Log files: what they are, how they are analyzed, what they are used for
These are digital logs that note every event, every access and every action that occurs within a computer system and, in particular, on the server that hosts our website. Basically, they are the digital version of a ship captain’s old logbook, and thus record every single event that happens during the voyage. Log files or log files are automatically generated by the various software and services we use, and they provide a detailed account of what is happening “under the hood”: therefore, they can offer us a way to check the actual behavior of Googlebots and other crawlers on our pages and reveal hidden data to be turned into opportunities to optimize our online presence. Already from this we should understand the SEO value of analyzing log files, which also offer us other useful data for analyzing information related to the technical aspects of the domain, so that we have the tools to check whether a search engine reads the site correctly and scans all its pages.
What log files are
A log file is a record that documents events in a computer system, providing a transparent and detailed view of what is happening so that we can act accurately and knowledgeably.
Essentially, the log file is thus a repository of information in which a computer system records all operations performed. Just like an old paper log, it meticulously catalogs each and every event that happens within an application, operating system, or server. The primary purpose of these documents is to provide diagnostic support, facilitating the resolution of even complex problems.
Log files: computer definition and meaning
Also called log files or log files, log files are precisely digital documents in which the Web server records every single request launched by bots or users to our site, reporting any kind of event that took place at a given time with, possibly, metadata that contextualizes it.
Basically, whenever a user or bot interacts with our site, the server notes this activity in a log file, as if keeping a logbook of all visits.
But how does this work concretely? Whenever a process, such asstarting a program, accessing a website, or updating a system, takes place on a digital machine, this operation is recorded in a log file. The record may include several types of information, including the date and time of the event, the specific nature of the request executed, the result obtained, and, often, any warning messages or errors encountered.
The informational significance of log files is thus twofold: on the one hand, they collect a detailed history of system behavior; on the other hand, they provide a crucial starting point for investigating and resolving any malfunctions. If an application crashes suddenly or a server goes offline, the first action to take will be to check its logs. These tell us where and when the problem occurred, providing an accurate starting point for any action.
But the importance of log files goes far beyond error diagnosis. They help monitor the integrity of a system by tracking possible security threats, such as unauthorized access, unanticipated changes, or suspicious activity. Because in a world increasingly exposed to cyberspace risks, knowing how to read and interpret logs offers an important line of defense against potential attacks and vulnerabilities.
What is a log in computer science
It is necessary at this point to broaden the discussion and clarify what a log is in the context of computing.
The word “log” itself refers, in a general sense, to the sequential and chronological recording of events or activities occurring in a system, program, or server. “Log” is a broad term that can refer to the act of logging itself, a single record of a specific event, or the entire concept of monitoring and tracking activities.
The term finds its roots in maritime navigation of the past. Specifically, this term derives from 18th-century nautical jargon, when the log was literally the piece of wood used to roughly calculate a ship’s speed based on the number of knots outboard (which is why ships’ speeds are still measured in knots today). Originally, then, the word referred to the device called a “log,” which was a kind of nautical “diary”: once thrown into the water, the log counted the knots tied to an unfurling rope, indicating precisely the speed of the ship. The records of these measurements were noted in a “logbook,” a detail that sailors updated regularly to document the voyage.
With the advent of electronics and information technology, the term “log” was adapted to refer to the practice of recording and tracking events within a system, much like the entries in a ship’s logbook. Even in modern computing, “log” thus retains its original connotation of meticulous documentation, chronological transcription and monitoring of operations.
Main functions of logs
Returning to our day-to-day matters, log files are thus records of who accessed the website and the content they accessed; they also contain information about who made the request to access the website (also known as a “client”), distinguishing between human visitors and bots from a search engine, such as Googlebot or Bingbot.
Log file records are collected by the website’s web server, are usually kept for a certain amount of time, and are made available only to the website’s webmaster. Much like the old maritime logbooks, in short, they are a historical record of everything that happens within a system, including events such as transactions, errors, and intrusions, so that navigation can continue smoothly.
The primary function of logs is to track and monitor the activity of a system or software. With logs, system administrators can see what activities are occurring in real time or have occurred previously, identifying problems, verifying configurations, and diagnosing malfunctions. Logs can also prove crucial to security: by recording unauthorized access or anomalies, they enable rapid detection and resolution of threats.
