All You Need to Know About Log Management Tools

By Tek-Tools on April 13, 2020

Today, every business has set up stringent processes and systems to ensure their operations aren’t interrupted by system outages or application failures. Any unplanned downtime can lead to significant commercial and reputational losses. As a result, IT teams are always working under strict mean time to detect (MTTD) and mean time to resolve (MTTR) metrics. At the same time, applications and systems have become more complex than ever before. Most applications are deployed over containers in a hybrid environment and use microservices architectures. Though modern stacks provide higher agility, security, and efficiency in the continuous delivery of applications, their troubleshooting and debugging have become highly challenging. This is where log management tools come into the picture. In this article, we’ll discuss how log management tools can help troubleshoot infrastructure and application bottlenecks.

What Is Logging?

In modern IT environments, all networking devices, security equipment, operating systems, servers, databases, applications, cloud resources, and more produce digital records of events. These events are recorded locally in a log file before they’re transmitted to another central location. The process of recording log messages in a file is known as logging.

Here’s an example of a log message:

127.0.0.1 user-identifier david [10/Nov/2014:14:45:38 -0700] “GET /apache_pb.gif HTTP/1.0” 200 2318

The above log message contains crucial information like the IP address of the host, the user identifier, the time of the event, and the HTTP status code (2XX, 3XX, etc.). Most server log messages (like the one above) are plain text and can be read easily. However, logs can also be produced in binary and structured formats. Most organizations and IT practitioners now advocate the use of structured log formats like JSON.

Logs are crucial for tracking changes, and they provide an audit trail during troubleshooting or forensic investigations. Security information and event management (SIEM) processes and tools rely heavily on these logs. Moreover, logging is a crucial compliance requirement for many businesses. With log management tools, teams can analyze their logs to gain crucial insights about the health and performance of their systems.

What Makes Log Management Important?

For an IT administrator, a log file holds crucial data about system performance and health. Though logging is enabled by default on most systems, local logs don’t persist and are replaced by new logs over time. In the past, when organizations experienced performance issues, their IT administrators would look into local logs or SSH into remote servers to resolve the issue. As organizations scaled up their IT infrastructure, however, it soon became impractical for IT teams to log in to different systems to inspect log files. As a solution, IT teams started managing their logs in a central location or database for a longer period. With logs, they could find out the cause of security breaches, track policy violations, and find out if a suspicious change had been made to a critical file or folder. This led to the rise of SIEM tools, which also helped organizations meet compliance mandates. Today, log management tools also help with real-time application performance monitoring.

With log files, DevOps teams can identify what’s leading to a slow webpage and analyze past traffic and system trends to better understand their application performance. With a log analyzer, the team can plan their operations better and provision resources in advance to meet increased workloads. Furthermore, log management tools can provide crucial business insights capable of helping in marketing and other business decision-making.

What Are the Important Steps in Log Management and Analysis?

Log Collection

Log collection is the first step in the log management process, but there are different methods to collect and store log data. Because no two organizations have the same IT setup, their methods and tools for data collection may vary. However, certain systems and applications produce a vast amount of log data, which can easily overwhelm self-hosted or on-premises logging setups. It’s up to the IT teams to control log volumes by defining their logging levels and verbosity, and it’s up to them to ensure only the most critical information is stored. Leaving out information such as users’ personally identifiable data or anonymizing this information is also a crucial compliance requirement for log collection.

Centralized Log Aggregation

Since it’s not possible in large setups to log in to different systems and servers to access individual logs, organizations rely on centralized log aggregation. Logs from all sources are sent to a central server for unified analysis. However, log aggregation in modern IT environments can be difficult, as logs easily spiral out of control. A spike in log volumes often signals a critical issue and ensuring all these logs are captured reliably becomes even more crucial. This is why organizations often choose cloud-based log management tools, which offer better scalability than any other self-hosted setup. Teams also have to deal with numerous log formats, which is another major challenge. To improve efficiency, teams need to convert these logs into a common format, a step known as normalization.

