Log Aggregation Explained

Getting Started with Log Aggregation in Production

Better Stack Team
Updated on March 9, 2023

Log aggregation is a crucial aspect of modern IT operations, enabling organizations to collect, centralize, and process large volumes of log data from disparate sources. This process is essential for achieving a comprehensive understanding of the behavior and performance of complex IT systems, and for troubleshooting issues, detecting security threats, and ensuring compliance with industry standards.

By aggregating logs from multiple sources, you'll gain greater visibility into your environment, identify trends and patterns, and make informed decisions to optimize your applications and their infrastructure. You'll also be able to quickly identify and diagnose issues, troubleshoot problems, and resolve incidents which is particularly important in high-traffic environments where log data is generated at a rapid pace and can be overwhelming to manage manually.

This article will provide a comprehensive overview of log aggregation, including its benefits, best practices, and how it fits into the broader context of engineering operations and security. Whether you're just getting started with log aggregation or looking to optimize your existing approach, this article will help you understand the importance of this critical aspect of log management and how to get the most out of it.

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Why is log aggregation needed?

Most non-trivial production systems are composed of several services which are deployed to a significant number of servers with each one generating copious amount of log data. Such data can be stored locally in files, but the need to find a different solution will quickly become apparent when you need to troubleshoot an issue or correlate a problem through your logs.

Aggregating your logs in one place provides several important benefits. The most noticeable one from an engineering standpoint is that you'll no longer need to log into multiple servers to inspect log files which can save many hours when troubleshooting a problem. By collecting logs from multiple sources into a single location, it is easier to manage, search, and analyze the data.

For example, when tracing a request that spans multiple servers, you must review one or more log files for each server that are involved in process of generating a response for that request. Depending on how many services are involved, and how complex the request is, this can take a bit of time as you'd have to find the exact servers that the request was routed to and track the request in the logs through some sort of ID.

With a centralized logging system in place, this process is greatly simplified . You'll typically only need to create a filter based on the request ID which will then display only the relevant logs regardless of what servers they originated from. This is usually the major reason for switching to a centralized logging solution, but there are other benefits too such as the following:

1. Improved visibility and insights

Log aggregation provides a centralized view of your organization's entire log data. This makes it easier to identify patterns, detect anomalies, and diagnose issues, providing greater visibility and insight into the behavior of applications, services, and infrastructure.

When logs are collected from multiple sources, it is possible to see patterns, trends, and correlations that might otherwise be missed. For example, if logs are aggregated from several servers, it is possible to see if there is a trend of increasing errors on a particular server, or if there is a common issue affecting multiple servers. This information can be used to identify and resolve problems more quickly and efficiently.

2. Enhanced troubleshooting

When it comes to troubleshooting, log aggregation plays a significant role by providing a comprehensive view of the system and infrastructure. This is because log data from multiple sources can be analyzed together, providing a more comprehensive picture of what is happening in the environment. You'll be able to quickly search, query, and filter log data in real-time, making it possible to quickly pinpoint problems and take corrective actions. This helps to save valuable time and resources that would have otherwise been spent on manual log searches, correlation and analysis

3. Real-time monitoring and alerting

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Taking advantage of centralized log management solutions allows you to monitor logs in real-time and set up alerts based on specific events and patterns. This helps with proactively identifying potential issues and solving them quickly to avoid or reduce downtime, which improves the overall availability and stability of your systems. Most solutions also support setting up dashboards and reports for viewing the state of a service or the overall system at a glance and sharing with other relevant stakeholders.

4. Better compliance

Log aggregation is an important tool for ensuring compliance with various regulations and standards, such as security and privacy laws. By collecting and centralizing logs from various sources, you will have a comprehensive view of the system and infrastructure, making it easier to track and audit activity. It also makes it easy to prove to auditors and regulators that you are following the required policies and procedures to ensure compliance with regulatory standards.

5. Increased efficiency

Log aggregation can also increase team efficiency by automating the process of collecting, analyzing, and storing log data. This reduces the manual effort required to manage log data, freeing up IT teams to focus on more strategic tasks.

How does log aggregation work?

Log aggregation can be a complex process, but it is essential for organizations that want to effectively manage and analyze log data. There are several steps involved in the log aggregation process, and it is important to understand each step to ensure a successful implementation.

By following a structured approach, such as the one outlined in this section, you can ensure that your log aggregation process is efficient, effective, and meets your needs. Now, let's take a closer look at the steps involved in log aggregation and how you can go about them.

1. Determine the types of logs you need to collect

This is the first step in the log aggregation process and it is a critical one as different logs are useful for generating different insights. Essentially, you need to identify the types of events you want to track and monitor, depending on your use cases. Some common types of logs that you may need to aggregate include the following:

  • Application logs
  • Web server logs
  • Operating system logs
  • Security logs
  • Network logs
  • Database logs
  • Cloud platform logs
  • Load balancer logs
  • Infrastructure logs
  • Backup and recovery logs
  • Authentication logs
  • DNS logs
  • Router and firewall logs

Once you have identified all the types of logs you need to collect, you can move on to the next step.

2. Identify the log sources

This step involves finding all of the sources that produce the logs you want to collect and aggregate. Common log sources include servers, applications, network devices, databases, containers, and cloud platforms. A complete and comprehensive log aggregation strategy can only be realised when you identify all the important log sources in your environment.

