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The Complete Guide to Log Analysis: What it is, How it Works, Use Cases & Tools

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Logs are one of the most valuable assets when it comes to IT system management and monitoring. As they record every action that took place on your network, logs provide the insight you need to spot issues that might impact performance, compliance, and security. That’s why log management should be part of any monitoring infrastructure.

The first challenge is to aggregate your logs in a single and accessible location which you can easily do as part of your logging solution setup. However, merely centralizing logs is not enough – to gain insights from the aggregated logs you need to follow up with log analysis, which is what we’ll cover in this post.

Read on to find out what log analysis is, why it is important and which are the best paid, free, and open-source log analysis tools available on the market to help you make sure your whole infrastructure is up to par.

What Is Log Analysis?

Log analysis is the process of making sense of computer-generated log messages, also known as log events, audit trail records, or simply logs. Log analysis provides useful metrics that paint a clear picture of what has happened across the infrastructure. You can use this data to improve or solve performance issues within an application or infrastructure. Looking at the bigger picture, companies analyze logs to proactively and reactively mitigate risks, comply with security policies, audits, and regulations, and understand online user behavior.

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Why Is Log Analysis Important?

Most businesses are required to perform log archiving and log analysis as part of their compliance regulations. They must regularly monitor and analyze system logs to search for errors, anomalies, or suspicious or unauthorized activity that deviates from the norm. This allows them to re-create the chain of events that led up to a problem and effectively troubleshoot it.

Moreover, while at first glance data log analysis may seem to affect only the IT aspect of your business it in fact impacts all its aspects, from legal, to finance, sales and marketing, human resources, security, and operations. When leveraging log analysis, you can detect issues before or as they happen and avoid time waste, unnecessary delays, and additional costs, as we’ll explain shortly.

But let’s dive into the specifics – here’s why log analysis is necessary for your business:

Log analysis importance

Reduce Problem Diagnosis and Resolution Time

Hunting down issues can be a tedious and time-wasting task, especially when it’s not clear if the problem is on the application layer or infrastructure.

Whether it’s the former, the latter, or a combination of the two, they prolong the time your app delivers a poor user experience. Log file analysis allows you to take a proactive approach by pointing out issues and their root causes before or as they happen. This avoids time loss and reduces MTTR.

Also, DevOps can intervene and solve problems faster, thus allowing them to focus more on improving existing and adding new functionalities to products and services they are creating instead of spending time troubleshooting. This, in turn, increases value of software they are building, leads to more frequent releases and increases the overall value for the business.

Reduce Customer Churn

Customers are more selective than ever when it comes to the applications they use. With such a large pool of alternatives at their disposal, they can easily turn to one of your competitors if they’re not satisfied with your product or service. You must deliver an excellent user experience that, looking beyond functionalities, boils down to a stable and performant application with regular updates.

Frequent downtimes and poor product quality are among the top reasons for high customer churn. By analyzing your log files you are able to detect the root cause of performance and stability issues faster, thus improving your users’ experience and reducing customer churn

For example, you’ll be able to search for HTTP errors and understand where and why they occurred; or detect when users don’t receive the information they searched for or if their requests are taking too long to load, or if some microservices are experiencing issues, and so on.

Improve Resource Usage & Production Infrastructure Costs

One of the most challenging aspects of any organization is resource management – from network bandwidth to CPU cycles or storage capacity and beyond.

You can speculate resource sizing, but you either end with not enough resources – which leads to poor performance, frustrated customers and, ultimately, lost sales – or too many – which increase expenses, thus affecting your bottom line. Instead of guessing your resource requirements, log file analysis – along with metrics-based resource usage and planning – allows you to easily and more accurately understand your current resource utilization and your future resource requirements.

Also, when it comes to system performance, more often than not, it’s not the software at fault, but rather users’ requests that overload your system to the point where it has trouble handling the demand. Log analysis allows you to track resource usage and detect where your system is struggling so that you can add extra capacity.

On the other hand, you can also see underutilized or dead assets so that you can restructure and optimize your infrastructure to improve productivity and proficiency. You can also use server-sprawl data to optimize your on-premise or cloud infrastructure costs.

How Does Log Analysis Work?

Logs are streams of chronologically arranged messages that are generated by applications, network devices, operating systems, and any programmable or smart device. They can be either stored on disks as files or directed to a log collector as network streams.