Archiving Logs

Most commercial log management tools allow log retention for up to a week, after which newer logs are written over older ones. In many cases, it’s sufficient for teams to troubleshoot issues by looking at the past week’s data. In some cases, however, organizations may want to increase their log retention period. According to their log rotation policies, organizations automatically resize, move, or delete their older log files, creating space for new log files. However, maintaining or archiving older logs in long-term storage is mandatory for highly regulated industries (e.g., banking and finance). This data can be stored in tapes, discs, or a cloud-based service (e.g., Amazon S3 buckets).

Log Analysis

This is the most important step in the log management process, as it allows teams to gather crucial insights from arcane data. With a capable log management tool, teams can slice and dice their log data for simpler processing, faster search, and visualization. Log analysis makes it possible for teams to identify recurring patterns, hidden issues, anomalies, and outliers. With log analysis tools, teams can live tail their logs, which helps them monitor production environments. Teams can also identify the normal behavior of their systems and applications to set up threshold-based alerts, which help them stay on top of their environment, avoid oversights, and proactively resolve critical issues.

What Are the Best Practices for Log Management?

Ensure Secure and Reliable Log Transfers

When hackers invade an enterprise network, they often delete logs to hide their activities. This is why organizations need to ensure their logs are handled securely and reliably. It’s critical to send all logs to a secure server in real time for forensic analysis. There are three major protocols for streaming log data: User Datagram Protocol (UDP), Transmission Control Protocol (TCP), and Reliable Event Logging Protocol (RELP). Though UDP is a fast and resource-efficient protocol, it doesn’t support log encryption and lacks acknowledgment of receipt (ACK). TCP improves reliability with ACK, but it can be resource intensive. RELP is the most reliable of these protocols. But even though RELP helps in the secure transmission of logs, it’s crucial to ensure the logs are properly encrypted using protocols such as TLS.

Use a Cloud-Based Log Management Tool

Though creating your own log management setup with different open-source tools may seem like a viable option, it usually becomes difficult to manage and optimize. Organizations face numerous configuration challenges and lack clear visibility into the costs of managing such a setup. This is why most IT practitioners advocate the use of cloud-based log management tools. Cloud logging tools offer quicker provisioning and ease of implementation. Organizations can also choose to scale up or try out different options without worrying about vendor lock-in. The tools also offer better integration with various third-party solutions.

Keep Tabs on Log Volume

Log volumes rise rapidly in modern IT environments. Though the cloud can offer auto-scaling to meet surges in log volumes, organizations should aim to control their log volumes and cloud spends. Logging everything without prior planning is not an efficient use of resources. IT teams need to prioritize and understand which information needs to be logged and avoid redundant logs. They should also evaluate the trade-offs of aggregating logs from testing and development environments.

Reduce Complexity

Log analysis is a complex process to begin with. But if log messages lack sufficient context for troubleshooting, analyzing them becomes even more challenging. Instead of an error code, teams should use verbose logging, which helps expedite root cause analysis. Furthermore, structured logging formats like JSON have become a standard. Most tools can automatically parse these logs into different fields, which helps in search and analysis. You can also assign tags or unique identifiers (API tokens, logging session IDs, etc.) to track sessions or user activity. With these tags, you can easily click and filter events of interest.

Monitor Logs in Real Time

When a network or application experiences performance issues, it’s reflected in the log messages. Sometimes, it’s even reflected in the log volumes. Monitoring logs in real time is extremely important in production environments, which is why most log management tools offer a live tail feature. Additionally, threshold- and event-based alerts can help IT teams address critical issues in time. To ensure all team members stay cognizant of system performance, security, and health, organizations can integrate their log management tools with their DevOps ecosystems and workflows.