A log can contain a variety of details depending on the context and events it is monitoring. For example, a system log might record the exact time of system startup and shutdown, process identifiers, error messages, and security logs such as failed login attempts. A web server log, on the other hand, might contain information regarding HTTP requests, including the user’s IP address, the web page visited, the server’s response code (such as 200 for “OK” or 404 for “Page not found”), and timestamps related to each request.
Log management and analysis are critical to maintaining a high level of performance and security. For example, in a Web server, log analysis can reveal response timings, frequent errors, or access patterns that could indicate a cyber attack in progress. Similarly, in an e-commerce environment, logs can show user behavior during a purchase process, detect errors in checkout, and gather essential data to optimize the user experience.
Over time, the amount of data recorded from logs has increased significantly, making it essential to use advanced tools to manage and analyze these files. Software such as ELK Stack, Splunk, and Graylog facilitate real-time collection, indexing, and analysis of large volumes of logs, turning raw data into useful insights for making operational decisions and improving system efficiency.
Difference between logs and log files
Over the years, the term log has been extended to cover multiple technology domains while keeping true to its original concept of accurate logging and documentation. This then gave rise to the concept of the log file-a natural evolution of the log as a “record” in a specific format, ordered, and physically stored (digitally) for analysis and diagnosis. The log is essential whenever we need a persistent record of events, especially in the IT context, where timely monitoring of operations is crucial.
When we refer to a log file, we are specifically talking about the file that houses log data, including information about specific events, with details such as date and time, event type, event results, and other relevant metadata. It is then the physical medium (often a text file) in which these logs are actually stored, the container for the records, representing a collection of logs stored in a structured format that is accessible for reading and analysis.
When we speak of “logs” in computer science, we are, in short, referring to an organized history of events, usually in text format, that provides a detailed view of what is happening at a specific time within a system, application or on a server. These events can include a wide variety of actions, such as access to a system, execution of applications, requests sent to a Web server, unauthorized access attempts, and more.
While log is the broadest and most generic concept, the log file represents the concrete materialization of this concept, translated into a sequence of ordered and persistent data.
Types of logs: what they are and what applications they have
There are various types of logs that perform different functions within an IT ecosystem. Understanding these types is essential to operate effective management and in-depth analysis of systems and applications. Let’s look at the main categories in detail:
- System Logs
System logs focus on monitoring the core operations of the operating system. These logs record events such as machine startup or shutdown, hardware device loads and unloads, system updates, and changes to network configurations. In the security context, system logs track unauthorized access attempts and changes to file or directory permissions. They represent a critical component for system administrators, as they allow them to keep tabs on the “health” of the entire software and hardware environment. In environments such as Linux, we can access these logs via files such as /var/log/syslog, while in Windows these events are viewable in the Event Viewer.
- Software Logs
Software logs (or application logs) are specific to each application. They collect data about the internal behavior of the software: any anomaly, error, or significant event within the application is logged with specific details. This type of log is critical for developers and administrators because it allows them to monitor the proper execution of applications and take prompt action in case of malfunctions. For example, database management software might generate logs that track queries executed, data access errors, and overall database performance. These logs are often stored in specific files that reside in the application directory or in a designated location for logging.
- Web Logs
Web logs (sometimes called server logs in the context of Web servers) collect all activity related to a Web server, such as HTTP/HTTPS requests sent by clients and responses sent by the server. Every interaction with the Web site is recorded in a log, providing detailed data on user accesses, resources requested, response times, and errors encountered. For example, a log such as access.log records every user access to a site, allowing administrators and webmasters to analyze web traffic, identify potential attacks (such as intrusion attempts or DDoS attacks), and optimize server performance. These logs are crucial both for SEO optimization, as they provide data on how pages are loaded and indexed by crawlers, and for site security.
- Security Logs
While system logs may contain security information, there are also security-specific logs that focus exclusively on events related to system protection. These logs record unauthorized access attempts, firewall rule changes, suspicious activity, and more. Security logs are critical for defense and post-incident strategies because they provide detailed traces of events that could indicate a security breach.
- Audit Logs
Audit logs are closely linked to compliance and governance requirements. They record the activities of administrators and users to ensure that all operations performed within critical systems are documented and traceable. These logs are used to verify accountability, enabling internal or external audits to assess compliance with regulations and corporate policies.
All of these types of logs, which are saved in specific log files, play a central role in the management and maintenance of modern information systems. By understanding these categories and being able to correctly interpret the data they contain, performance, security and reliability can be kept under control, ensuring efficient operation and a robust architecture for any digital infrastructure.