Seeing as they come from different log sources, logs can take various formats. For instance, what one system calls “warning,” another may refer to as “critical,” “authentication” could be “login,” and so on. They are application or vendor-specific, so they need to be interpreted according to context. As such, when collected to a centralized location, they are normalized to a common format and terminology to avoid confusion and ensure uniformity. This helps ease the analysis, reduce errors, and make sure that reports and statistics provide useful and accurate data.

Once logs are aggregated, DevOps can analyze them to detect patterns, anomalies along with their root causes, and trends. They can see what happened, when, where, why, and how it impacted performance, thus enabling them to build appropriate countermeasures and models to avoid risks in the future.

Log Analysis Use Cases & Applications

From handling security issues to troubleshooting app performance anomalies or compliance with regulations, there is a wide range of situations where analyzing log data provides invaluable insights.

Let’s dive deeper and see which are the most common use cases for log analysis:

Log Analysis Use Cases

Better System Troubleshooting

One of the most obvious use cases for log analysis is probably in troubleshooting servers, networks or systems, from application crashes to configuration issues and hardware failure. Fast troubleshooting helps avoid downtime and performance issues that can increase customer churn.

Troubleshooting with log analysis is often used in production monitoring as it enables DevOps to detect and solve critical system errors faster, improving operational efficiency. They have more time to invest in production, thus reducing production downtime.

Respond Better to Data Breaches and Other Security Incidents

When it comes to cyber-security, logs provide a fountain of information about your attackers, such as IP addresses, client/server requests, HTTP status codes, and more. However, they remain under-appreciated. A lot of companies fail to understand the value of logging analysis still relying only on basic firewalls or other security software to protect their data against DNS attacks. However, without log analysis, you can’t understand security risks and respond accordingly.

Logs act as a red flag and with security log analysis, you can track down suspicious activities and set up thresholds, rules, and parameters to protect your system from similar threats in the future. With log analysis, you’re even able to assist in blocking your attackers by their IP address.

Log data analysis tools can alert you whenever they detect anomalies so that you can quickly intervene and eliminate the threat. They use artificial intelligence and machine learning to spot patterns and behaviors that would have otherwise flown under the radar.

Furthermore, logs are extremely useful in cyber forensics. In case of an investigation, forensic log analysis can provide the time and place of every event that happened in your network or system.

Ensure Compliance with Security Policies, Regulations & Audits

Most organizations are subject to government-set standards and industry requirements they need to adhere to guarantee safety and functionality. As such, many are required to log data and analyze it on a daily basis. Doing so, not only helps to defend against insider and outsider threats but also to demonstrate a willingness to comply with ISO, General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA), Sarbanes-Oxley, PCI DSS, and many others.

In addition, log files analysis can also help with audit requirements, litigation needs, subpoena requests, and forensic investigations.

In short, considering the ever-growing complexity of systems and software solutions, log analysis is the only way to make sure policies are followed, and regulations are met.

Understand Online User Behavior

Log analysis is one of the best ways to understand your app or webapp’s visitors’ behavior. It shows not only how many visitors you had but also allows you to re-trace their exact journey and understand on what pages they spent the most time, what were they doing on your website, why are there changes in the number of visitors, etc.

With trends and patterns in plain view, it’s easy to spot opportunities like when is the best time to send a newsletter, when to release a new version or launch a product, when to close down your site for maintenance or tests, and much more.

Furthermore, log analysis can be used to impact marketing efforts as well. By collecting data such as referring sites, page accessed, and conversion rates, you can determine how well your marketing campaign does and take measures to improve it if needed.

Similarly, as logs contain information about conversion errors, customer navigation, and traffic loads, logging analysis can provide meaningful insights about how to optimize website performance to better support the sales process.

Log Analysis Best Practices

Log analysis is a complex process that should follow the following functions:

Log Analysis best practices

Pattern Detection and Recognition refers to filtering incoming messages based on a pattern book. Detecting patterns is an integral part of log analysis as it helps spot anomalies.

Log Normalization is the function of converting log elements such as IP addresses or timestamps, to a common format.

Classification and Tagging is the process of tagging messages with keywords and categorizing them into classes. This enables you to filter and customize the way you visualize data.

