As IT environments grow increasingly complex, businesses generate more log data than ever before. However, simply collecting logs isn’t enough. Without a well-structured log management strategy, organizations risk missing critical insights, delaying incident response, and failing to meet compliance requirements.
In this article, we’ll explore the key components of effective log management and best practices to help you transform raw data into valuable security and operational insights.
Let’s dive into how you can take control of your logs and convert raw data into actionable intelligence.
What Is Log Management and Why Does It Matter?
Log management is the process of collecting, storing, monitoring, and analyzing log data generated by applications, servers, network devices, and other parts of the IT environment.
It is a crucial discipline for keeping an organization’s IT systems operational and secure, as well as ensuring compliance with regulatory requirements.
Log management is especially crucial for organizations with complex IT environments, where manually investigating events across multiple devices, applications, and services can be overwhelming.
Instead of accessing and analyzing logs individually on every device/application/service, a centralized log management system collects and normalizes logs from the entire infrastructure.
This streamlined approach enables efficient analysis and event correlation, allowing IT teams to not only understand isolated incidents but also assess their broader impact on system performance and security.
Why is Log Management Important?
Effective log management is not just about storage. It’s about making data available for security, compliance, and operational efficiency. Typically, log management plays an important role in the following areas:
- Systems Administration – Log data provides real-time insights, helping IT teams quickly identify and resolve issues such as application crashes, slow response times, and hardware failures.
- Cybersecurity – Cyberthreats, i.e. unauthorized access attempts and malware infections, can often be identified through proactive log monitoring. It enables organizations to detect and respond to security incidents before they escalate, mitigate their impact and prevent spreading threats across the IT environment.
- Regulatory Compliance – Many organizations are required to maintain and audit log data. Those typically include healthcare (HIPAA), finance (PCI-DSS), government, etc. Also, many general cybersecurity acts on data protection, such as GDPR or NIS2, require subjects to monitor and store log data for future evidence. Proper log management helps businesses meet these regulatory requirements and avoid costly fines.
- Business Continuity and Forensics – In the event of a system breach or failure, logs act as a forensic trail that helps teams reconstruct events and pinpoint vulnerabilities.
Fig 1: The VPN traffic dashboard provides a comprehensive view of network activity. At the top, a histogram displays communication over time, followed by visualizations breaking down activity by user, VPN groups, and status. (Logmanager)
What Is the Difference between SIEM and Log Management?
When it comes to IT security, log management and SIEM (Security Information and Event Management) often come up. While they share some similarities, they serve different purposes.
Log management is all about collecting, storing, and organizing logs from various systems, applications, and devices in one, centralized solution. Think of it as a detailed record of everything happening in your IT environment. These logs help with troubleshooting, monitoring system health, and ensuring compliance.
SIEM takes log management to the next level. Functions of SIEM that distinguish it from basic log management include log analysis, event correlation and alerting teams about potential threats. SIEM is designed to help with detecting cyberattacks, supporting incident response, and meeting compliance requirements.
SIEM is often considered a must-have for large enterprises with dedicated security teams. For smaller businesses, it can be expensive and place an overwhelming burden on the IT department.
We cover this topic in more detail in our blog article SIEM vs. Log Management.
Key Components of Effective Log Management
To build an efficient log management strategy, organizations must develop competencies that ensure logs are collected, stored, analyzed, and monitored effectively.
Basically, whether a company decides to build an in-house log management solution from the ground up or purchase a professional tool, it must ensure that the solution includes the following key components.
1. Log collection
Logs (log files) are digital records that capture information about specific events related to a particular applications, servers, networks, services etc., helping IT teams track system activities, detect anomalies and cyberthreats.
Fig 2: An example of a raw log.
Log collection is a process of querying log data from different sources into one location, a centralized log management system. There are many sources of log data, but with some simplification, we can categorize them as follows.
- System logs – Provide an overview of the operation of operating systems, e.g. Windows Event Logs, Syslog (service start and stop events, system errors, updates, configuration changes, etc.).
- Application logs – Offer details about application behavior, including errors, warnings, successful or failed connection attempts, and specific application events.
- Security logs – Should include data on user logins and logouts, unauthorized access attempts, permission changes, malware detection, or unusual activities.
- Network logs – Monitor communication between devices on a network and may contain information about intrusion attempts, firewall configuration changes, IDS/IPS and VPN activities, exploit attempts etc.
2. Log storage, rotation and retention
Having a searchable database of all logs in one centralized storage is a key advantage of a log management solution. Using centralized log storage prevents data silos and allows IT teams to search, monitor, and eventually correlate logs in real time.
On the other hand, without a log management tool, IT teams must access logs directly on individual devices/applications/services which in case of the unexpected event, extends analysis and troubleshooting time.
Considering the right log retention period is about balancing business needs with available resources. Longer retention period usually leads to higher costs.