- Logging, recognition and access logs
Registration, recognition, and access logs are key elements for monitoring and documenting user activities related to authentication and session management within a system. These logs, most commonly associated with login and logout processes, record important details such as the user’s ID, the exact time at which access is made, the authentication method used (e.g., entering a password or using two-factor authentication), and often the IP address and device used.
Cookies are often used for their operation: when a user logs in to a website, a session cookie may be created and sent to the user’s browser to maintain session continuity. This cookie, which contains a unique session identifier, allows the server to recognize the user without requiring further authentication while browsing. Access logs can then also record events related to the creation, modification or invalidation of these cookies, providing an additional useful track to monitor the entire user experience and ensure session security.
When a user logs out, the log records not only the session close event, but can also document the deletion or invalidation of the session cookie. This data provides a comprehensive view of logon activity and is critical for preventing and detecting unauthorized access or attack attempts, such as fraudulent use of still-open sessions via stolen cookies.
In a security and regulatory compliance context, logging and access logs are essential for documenting who has accessed critical resources and for determining whether suspicious or abnormal access has occurred; again, they can document access to sensitive data and ensure that only authorized personnel have accessed critical resources, facilitating any post-event investigations or audits required to verify compliance with security regulations.
Being able to monitor and analyze these access logs-as they are often called-is particularly useful in ensuring that access policies are strictly adhered to, and in protecting the system from possible intrusions.
Focus on the server log
The server log is a specific type of log that focuses on the centralized collection and management of data from various systems, applications, and services within a digital infrastructure. Rather than referring to a single category of events, the term log server describes an approach in which logs generated by various devices and applications are sent to a central server for collection, storage, and analysis.
In practice, a log server receives and manages the log fragments generated by numerous servers, network equipment, firewalls, applications, and various distributional components of an IT infrastructure. This approach ensures the centralization of log records, facilitating real-time monitoring, diagnosis and analysis operations from a single point of control. It is a crucial tool for all those environments where the volume of logs generated is high and requires a coordinated and structured approach in order not to lose sight of essential information.
The log server thus acts as an aggregator: it collects software logs from distributed applications, web logs from various web servers, system logs from servers and hardware devices, and security logs, bringing everything into one central repository. This centralization significantly simplifies log management, as it allows administrators to:
- Correlate logevents from different sources to track and troubleshoot complex problems.
- Proactivelydetect anomalies by aggregating data that would otherwise be distributed and isolated.
- Conduct audits and reporting more quickly and effectively.
With log servers, conducting advanced analysis using visualization tools such as Kibana (part of the ELK suite) or commercial solutions such as Splunk becomes more efficient. These tools are able to manage large volumes of centralized logs, producing graphs, dashboards, and alerts that provide insights into the progress and overall state of the infrastructure. In addition, in the event of a cyber attack, the log server provides a quick and accurate overview of the events that led to the incident, facilitating the implementation of timely countermeasures.
Historical origin of logs: from early implementations to modern logging systems
The history of log files is intimately linked to the very evolution of early computer systems and the growing need to automatically document computer and network activity. The first logging systems date back to the 1960s, during the pioneering era of computing. Initially, mainframes-the large central computers of the time-produced logs primarily to monitor user use of processes, providing oversight of execution times and consumption of computational resources.
In those early stages, log files were simplistically thought of as a series of “records” of events that occurred in a system, typically saved in text format on magnetic tapes. This data was critical not only for diagnostics but also for accounting purposes, especially in environments where computer usage was billed based on resources used. The introduction of multitasking and local area networks in the 1970s and 1980s brought with it increased complexity in systems, and with it the need to record an increasing number of events and to handle a variety of parallel processes. In response, programmers developed more sophisticated systems for log file management, integrating functions for error logging, operation tracking, and application debugging.
During the 1990s, with the rise of theInternet and the proliferation of Web servers, log files assumed a critical role not only for internal technical purposes but also for digital security management. Log servers began to track HTTP requests, monitoring who was accessing particular web resources, cataloging IP addresses and logging unauthorized access attempts. It was during this period that logs proved critical to cybersecurity, enabling administrators to quickly detect and respond to potential threats.
Over the past several decades, logs have continued to evolve, becoming a central component of not only traditional computing but also the emerging world of cloud infrastructure and microservices. Today, the most advanced log systems do not simply record events in a linear fashion. Rather, especially with the advent ofartificial intelligence and machine learning, log files can be analyzed in real time to identify suspicious patterns, automate response to security incidents, or dynamically optimize server resources.