Correlation Analysis refers to collecting data from different sources and finding messages that belong to a specific event. It helps to make connections between logs since multiple systems record an incident. For example, in the case of malicious activity, it allows you to filter and correlate logs coming from your network devices, firewalls, servers, and other sources. Correlation analysis is usually associated with alerting systems – based on the pattern you identified, you can create alerts for when your log analyzer spots similar activity in your logs.

Artificial Ignorance is a machine learning process that recognizes and discards log entries that are not useful and is used to detect anomalies. When it comes to logging analysis, it means to ignore routine messages generated from the normal operation of the system like regular system updates, thus labeling them as uninteresting. Artificial ignorance alerts your about new and unusual events, even about common events that should have occurred but did not – for example, if a weekly updated has failed. These should be investigated.

Best Log Analysis Tools & Log Analyzers (Paid, Free & Open-source)

As such, log analytics, log analysis, and log management tools have become essential in troubleshooting. With logging analysis tools – also known as network log analysis tools – you can extract meaningful data from logs to pinpoint the root cause of any app or system error, and find trends and patterns to help guide your business decisions, investigations, and security.

DevOps, security professionals, system administrators, network administrators, web developers, and site reliability engineers can use them to make better data-driven decisions.

To help you get started, we’ve put together a list with the best free and open-source log file analysis tools available in the market, to help you better parse your logs, run live tail searches, or query the specific log data you need.

best log analysis tools

1. Logstash

Logstash is one of the most popular free open-source for managing and processing log data and events. It collects and parses logs from various sources across your infrastructure and sends them to your preferred destination.

As part of Elastic Stack (former ELK), in most cases, it’s used together with Elasticsearch and Kibana. Together, they make for a powerful log analysis solution, where Elasticsearch provides the full-text search and analytics features, while Kibana allows you to visualize and explore the data you gathered with Logstash.

Read more about the pros and cons of Logstash in Logstash alternatives.

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2. Fluentd

Fluentd is another open-source log analysis tool that collects event logs from multiple sources such as your app logs, system logs, access logs, etc. and unifies them into one logging layer. It allows you to filter, buffer, and ship logging data to various systems such as Elasticsearch, AWS, Hadoop, and more. It’s a favorite among DevOps due to its extensive plugin library which allows you to connect with multiple data sources and drive better analysis.

3. Graylog

Graylog is a free and open-source log management platform that gathers data from different locations across your infrastructure. It allows you to search and analyze through terabytes of data instantly, detect performance issues and understand their root cause, and identify trends over time. You can set up alerts and triggers to monitor data failures or detect potential security risks. Graylog also helps your organization follow compliance rules.

4. LOGalyze

LOGalyze is a free log analyzer and parser that collects event logs from devices, Windows hosts, Linux and UNIX servers or any system or application. LOGalyze enables you to do predictive event detection in real time and generate reports based on multi-dimensional statistics. You can use these reports to spot performance trends or ensure your organization complies with standard regulations such as HIPAA, SOX, PCI-DSS, and more.

5. GoAccess

GoAccess is a fast terminal-based log analyzer software that enables you to quickly view and analyze web server statistics in real time, within milliseconds of it being stored on the server. With GoAccess, instead of using your browser, you get to access your data via SSH or the terminal of Unix systems. It’s able to generate complete HTML reports, as well as JSON and CSV.

Open-source and extremely easy to use, GoAccess allows you to process logs incrementally, track application response time and supports custom web log format strings (Apache, Nginx, Amazon S3, Elastic Load Balancing, CloudFront, and more).

6. Sematext Logs

Sematext Logs is a log management solution that offers you real-time actionable insights into your log analytics with hosted ELK as a service, in the cloud or on-premises. It’s compatible with a large number of log shippers, logging libraries, platforms, and frameworks, being able to aggregate logs from a variety of sources.

Sematext Logs features sophisticated full-text searching, filtering, and tagging capabilities and allows you to correlate logs with infrastructure and application metrics. You can set up alerts on both log data and metrics and use Live Tail to see new errors as they’re logged in real time. We offer both free and paid plans.

You can also read a review of Sematext Logs on Network Admin Tools, amongst other log management solutions.

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7. Loggly

Loggly is a cloud-based log management service that has both free and paid plans. With its dynamic field explorer, you get a real-time overview of your logs categorized by structure or by customized view. Loggly has powerful full-text searches featuring searches by individual fields, booleans, ranges, and more. Their interactive, ready-to-use dashboard provides performance indicators and metrics that allow you to spot trends as well as performance issues.