Since logs play a key role in achieving IT compliance with acts such as GDPR, HIPAA, NIS2 and standards such as ISO27001 and SOC2, log management tools must support respective retention periods (usually 3 to 18 months).
→ If you are interested in this topic, visit our blog discussing log management and NIS2 compliance.
Utilizing cloud-based log management solutions or on-premises storage with compression and archiving techniques can optimize storage space while maintaining data integrity. Regularly reviewing and purging outdated logs helps enhance system efficiency and reduces security risks associated with excessive data accumulation. By implementing automated log rotation and retention strategies, businesses can ensure efficient log management while meeting regulatory and operational needs.
3. Log monitoring and alerting
Log monitoring is a discipline of real-time observation of logs to detect issues, anomalies, or security threats as they happen. It involves setting up queries and triggers, dashboards, and automated responses to specific events or patterns.
The goal is to identify and respond to problems quickly. For example, if there are repeated failed login attempts indicating a possible brute-force attack, an alert is triggered so that IT teams can investigate and take immediate action.
4. Data visualization and dashboards
Effective log management is about making sense of huge amounts of data. That’s where data visualization and dashboards come in.
A well-designed log management system provides customizable dashboards that help users monitor system health and security incidents at a glance. These dashboards can display real-time data through charts, heatmaps, and trend graphs, making it easier to spot anomalies, such as sudden spikes in error rates or security breaches.
Fig 3: An example of the log management dashboard – authentication events across the organization, bringing together logs from various systems, applications, infrastructure, and security solutions.
Beyond dashboards, log management tools offer prebuilt and custom reports, which can be used for compliance audits, security reviews, and performance tuning. Drill-down capabilities allow IT teams to investigate specific log entries directly from the dashboard, providing deeper insights into potential issues.
For example, a security analyst investigating an alert can click on a suspicious event to reveal a full timeline of related log entries. By transforming raw log data into visual insights, organizations can improve decision-making, speed up troubleshooting, and enhance overall system visibility.
5. Log analysis
When log monitoring is essential for immediate issue detection, such as security breaches or system failures, log analysis is useful when you need to dig deeper into incidents. Simply put,
log monitoring and log analysis serve different purposes and operate at different levels of depth.
| Log Monitoring | Log Analysis | |
| Purpose | Continuous tracking of log events in real-time | In-depth examination of logs for insights and troubleshooting |
| Focus | Detecting anomalies, errors, and patterns | Investigating root causes, trends, and correlations |
| Usage | Alerts on critical issues (e.g., failed logins, system errors) | Diagnosing security breaches, performance bottlenecks, and compliance issues |
| Scope | Surface-level visibility | Deep dive into log data |
| Method | Uses predefined rules, thresholds, and alerts | Involves querying, filtering, correlation, and machine learning in some cases |
| Timeframe | Primarily real-time or near real-time | Historical and real-time data analysis |
| Outcome | Quick detection and response | Data-driven decision-making and long-term improvements |
Log management tools usually offer a range of features specifically designed to conduct log analysis, helping IT teams extract meaningful insights. Such features include:
- Centralized logs aggregation from various sources (servers, applications, cloud services, network devices).
- Parsing and normalization in order to convert raw logs into a consistent format for easier/faster understanding.
- Log indexing for fast querying of logs using keywords, filters, tags or complex queries.
- Historical search to find specific events.
- Predefined rules and ability to create custom ones in order to detect unusual patterns and anomalies (unexpected traffic spikes, repeated failed login attempts, etc.).
- Alerting on critical issues, such as security breaches or system failures.
- Dashboards to visualize log data in real time in order to see patterns and trends.
- Log correlation and contextual analysis to link related log events across different systems and reveal root causes or impact of unwanted behavior.
How to Manage Logs Effectively? Best Practices for Log Management
Implementing log management best practices ensures that organizations can efficiently collect, store, and analyze logs while maintaining security and compliance.
1. Define the scope of log management
Conduct a full inventory of your infrastructure to determine what should be included in log management. Don’t overlook even the smallest or least important device on the network – attackers often exploit the ones you least expect.
As a part of this thinking, assess business impact of systems included within the scope of log management. A simple but effective question to guide prioritization: “If asset X were compromised or lost, could the organization continue to operate?” This approach helps focus security efforts.
2. Log key areas of interest
This point directly follows defining the scope of log management. Start by determining which activities should be logged and set the appropriate level of monitoring for each.
Logged data often includes transactions that must adhere to compliance requirements. It also covers authentication activities like login attempts and password changes, as well as database queries and server commands.
While this is not a comprehensive list, logging the following is considered best practice:
- User access – Who logged into the system, when, and what actions they performed (e.g., access to sensitive information, configuration changes).
- Failed login attempts – Number of failed attempts, time intervals between them, and geolocation data to identify suspicious patterns.
- Configuration and update changes – Any system modifications, installed updates, and changes in device settings.
- Application and system errors – Logs of application crashes, error messages, and availability issues.
- Security Incidents – Unauthorized access attempts, DDoS attacks, malware activity, and unusual user behavior.