How log files are generated
Log files are constantly generated and updated whenever a computer system, application, or server performs a relevant action. The creation of these files occurs automatically, driven by internal operating system or application code, often without requiring any manual intervention. Whenever a process is started, a connection is made, or any significant event occurs, the system records a log message containing details such as theexact time, the activityidentifier (e.g., process ID), and a description of the event itself.
Overall, the log file sits at the intersection of management, security, and performance. Beneath its technical appearance, it hides immense practical value that is not limited to IT experts. Understanding and using log files enables anyone who manages a site, server, or digital infrastructure to have every aspect of the system under control, with obvious benefits in terms of efficiency and security.
What log files are for: meaning and value
The log file thus tells the whole story of the operations recorded in the course of daily use of the site (or, more generally, of a software, application, or computer), preserving in chronological order all the information both when it is running smoothly and when errors and problems occur .
The log thus contains useful data to have full awareness of the health of the site, because it allows us, for example, to identify whether pages are being scanned by malicious or useless bots (which are then prevented from accessing, so as to relieve the server), whether the actual speed of the site is good or whether there are pages that are too slow, whether there are broken links or pages that return a problematic status code.
More generally, through log files we can find out which pages are visited the most and how often, identify any bugs in the online software code, detect security holes, and collect data on site users to improve the user experience.
That’s why log files are a gold mine for SEO and digital marketers: through their analysis we can understand how search engines interact with our site, what pages are indexed, what errors are detected, and more; in addition, log files can be used for security purposes to identify unauthorized access attempts or suspicious behavior.
Where the log files are located
From a technical point of view, log files are located at the heart of the server hosting the site and can be accessed through our hosting control panel or through protocols such as FTP or SSH, depending on the level of control we have over the server itself.
Although the term log file might conjure up images of gibberish code and cryptic strings of text, in reality these documents are quite accessible and, more importantly, are useful for the full and complete management of a site.
In fact, these files contain valuable information: each line represents a specific event, such as the launch of a program, a system error, or an unauthorized access attempt, and reading this data can help us better understand how our system works, identify any problems, and prevent future malfunctions.
But where are these log files located? The answer depends on the specific context in which you are operating. In Windows operating systems, for example, system logs are stored in a dedicated application called Event Viewer. This tool provides access to logs generated by system events, security, applications, and more. The associated log files are typically located in the C:\Windows\System32\winevt\Logs\ directory and are available in .evtx format, viewable and analyzable through the Viewer.
In Unix and Linux systems, logs are basically much more accessible through the terminal. General log files, such as /var/log/syslog and /var/log/auth.log (for authentication logs), are usually stored within the /var/log/ directory. In particular, system logs and security logs are saved in text format, easily readable with basic Unix commands such as cat, less, grep, or tail.
When working with Web servers such as Apache or Nginx, logs related to handling HTTP requests (such as access.log and error.log) are usually found within the directories configured during server installation. For Apache, for example, its log files might be located in /var/log/apache2/, and for Nginx in /var/log/nginx/. These files provide a detailed view of all interactions with the server, including information about visitors, connection errors, and response times.
It is important to note that no matter what operating system or server you use, log files are powerful tools when used properly. Being able to find them easily and read them meaningfully is a crucial skill, especially when troubleshooting or improving performance. This requires not only knowledge of the appropriate paths and commands, but also the ability to filter and analyze the data in the context of the operations being performed.
In addition to ease of access, there is also the aspect of log protection and retention. Log files can contain sensitive and crucial information; therefore, it is critical to ensure that they are stored securely to prevent unauthorized access and that they are regularly saved and managed to prevent loss.
Proper management and interpretation of log files puts us in a position of control and understanding, making it easier to manage a complex system and ensuring a standard of reliability and security that is indispensable in modern computing.
How to read log files
Trivially, in order to analyze the site’s log file we need to get a copy of it: the method of getting access to it depends on the hosting solution (and the level of authorization), but in some cases it is possible to get the log files from a CDN or even from the command line, to be downloaded locally to the computer and executed in the export format.
Much, however, depends on the system we are using: on a Windows operating system, for example, log files can be found within the Event Viewer, while on a Linux system, they are usually found in the /var/log directory.
Usually, to access the site’s log file we must instead use the server’s control panel file manager, via the command line, or an FTP client (such as Filezilla, which is free and generally recommended), and it is precisely this second option that is the most common.
