of events per second (EPS) and have significant network flows;
• Separate devices for monitoring network activity.

Data mobility, an increase in the number of users and applications, and the expansion of the boundaries of corporate networks has led to the emergence of a significant number of various information security tools. These include firewalls, antiviruses, complex UTM devices, intrusion detection and prevention systems, DLP systems, IAM and Vulnerability Management solutions, specialized Web and Email gateways, and NAC systems. All these solutions in the course of their work create a lot of useful information that is placed in logging data. Obviously, this information should be regularly analyzed – this allows you to fine-tune security measures, assess the overall state of the corporate infrastructure and, of course, investigate and identify information security incidents.

The problem is that to analyze log files of different formats and event logs of heterogeneous systems can be quite expensive. Anyone who has been involved in maintaining security systems knows how difficult it is to manually conduct log file analysis, especially in solutions with a traditionally high number of false positives, such as, for example, IDS / IPS, proactive antiviruses or DLP systems. Another important challenge is the need to correlate data obtained from different sources. The occurrence of a security incident, as a rule, is displayed simultaneously in the logs of several security systems, and in order to respond correctly, you need to have detailed information about the incident.

In addition, every organization has many active network devices such as switches, routers, wireless access points, remote access tools, and Deed Packet Inspection solutions. Such devices collect statistics on the passage of all network traffic and put it in log files. Data on network traffic is of interest to both security personnel (regarding the details of calls to critical servers and applications) and network personnel.

And, finally, various server and client operating systems, as well as applications that are installed on these systems (these are databases, corporate applications such as ERP, CRM and accounting, mail and Web servers, and so on), put information into event logs. In this case, security specialists are most interested in log file analysis on authentication, access attempts, successful authorization, and performance of critical actions on servers.

Thus, in any organization, even a small one, there are many data sources that generate a large amount of information every day. This information needs to be securely stored centrally and analyzed regularly. Log analysis tools can help with this task.

There are many tools created for log file analysis. They have both similar types of processing and analysis tools and unique functions – it all depends on the reason for logging data. When choosing a service to analyze logs, it is important to know the difference between static tools and real-time analysis tools.

• Static tools: this type of tools makes it possible to analyze only a static file. The main disadvantage is that it is not possible to choose the time period for providing data. To analyze a different period, you need to upload a new log file.
• Real-time analysis tools: this type of tool gives direct access to server logs. Services of this group are installed in the server software environment and monitor all available changes online. The advantage is the ability to choose any period of time for log file analysis.
• Data processing and analysis in Microsoft Excel (Google Spreadsheet): in fact, this method can be classified as a static tool for analyzing log data. This is both the easiest and most time-consuming way to analyze server logs. This method has one significant drawback – the number of analyzed lines is limited by the resources of your computer. You can solve this problem by splitting the source file into several parts. The advantages include the most powerful functionality in terms of statistical data processing, which is not available for the other two services.

As of today, there is a wide variety of log management tools to choose from. Let’s take a look at the best ones.

SolarWind Sem

This is one of the top choices in reporting software. Event logs are extremely important for understanding safety threats, but their significance is greatly reduced if they are stored in isolation. event logs must be monitored and analysed collectively to distinguish threat models. This SIEM enables log retrieval from hundreds of infrastructure sources (firewalls/apps/networking equipment/servers). Real-time events analysis reveals patterns that could indicate an attempted attack.

Splunk

Splunk keeps track of all the intricacies of your system, which is especially valuable if it is complex and distributed. If something goes wrong, it is necessary to select all the events from the logs related to the incident, combine them into a logical sequence, automate and describe the problem. Splunk can do it all. Considering the complexity of tracking the situation in public clouds and clouds in general, Splunk is an ideal solution, because it will allow you to “combine” log files of one logical application, which is spread across different cloud nodes, linking all events by time stamps. Splunk can collect logs from various sources – OSSEC, Snort, AppArmor / SELinux or SSH authentication logs, which will allow collecting logs related to security events.

Kiwi Syslog Server

Kiwi Syslog Server is a useful tool that provides up-to-date information about the operation of network devices, sudden failures and errors. For example, Kiwi Syslog Server can monitor system messages (syslog) from devices that support SNMP trap, Unix and Linux servers, routers, firewalls and other devices involved in networking. It allows you to organize a large amount of data. For this, you can create rules and filters, both for the entire data stream and for each device separately. All messages can be grouped and displayed in separate windows. The tool selects the most important warnings by keywords, notifies users with sound signals, SMS messages, and e-mail. You can automate the work with the message database: specify the time when archiving will take place, start cleaning unnecessary messages, generate regular reports, and display statistics in the form of graphs and tables.

Data storage and analysis is almost always time-consuming and expensive. Nonetheless, you need logging in order to immediately address problems with your app or server operation. We’ve come up with several solutions to optimize logging costs:

• reduce logging space: discover which logs are the largest and find a way to get rid of them. For instance, with the logging data of your app, try saving the variables of most significance.
• set compact logging format: structured logging is the right way of logging. However, it is tremendous in size and often includes repeated records. If the metadata contains minor or rarely used fields, they probably can be removed. Try using shorthand forms of values, avoiding redundant indentation, and optimizing field names.
• set logs auto-delete/archive function: archiving your logs using one of the available services (there are so many of those on the Internet) you can be sure that you will have your log data at hand whenever you need it. Or you can just set a log rotation scheme: once in while your logs can be self-deleted. You can set a time period for this operation and forget about data storage problems.

The use of modern log data analysis tools allows you to obtain valuable insights to the work of your app/site. Such tools allow for the secure storage of information system logs based on one device, reduced labor costs for analyzing and correlating log files and event logs. In addition, the use of such solutions allows you to increase the overall level of security of the corporate infrastructure and increase the efficiency of investments in information security tools.

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