- Network activity – Records of suspicious or unusual connection attempts, communication with unknown IP addresses, and large data transfers to and from external sources.
3. Structure logs for better search and accessibility
In modern IT environments, logs originate from a diverse range of sources, such as applications, databases, network devices, cloud services, and security tools. Each has its own unique approach to log file structure.
To store data in a unified format on a log server, it must first be read and restructured. This process is known as parsing. A parser acts as a translator that understands the text in the source syslog / JSON or other file type, extracts relevant information, and converts it into a structured format, essentially converting a text into a table on the log server.
Fig 4: An example of creating a new parser via Blockly. User can easily test parsers using embedded test logs and instantly see the results – without affecting production data in any way (Logmanager).
By doing this, data from different sources is standardized, making it easier to analyze, search, and correlate. Proper parsing ensures that logs are consistent, organized, and usable for monitoring, troubleshooting, and security analysis.
Standardizing logs improves operational efficiency, reduces the burden on IT and security teams, and enhances the overall observability of complex infrastructures. Additionally, structured logs facilitate compliance with industry standards (e.g., PCI-DSS, ISO 27001) by ensuring that critical events are consistently recorded and easily auditable.
4. Use log indexing and tagging
Log indexing structures logs to improve searchability and analysis. It is a fundamental operation that enables near-instant retrieval of captured logs and simplifies analysis and troubleshooting.
In structured logging, log messages follow a predefined format for key log fields, such as timestamps, user IDs, error codes, or IP addresses.
Fig 5: An example of how log indexing works (processed via Blockly in Logmanager).
While its main purpose is to enable quick log searches, log indexing also provides additional benefits. It helps optimize storage on the log server, enables fast data backups, and serves as a best practice for managing data volume to maintain the desired retention period based on available storage.
Log tagging involves adding metadata (such as source, application, environment, or severity level) to log entries, making them easier to filter and categorize. This simplifies searching and enables more precise queries, helping IT and security teams quickly identify relevant logs when investigating issues.
Together, log tagging and indexing play a crucial role in improving observability, streamlining troubleshooting, and enhancing the overall efficiency of log management.
5. Centralize logs for better visibility
Logs are generated across multiple IT systems – servers, applications, firewalls, databases, cloud services, etc. Each produces vast amounts of data in different formats.
A centralized log management software such as Logmanager aggregates logs in one place, allowing for effective log monitoring, advanced search, automated alerts, and cross-platform correlation.
Without a centralized log management tool, administrators must manually access each system, parse logs separately, and correlate events across various sources, leading to operational bottlenecks, inconsistencies, and missed security threats.
Centralization significantly reduces manual effort and improves response times when investigating security incidents or system failures. Instead of sifting through disparate log files on individual devices, administrators can use queries and dashboards to quickly identify patterns, detect anomalies, and streamline troubleshooting.
6. Set up alerts
To ensure a swift response to potential threats, automated alerts should be set up for critical events as a part of best practices for log management.
Such alerts should cover events such as:
- Unauthorized access attempts or configuration changes.
- A sudden spike in failed login attempts within a short period.
- Detection of malware or unknown files that could be executed.
- Modifications to firewall settings or security rules.
- Evidence of attempted exfiltration of sensitive data.
A major task closely related to alerts is the prioritization of alert severity. As a best practice, it’s crucial to configure alert severity levels properly to prevent administrators from being overwhelmed with unnecessary notifications. Focus on delivering only relevant alerts to ensure a timely and effective response to real security threats.
7. Conduct regular testing and validation of logging
Conduct routine tests to ensure that all critical devices and applications are correctly configured for logging. Additionally, verify that the collected logs are sufficiently detailed, relevant, and properly parsed, making them searchable and filterable.
Also, perform regular simulations and tests to evaluate how logging and alerting systems would respond in the event of an attack or security breach.
8. Store logs in immutable storage & use access control
Ensure that logs are stored in a secure, tamper-proof environment (commonly known as immutable storage). Immutable storage refers to a type of data storage where, once data is written, it cannot be modified, altered, or deleted—either permanently or for a specified retention period. This ensures data integrity, security, and compliance with regulations.
It is also considered best practice to restrict log access to authorized personnel only, using access control systems such as RBAC (Role-Based Access Control).
Any modern log management solution should prevent log manipulation. However, if you are unsure, ask the vendor how they handle this issue.
Conclusion
As the volume of log data grows, businesses need more than just storage solutions, they need systems that offer real-time monitoring, advanced analysis, and seamless compliance management. Implementing structured logs, centralized management, automated alerts, and immutable storage will be crucial for staying ahead in 2025.
If your organization hasn’t adopted effective log management practices yet, now is the time to begin.
With Logmanager, you get a full-featured log management system for fast incident detection, investigation, and compliance adherence.
If you want to learn more about how Logmanager can help your organization optimize log management, book a demo today or start your 7-day free trial.