In this case, we need to connect to the server and access the location of the log file, which generally, in common server configurations, is as mentioned:
- Apache: /var/log/access_log
- Nginx: logs/access.log
- IIS: %SystemDrive%inetpublogsLogFiles
Sometimes it is not easy to retrieve the log file because errors or problems may intervene. For example, the files may be unavailable because they are disabled by a server administrator, or they may be large, or it may be set to store only recent data; in other circumstances there may be problems caused by CDNs or export may be allowed only in custom format, which is unreadable on the local computer. In any case, none of these situations are unsolvable, and just working together with a developer or server administrator is enough to overcome the obstacles.
As for reading log files, there are various tools that can help us decipher the information contained in them: some are built into operating systems, such as the aforementioned Windows Event Viewer, while others are third-party software, such as Loggly or Logstash. These tools can range from simple text editors with search capabilities, to dedicated software offering advanced features such as real-time analysis, automatic alerting and data visualization.
Sometimes, in fact, log files can become very large and complex, especially in large or very active systems, and so resorting to such log analysis tools can serve to filter, search, and display information in a more manageable way.
Log files: what they look like and what information they show
These files are usually in text format, which makes them readable (although not always immediately understandable) and are organized in such a way that they can be analyzed with specific tools. Their location and structure may vary depending on the server operating system and software used, but their presence is a constant in any hosting environment.
The basic structure of a log file includes a number of entries, each usually consisting of a series of fields separated by spaces or other delimiting characters, representing a specific event. Although the exact structure may vary depending on the software or service generating the log file, most entries include at least the following information:
- Timestamp, which indicates the precise time when the logged event occurred, expressed in date and time format.
- Loglevel, which indicates the severity of the event. Common levels include “INFO” for normal events, “WARNING” for potentially problematic events, and “ERROR” for errors.
- Logmessage, which provides details about the event, including, for example, the name of the service or software that generated it, the action that was performed, or the error that occurred.
However, depending on the type of log source, the file will also contain a large amount of relevant data: server logs, for example will also include the referenced web page, HTTP status code, bytes served, user agents, and more.
Thus, this computer-generated log file contains information about usage patterns, activities, and operations within an operating system, application, server, or other device, and essentially serves as a check on whether resources are functioning properly and optimally.
Log files: analysis of the standard structure
Each server records events in logs differently, but the information provided is still similar, organized into fields. When a user or bot visits a web page on the site, the server writes an entry to the log file for the loaded resource: the log file contains all the data about this request and shows exactly how users, search engines and other crawlers interact with our online resources.
Visually, a log file looks like this:
27.300.14.1 - - [14/Sep/2017:17:10:07 -0400] “GET https://example.com/ex1/ HTTP/1.1” 200 “https://example.com” “Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)”
Going to split its parts, we find this information:
- The client’s IP.
- A timestamp with the date and time of the request.
- The method of access to the site, which could be GET or POST.
- The requested URL, which contains the page being accessed.
- The status code of the requested page, which shows the success or failure of the request.
- The user agent, which contains additional information about the client making the request, including the browser and bot (e.g., whether it came from mobile or desktop).
Some hosting solutions may also provide other information, which could include, for example:
- The host name.
- The IP of the server.
- Bytes downloaded.
- The time taken to make the request.
Example of log files: how they appear and what they communicate
An example of a log file might look like the following:
2022-01-01 12:34:56 INFO Service X was successfully started.
In this case, we learn that the event occurred on January 1, 2022 at 12:34:56, that it is a normal event (as indicated by the “INFO” level), and that service X was started correctly.
For better understanding we provide another example of an excerpt from a log file.
We might see something similar to this:
123.123.123.123 – – [12/Mar/2023:06:25:45 +0000] “GET /page-example.html HTTP/1.1” 200 5324 “-” “Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)”
In this line, we have an IP address that identifies who made the request, the date and time of the event, the type of request (in this case, a “GET”), the path to the requested resource, the HTTP status code returned by the server (200 indicates that the request was successfully fulfilled), the size of the file sent in response, and finally the User-Agent, which tells us that the access was made by Googlebot, Google’s crawler.
By analyzing this data, we can draw valuable conclusions about visitor and bot behavior on our site, and use this information to refine our SEO strategy.
What is log file analysis and what it is used for
So here we already have insights into why log file analysis can be a strategic activity for improving site performance, since it reveals insights into how search engines are scanning the domain and its web pages, and more generally what is happening to our system, giving us a detailed view of events, even the “unwanted” ones.