Knowing the log format and location of each log source is another crucial step to the log aggregation process. This allows you to properly collect, parse and aggregate the logs that are being generated. In some cases, you may need to modify the log format or location of certain log sources to make them compatible with your log aggregation tool.

3. Choose a log management solution

There are many different log management solutions available, so it is important to choose one that is compatible with your log sources and meets your needs. Some common aggregation tools include the Elastic Stack, Amazon CloudWatch, Logtail, Graylog, Splunk and others. You should evaluate each tool based on its features, compatibility with your log sources, and ease of use to find the best solution for your organization. In the next section we will discuss some criteria to consider before deciding on which solution to use.

4. Collect, parse and transport your logs

Once you have identified your log sources and chosen your log management solution, you need to collect and normalize logs from each source, and transport them to centralized location. This typically involves setting up a log collector to capture logs from each source, parse them, and forward them to a centralized repository for storage and analysis. Examples of log collectors include Vector, Rsyslog, Fluentd, Logstash, Beats, and others.

Before choosing a log collector, you need to consider several factors such as compatibility with your log sources, ease of use, performance (given the volume of logs you need to collect), and security. You should also consider if the log collector provides the necessary features for parsing and normalizing the logs, and how well it integrates well with your log aggregation solution.

5. Process the logs

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Once your logs have been ingested into your logging solution of choice, they typically undergo several processing steps to make the data more useful and easier to analyze. Some of the common processing steps are:

  1. Parsing: If the data coming from the log collector isn't in the desired format, the parsing step can be often be done in the log management tool. Parsing involves turning raw data into a structured format, such as JSON, so that key fields, such as timestamps, error messages, and request URLs, can be easily extracted and store them in a format that is easy to query.

  2. Filtering: After the log data is parsed, you may want to filter it based on specific criteria, such as log level or error message. Filtering helps you focus on the log data that is most relevant to your needs and eliminates noise from the data.

  3. Data enrichment: You can add additional context to your log data by enriching it with information from other sources, such as metadata from AWS services or customer data from databases. This allows you to gain a deeper understanding of the data and make better informed decisions.

  4. Masking: This is the process of obscuring sensitive information in logs before they are stored or transmitted. The log collector is usually responsible for this but it can also be done in the log management tool. Ideally, logs produced shouldn't contain sensitive information but this isn't always possible so ensure to set up log masking to avoid leaking sensitive data to unauthorized parties.

  5. Metrics generation: Log data can be aggregated to provide a summarized view of the data which is useful for monitoring, analysis, or troubleshooting. For example, you can aggregate log data to count the number of errors by type or to track the average request latency over time.

6. Archive your logs

Log removal and archiving are important components of the log aggregation process. It helps you manage the volume of log data, maintain the performance and efficiency of your log management tools, and ensure that important log data is retained for as long as they are needed.

Typically, a log management solutions will allow you to choose your log retention policy which determines how long they will be kept before they are removed or archived. The retention policy will depend your organization's requirements, such as regulatory compliance, legal requirements, and data privacy policies. Different types of logs can also have different retention policies.

Once the retention policy is exceeded for a set of log data, it can be deleted to free up space or compressed and archived on-premises, in the cloud, or using a third-party log archiving service. Archiving is the process of storing logs that are no longer needed for active analysis but may still be needed for regulatory, compliance, or auditing purposes.

Factors for choosing a log management solution

Choosing a centralized log management solution can be a complex process, as there are many factors to consider. Some of the key factors to take into account include:

  1. Data Volume: Consider the amount and type of log data you need to manage. Some solutions are better suited for smaller data sets, while others are designed to handle large, complex log data.

  2. Scalability: Consider your future needs, as log data can grow quickly. Ensure that the solution you choose is scalable and can accommodate increasing data volume over time.

  3. Compatibility: Make sure the solution you choose is compatible with your existing IT infrastructure, including your operating systems, applications, and security tools.

  4. Data Retention: Consider the length of time you need to retain log data, as some solutions may have data retention limitations. Ensure the tool also provides a convenient way to compress and archive old logs.

  5. Search and Analysis: Look for a solution that provides advanced search and analysis capabilities, so you can quickly find and resolve issues. Consider factors such as the ability to search log data using keywords and filter based on specific criteria (such as log levels).

  6. Integration: Consider the level of integration you need with other tools, such as security and monitoring solutions, and ensure that the solution you choose can easily integrate with these tools.

  7. Security: Ensure that the solution you choose provides strong security features, such as data encryption and user authentication, to protect your log data in transit and at rest. Look for compliance with GDPR and SOC 2 in whatever solution you choose.

  8. Cost: Consider the cost of the solution, including both upfront and ongoing expenses.


If you're looking for a log management solution that provides centralized logging, reliable storage, and efficient processing, look no further than Logtail. Our solution offers a range of features that make it the right choice for organizations of any size and industry. With real-time data analysis, you'll be able to quickly identify patterns and gain insights that can improve your operations. And with flexible data retention policies, you can make sure that your logs are stored for as long as you need them.

Whether you're looking to comply with industry regulations or simply want to get more value from your log data, our log management solution is designed to meet your needs. So why wait? Get started today and see the benefits for yourself!

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