Unify Logs for Correlation

Traditional log viewers for analyzing individual log files offer little information. Organizations need to correlate data from different applications, servers, devices, and more to differentiate normal patterns from potential threats or troubleshoot performance bottlenecks. For this purpose, SIEM tools offer advanced event correlation engines. However, modern applications also require distributed transaction tracing for debugging and optimizing applications. Organizations should connect their distributed traces to associated logs to further improve MTTR.

Extract Business Intelligence

The benefits of logging for security and compliance, infrastructure maintenance, and application performance monitoring are well-documented. However, organizations can also extract critical business intelligence from logs. Cloud-based log management tools simplify log analysis, allowing teams with limited technical knowledge to make sense of their logs. They can get visual reports and dashboards displaying important business metrics. These insights can help organizations make important decisions affecting business strategy and growth.

Top 10 Log Management Tools in 2020

  1. Open-Source ELK Stack
  2. Security Event Manager
  3. Log Analyzer
  4. Loggly
  5. Papertrail
  6. Kiwi Syslog Server
  7. Graylog
  8. Sumo Logic
  9. Logz.io
  10. Splunk

1. Open-Source ELK Stack

screenshot of elk stack's overview dashboard

The ELK Stack (Elasticsearch, Logstash, and Kibana) is a popular open-source stack for log management and analysis. It includes Elasticsearch, a powerful search and analytics engine built on Apache Lucene. It uses distributed search nodes, which makes it possible to search through large volumes of data with ease. Logstash is used for log aggregation and transformation. Additionally, teams must also configure Beats for log collection. Beats offers lightweight shipping agents for this purpose. Because Logstash often proves to be resource intensive, organizations can also choose Fluentd for log aggregation. However, configuring Fluentd can be a bit challenging. Finally, Kibana is used for visualizing log data. With this stack, organizations can collect logs from each source for unified search and analysis. However, additional sources such as message queues for log persistence and cloud-based databases for log archiving might be required depending on the scale and complexity of the IT environment.

2. Security Event Manager

screenshot of solarwinds security event manager's dashboard

SolarWinds® Security Event Manager is a comprehensive SIEM solution offering centralized log collection and normalization, file integrity monitoring, automated threat detection and response, out-of-the-box monitoring dashboards, compliance reporting, and more. This solution offers several prebuilt connectors to collect logs from different sources. It can automatically parse these logs and transform the log data into a common, structured format. You can easily search and filter the data and visualize it to identify anomalies and patterns. Security Event Manager also offers various templates for major compliances, including HIPAA, SOX, and PCI DSS. You can customize these automated reports and schedule their delivery to all important stakeholders.

3. Log Analyzer

screenshot of solarwinds log analyzer's log viewer report

SolarWinds Log Analyzer is another powerful tool for troubleshooting in live environments. This solution collects logs from a network in near real time and offers visualization, which helps you spot suspicious patterns or abnormal behavior. With this tool, network administrators can easily search and filter a large amount of log data from different sources using custom and predefined tags. It also integrates with the SolarWinds Orion® Platform, giving you a simpler, unified view of network and system performance along with your log data. You can also integrate Log Analyzer with the Orion Platform’s smart alert engine, which not only sends notifications and alerts but can trigger external scripts when certain predefined conditions are met.

4. Loggly

screenshot of solarwinds loggly's dashboard

SolarWinds Loggly® is a popular cloud-based log management tool capable of simplifying log aggregation with its agentless architecture; you don’t need to install any software to collect logs from different sources. It can automatically parse incoming logs into various fields, which are available for search and analysis via its intuitive Dynamic Field Explorer. With this explorer, you can click and sift through various fields without typing multiple queries. Furthermore, Loggly offers advanced visualization so you can quickly analyze logs. Loggly also integrates with tools like GitHub, JIRA, Slack, PagerDuty, and more, making it a useful tool for application and infrastructure monitoring.