For example, if we are experiencing problems with a particular piece of software, analysis of the log files can help us identify the source of the problem. If we notice that our website is slower than usual, log files can tell us whether it is a traffic problem, an error in the code, or a cyber attack. If we are trying to optimize the performance of our system, log files can give us valuable data about how various components are performing.
In addition, log file analysis can play a crucial role in cybersecurity: the log can reveal unauthorized access attempts, suspicious activity, and other signs of possible cyber attacks, and by analyzing this data, we can detect threats before they become a serious problem and take appropriate measures to protect our systems.
Regarding SEO, then, we can analyze log files to focus on studying certain aspects, such as:
- Frequency with which Googlebot crawls the site, list of the most important pages (and whether they are crawled), and identification of pages that are not crawled often.
- Identification of the most frequently crawled pages and folders.
- Determination of crawl budget and verification of any waste on irrelevant pages.
- Searching for URLs with parameters that are crawled unnecessarily.
- Verification of transition to Google’s mobile-first indexing.
- Specific status code served for each of the site’s pages and search for areas of interest.
- Verification of unnecessarily large or slow pages.
- Searching for static resources crawled too frequently.
- Searching for frequently scanned redirect chains.
- Detecting sudden increases or drops in crawler activity.
How to do log file analysis to obtain useful and relevant information
Log file analysis is an essential practice for those who manage complex computer systems, website managers, security specialists, and application developers. However, the vast amount of unstructured data that logs contain can be intimidating if the right tools and interpretation techniques are not used. In this context, it becomes crucial to know how to approach log analysis, what tools to use, and how to derive meaningful and useful information from this data to improve system management, performance, and security.
To begin with, there are several tools available for log analysis, depending on the complexity of the system and your specific needs. In simpler operations, such as log filtering on Unix and Linux systems, basic commands such as grep, awk, sed, and sort are of great use. These tools allow you to search for specific patterns, filter out only relevant information, and present it in an orderly and understandable manner. For example, grep can be used to identify all instances of a given error within a log file, while awk allows you to extract only certain columns of data, thus simplifying interpretation.
When needing to analyze a large volume of logs or working with logs distributed across many servers, it is essential to resort to more advanced tools such as ELK Stack (Elasticsearch, Logstash, Kibana), Splunk, and Graylog. These tools offer centralized collection, indexing, and advanced log visualization capabilities, allowing data from multiple sources to be aggregated and analyzed in real time. ELK Stack, for example, is an open-source suite that not only allows log data to be visualized in the form of customized graphs and dashboards, but also allows automatic alerts to be set up that can alert system administrators to anomalies.
Once the tools have been chosen, log interpretation becomes the next step. It is critical to determine in advance which metrics are of interest. Taking web log files as an example, we may want to examine HTTP response codes (such as the famous 200, 404, 500) to identify which requests were served correctly and which generated errors. We may want to identify those IP addresses that make an excessive number of requests in an attempt to overload the server (potentially indicative of a DDoS attack). Another useful technique is to track the frequency and temporal distribution of requests to identify anomalous patterns or peak periods.
In addition to the technical part, log analysis also requires an ability to look at patterns at a higher level. One needs to be able to make connections between separate events, contextualizing the logs within the overall activities of the system. For example, abnormal access events may not be significant individually, but when associated with a spike in critical errors in a narrow window of time, they may signal an attempt to compromise an account.
Thus, effectiveness in log analysis depends not only on knowledge of the tools, but also on the ability to interpret the data in a meaningful way. Our task does not end with having isolated an error or identified suspicious behavior; it is essential to understand the context of such events and to establish corrective actions to prevent future problems. Moreover, through regular and detailed log analysis, it is possible not only to respond to incidents, but also to develop a proactive view, aiming to anticipate problems before they become critical.
Specific tools for log analysis: when and why to use them
Log analysis is a process that varies greatly in terms of complexity and need depending on the operational context, the amount of data and the purposes to be achieved. To respond effectively to different needs, there are a number of specific tools that allow logs to be analyzed, visualized, and interpreted efficiently. Understanding when and why to use each of these tools is essential to optimizing the log management and analysis process, ensuring its effectiveness, and making sure we derive meaningful information from the data recorded.