8. Splunk

Splunk is one of the most well-known log monitoring and analysis platforms, offering both free and paid plans. It collects, stores, indexes, correlates, visualizes, analyzes, and reports on any machine-generated data. When using the tool, you can search through both real-time and historical log data. Splunk allows you to set up real-time alerts where automatic trigger notifications can be sent through email or RSS. You can also create custom reports and dashboards to better view your data and detect and solve security issues faster.

9. Logentries

Logentries is a cloud-based log management platform that’s available for both free and commercial use. It allows you to query data in real time with aggregated live-tail search to get deeper insights and spot events as they happen. Logentries also features live monitoring and receive instant alerts whenever anomalies are detected. You can then add custom tags to be easier to find in the future and analyze your logs via rich visualizations.

10. is another cloud-based log analysis service built on the Elastic Stack and Grafana, thus ensuring easy scalability, high availability, and security. The platform and offers both free and paid versions. With you can search through massive amounts of data and get real-time insights. It uses machine learning and predictive analytics to detect and solve issues faster. Other features include alerting, parsing, integrations, user control, and audit trail.

11. Sumo Logic

Sumo Logic is a machine learning analytics service that can provide real-time insights into applications and systems. It features advanced analytics to help understand data by using indexing and filtering. Machine learning allows you to process over 100 petabytes of data per day and learn from this to identify patterns and trends faster. Sumo Logic is available in both free and commercial options.

12. SolarWinds Log & Event Manager

SolarWinds’ Log & Event Manager is another big name in the world of log management. It allows you to collect and normalize data from multiple servers, applications, and network devices in real-time. However, the software lets you store and investigate historical data as well, and use it to run automated audits. SolarWinds’s log analyzer learns from past events and notifies you in time before an incident occurs. It helps take a proactive approach to ensure security, compliance, and troubleshooting. The company offers paid plan and a free trial.

13. ManageEngine EventLog Analyzer

EventLog Analyzer is a log management solution that has the basic functionalities of a SIEM product. Once installed, EventLog Analyzer is ready to collect, parse, and analyze event logs from all the devices in your network. Some of its other features include real-time alerting and event correlation, file integrity monitoring, and privileged user monitoring, to help you detect and avoid server errors and attacks. You can instantly generate various reports, including user activity reports and historical data trends. It’s one of the best tools available to conduct forensic log analysis and ensure regulatory due diligence. EventLog Analyzer has only a paid option, but you can get a free trial.

14. Papertrail

Papertrail is a log analyzer that automatically scans your logs to provide real-time insights into your infrastructure. It features real-time search to help detect issues faster and trace back the chain of events to identify the root cause. Filter log events by source, data, severity level, facility, or message contents to focus on the most meaningful data. You can then chart or graph them using third-party integrations to quickly spot trends and patterns. Papertrail is available as both free and paid options.

15. LogDNA

LogDNA is a log management service available both in the cloud and on-premises that you can use to monitor and analyze log files in real time. It gathers data from any app or system, including AWS, Heroku, Elastic, Python, Windows, or Docker, being able to handle one million log events per second. It features real-time searching, filter, and debugging capabilities and a robust algorithm to help connect issues with their root cause. LogDNA offers multiple paid options, as well as a free trial.

16. Datadog

Datadog is another log analysis tool you can use to record, search, filter, and analyze logs from all your devices and applications in real time. Datadog has rich and sophisticated dashboards that you can further customize by drag-and-drop. It allows you to correlate logs, metrics, and request traces to get a clear view of your systems and easily spot performance trends over time. The solution features smart alerting that uses machine learning to identify abnormal log patterns and errors faster. Datadog only has paid versions, but it offers a free trial.

Wrapping up

Thanks to its multiple purposes log analysis a critical part of log management. It helps with monitoring and alerting, measuring productivity, security incidents response, governmental compliance, and it’s useful even in cyber-forensics.

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There are plenty of log analysis tools to help you make sense of your log data, both free and paid. They help streamline your DevOps workflow and saves time by avoiding going through massive amounts of unstructured data. With such tools, you are better equipped to detect issues and threats before they impact your business, find the root cause, and proactively and reactively mitigate risks. If you’re not already using one, it’s best to get it soon and not wait for a serious incident to come up..

If you need help deciding or any support regarding logging, at Sematext, we offer Logging Consulting so feel free to reach us out!