5. Papertrail

screenshot of solarwinds papertrail's events report

SolarWinds Papertrail offers cloud-hosted log management, and unlike most open-source and even commercial tools, Papertrail is easy to set up and allows you to gain visibility into your application performance and infrastructure health in minutes. The event stream is presented in a real-time event viewer, which presents messages in an infinite scroll. You can pause the stream at any moment to inspect critical logs, and you can diagnose and fix a range of application and server errors using this tool’s powerful search and analytics capabilities. Papertrail also offers a live tail feature and integrates with common notification services for alerting.

6. Kiwi Syslog Server

screenshot of solarwinds kiwi syslog server's web access report

SolarWinds Kiwi Syslog® Server is a cost-effective solution allowing organizations to manage Windows event logs, syslog messages, and SNMP traps in a centralized location for unified monitoring. The solution is incredibly useful for managing enterprise networks. With this solution, teams can monitor logs from several networking devices, workstations, and Linux-, Unix-, and Windows-based servers from a unified console. It can also automatically raise alerts or trigger scripts in response to critical events. The solution is scalable, and it can buffer up to 10 million syslog messages and 1,000 email messages.

7. Graylog

screenshot of graylog's dashboard

Graylog is another open-source tool many organizations use for log management and analytics. It’s an Elasticsearch-based tool using a multi-threaded architecture to distribute your search load across various nodes in a cluster. This architecture allows Graylog to process several days’ worth of log data and quickly provide search results. There’s no need to learn any proprietary query language; Graylog supports common search operators, and you can run full-text search queries for analysis. Furthermore, Graylog offers various “Content Packs” to simplify complex configurations. You can download these packs from the Graylog Marketplace. Graylog also offers advanced visualization with the help of various widgets. Though the open-source version of Graylog is sufficient for most purposes, an Enterprise (paid) version with some advanced features is also available.

8. Sumo Logic

sumologic's search usage dashboard

Sumo Logic is an advanced cloud-based log management solution serving a wide range of use cases, including SIEM, application performance management (APM), and DevSecOps. This solution helps you correlate all kinds of log data and helps you derive rich insights using several machine learning algorithms. It can analyze a large amount of data in real time and offers visual dashboards to compare trends from past and current data. Because Sumo Logic is a cloud-based tool, organizations can benefit from its flexible pricing. However, this solution has a steep learning curve and can take some time to deliver its true value.

9. Logz.io

screenshot of logz.io's insights dashboard

Logz.io is an ELK-based commercial tool offering log management, infrastructure monitoring, cloud SIEM, and more. The tool also leverages Grafana for log visualization. With Logz.io, teams can correlate all their logs and metrics to get to the root cause of issues faster. Logz.io allows organizations to benefit from the flexibility of open-source software without worrying about configuration issues and other complexities. They can get dedicated technical support and leverage several prebuilt dashboards to monitor their infrastructure. This tool also offers several machine learning algorithms for quicker log analysis.

10. Splunk

splunk's overview dashboard

Splunk is one of the leading SIEM solutions, and it relies heavily on its advanced artificial intelligence-driven data analytics capabilities. With Splunk, organizations can analyze their data in real time with better efficiency and efficacy. Its visualization dashboards make infrastructure and application health monitoring a breeze. With Splunk, you can also automate a wide range of actions for incident management to reduce MTTR.

Conclusion

In this article, we discussed why log management is important and how organizations can use log management tools to gain visibility into their environments. Though logs are easy to instrument and collect, they can be resource intensive. For efficient log management, organizations need to carefully understand their baseline requirements for logging and select a solution capable of offering better value in the long term. In general, cloud-based log management tools offer a lower total cost of ownership (TCO). These tools are also easier to implement and come with dedicated support, which can help you resolve routine and advanced configuration challenges with ease. At the same time, you should look for tools aligned with your organization’s IT road map. You should short-list a solution capable of meeting your current needs and offering easy integration and support for your existing setup. This solution should also have next-gen features, allowing you to scale over time.

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