When we operate on small systems or find ourselves working with log files that are small in size, the basic tools available on Unix/Linux operating systems, such as grep, awk, and sed, may be more than sufficient. These tools, which work primarily through the terminal, are extremely powerful for performing quick searches, filtering specific portions of data, and manipulating the output for easy reading and interpretation. For example, grep is useful when you need to isolate specific rows containing a keyword that represents a particular error or event. In small environments, these tools allow you to quickly intervene and solve the problem without the need to install more complex software.
As the complexity of the infrastructure or the volume of data to be analyzed grows, the need may arise to use more advanced tools capable of centralizing and visualizing large amounts of logs from multiple sources. In this context, it may be useful to turn to specific tools, such as Splunk, Graylog, and the ELK Stack suite (consisting of Elasticsearch, Logstash, and Kibana). In any case, choosing the right tool for log analysis depends largely on the amount of data that needs to be managed, the need for centralization of sources, and the clear objectives one intends to achieve in log analysis. Possessing the ability to select and effectively use the most appropriate tool means not only improving operational management of the system, but also being able to turn raw data into valuable insights.
How to use log file analysis for SEO
Looking at a log file for the first time can be a little confusing, but it only takes a little practice to be able to understand the value of this document for the purpose of optimizing our site.
In fact, performing an analysis of the log file can provide us with useful information about how the site is viewed by search engine crawlers, so as to help us in defining an SEO strategy and optimization interventions that prove necessary.
We know, in fact, that each page has three basic SEO states – crawlable, indexable, and rankable: to be indexed, a page must first be read by a bot, and the analysis of log files lets us know whether this step is correctly completed.
In fact, studying the allows system administrators and SEO professionals to understand exactly what a bot reads, the number of times the bot reads the resource, and the cost, in terms of time spent, of indexing searches.
The first recommended step in the analysis, according to Ruth Everett, is to select site login data to display only data from search engine bots, setting up a filter limited only to the user agents we are interested in.
The same expert suggests some sample questions that can guide us in analyzing the log file for SEO:
- How much of the site is actually crawled by search engines?
- Which sections of the site are or are not crawled?
- How deep is the site crawled?
- How often are certain sections of the site crawled?
- How often are regularly updated pages scanned?
- After how long are new pages discovered and scanned by search engines?
- How has the change in site structure/architecture affected search engine crawling?
- What is the speed at which the Web site is crawled and resources are downloaded?
Log file and SEO, the useful information to look for
The log file allows us to get an idea about the crawlability of our site and how the crawl budget that Googlebot devotes to it is being spent: even though we know that “most sites don’t have to worry too much about the crawl budget,” as Google’s John Mueller often repeats, it is still useful to know which pages Google is crawling and how often, so that we can possibly take action to optimize the crawl budget by allocating it to resources that are more important to our business.
On a broader level, we need to make sure that the site is being crawled efficiently and effectively, and especially that key pages, those that are new and those that are regularly updated, are being found and crawled quickly and with appropriate frequency.
Information of this kind can also be found in the Google Crawl Statistics report, which allows us to view Googlebot crawl requests over the past 90 days, with analysis of status codes and file type requests, as well as what type of Googlebot (desktop, mobile, Ads, Image, etc.) is making the request and whether it is new pages found or previous pages crawled.
However, this report presents only a sample of sampled pages, so it does not offer the full picture that is available from the site log files instead.
What data to extrapolate in the analysis
In addition to what has already been written, the log file analysis gives us other useful insights to look for to further our oversight.
For example, we can combine data from status codes to see how many queries end up with different outcomes at code 200, and thus how much crawl budget we are wasting on broken or redirecting pages. At the same time, we can also examine how search engine bots are crawling indexable pages on the site, compared to non-indexable pages.
In addition, by combining log file data with information from a site crawl, we can also discover the depth in the site architecture that the bots are actually crawling: according to Everett, “if we have key product pages at levels four and five, but the log files show that Googlebot is not crawling these levels often, we need to perform optimizations that increase the visibility of these pages.”
One possible intervention to improve this is internal links, another important data point we can examine from this combined use of log files and crawl analysis: generally, the more internal links a page has, the easier it is to discover.
Again, log file data is useful for examining how a search engine’s behavior changes over time, an element particularly when a content migration or site structure change is underway to understand how that intervention has affected site crawling.
Finally, the log file data also shows the user agent used to access the page and can therefore let us know whether the access was made by a mobile or desktop bot: this means that we can find out how many pages of the site are being crawled from mobile versus desktop devices, how this has changed over time, and possibly work to figure out how to optimize the “preferred” version for Googlebot.
Practical log file management guide: from viewing to protecting against unauthorized access
Log file management is also a process that cannot be underestimated: as mentioned, these files contain information that is critical to the operation, security, and maintenance of computer systems. However, proper management is not limited to simply recording events; it requires safe practices for storing, analyzing, and protecting this data so that it can be useful when needed but without compromising the overall security of the system.
First, it is necessary to carefully consider where to save log files. Saving logs locally is a common practice, but it presents some risks, including the possibility of data loss in case of system crashes, errors, or attacks. Therefore, duplicating logs in remote or cloud locations is often recommended to ensure persistence of information even in emergencies. Environments such as Amazon S3, Google Cloud Storage, or dedicated remote servers can be configured to receive periodic copies of logs to minimize the risk of loss of critical data.
Once saved, reading the log files should be done carefully and methodically. Depending on the ability to access the logs, it may be useful to use visualization tools that allow more intuitive and graphical exploration of the data. In Linux systems, for example, logs can be read using basic tools such as tail, which allows monitoring the last lines added to a file in real time, or less, which facilitates browsing large files. However, the use of log aggregators, such as we have seen for Graylog or ELK Stack, can greatly reduce the time and effort required to interpret data by providing a more visual and easily digestible representation of the information contained in log files.
Parallel to reading the logs, a crucial component of their management is their long-term archiving. Retention of such data may be necessary for legal reasons or for corporate compliance policies. In these cases, the organization must provide for the proper duration and method of archiving logs to ensure that they are available when needed, but without unnecessarily burdening storage space. It is a good practice to archive logs in compressed formats such as .gz, .zipper or .bz2 to save space, and to maintain a clear and orderly structure for storage directories for easy reference.
Another critical aspect of log file management is protection from unauthorized access. It is essential that only authorized personnel be able to read or manipulate log files, as they may contain sensitive or critical information about system operations. Permissions at the file system level must be strict; only system administrators and users with specific expertise should have access to critical logs. In server environments, this may include restricting permissions in /var/log/ or using centralized logging systems with granularly defined access through administrative roles.
In addition, theintegrity of log files must be ensured. This means implementing systems and procedures to prevent files from being modified or deleted in an unauthorized manner. In many cases, it may be useful to apply encryption mechanisms to protect the contents of files during transmission or storage, as well as to configure regular backups to prevent data loss.
Managing log files to optimize performance and security in various types of websites
Log file management takes on a crucial role in maintaining and optimizing different types of websites, from the simplest personal blogs to complex e-commerce platforms and editorial news portals. The amount of data collected in logs and its proper interpretation can make the difference between a website that is operating at full capacity, satisfying users and search engines, and one that, on the contrary, risks compromising its online reputation through inefficiencies or, even worse, security breaches.
For e-commerce sites, log file management is critical in several respects. First of all, continuous monitoring of transactions allows detection of any anomalies or delays in the purchasing process, which could result in lost customers and consequently lost revenue. Logs allow tracking the user’s journey from the beginning to the end of the session, including the addition of products to the shopping cart, payment transactions, and any cancellations. Identifying and quickly resolving technical problems through log analysis can mean maintaining an unchanged, smooth customer experience. Also, in the area of security, rigorous log management ensures the ability to detect system intrusion attempts that could compromise both sensitive customer data (such as credit card details) and the integrity of the platform itself.
In publishing portals-sites that serve as hubs for a high volume of published content-logs play a strategic role in resource management and in-depth traffic analysis. Publishing platforms often handle thousands, if not millions, of unique visitors per day, each accessing different content. Web logs collect data on which articles are most read, which traffic sources emerge as most significant (e.g., social media, search engines, etc.), and how much time users spend on each page. Analysis of these logs not only helps editorial teams understand what content is performing best, but also assists in dynamic server management to manage traffic load, prevent downtime, and schedule updates or technical interventions during less busy periods.
But the importance of logs does not end there. Security in publishing portals is a priority, especially with the increase in cyber threats aimed at making defacements (unauthorized changes to pages), or establishing distributed attacks towards the site (DDoS). Logs allow administrators to actively monitor any unauthorized access attempts and prevent minor vulnerabilities from manifesting as serious security problems.
For both types of sites, but especially for complex platforms, having organized and automated log management translates into a considerable operational advantage. It means being able to respond quickly to problems, prevent service downs, and ensure a continuous, secure user experience. Proactive log management, in fact, enables not only troubleshooting but even anticipating problems, thus improving not only site efficiency but also user confidence in the reliability of the platform.
