In the world of computing, logs are an entity automatically appearing when your system registers an event. Log files come with a time stamp and usually record anything happening behind the scenes in operating systems or software applications. In summary, logs track everything the server, network, OS, or application deems worth documentation. They may carry records of several kinds of events, including messages and transactions exchanged between users or chronicles from a backup. They also record errors interrupting or interfering with a running application and even carry a record of the files requested by website users.
Log files are instrumental in reporting details like what went wrong when a system suddenly stops working, and they help you track and monitor changes made to your system. They constitute an essential aspect of a network system, as they’re useful in searching for and understanding errors, crashes, and exceptions in applications, and they can be crucial to system security. However, log files can accumulate terabytes of raw and unfiltered data in a single day. Frequently, programmers have to sift through line after line of logs, trying to analyze what caused the code abnormalities to lead to an error or exception.
Log management tools can help you gather a better overview of an application’s data. Though each tool has its own merits, here’s a detailed comparison between SolarWinds® Loggly®, SolarWinds Papertrail™, and Logstash to help you understand which one best suits your needs.
Comparison Between Loggly, Papertrail, and Logstash
Features Face-Off—Loggly, Papertrail, and Logstash
These tools differ in terms of look and feel, but they primarily work toward log management and have the same core functionalities. Let’s look at what sets them apart in each of the parameters.
Log Management: Loggly reformats log files into a standard format to process records from several sources. This enables you to monitor events across your system, irrespective of the operating system or methodology used to generate records. Papertrail, on the other hand, centralizes log file data in one place, so it acts as a log aggregator for text-based logs. It has unique file content filtering capabilities designed to extract records by date to help you with your event management tasks. Logstash alone doesn’t ensure meaningful and centralized log file management. This tool creates source files for analysis through other platforms, and you have the flexibility to choose where and how you want to project your data.
Log Tailing: Loggly has a live tail feature designed to let you monitor and filter incoming log data for near real-time updates. It leverages pattern-based filtering using regular expressions and color-coding, giving you the option to group or ungroup similar events. Papertrail also boasts a live tail event viewer offering real-time updates and instant visibility into your devices, apps, and services. You can filter incoming messages by time period, origin, or message content and set comprehensive access control permissions to limit users. You can even use Papertrail CLI to tail your logs from the command line itself, which makes it an intuitive tool. You can use Logstash in combination with Kibana to keep tabs on the logs streaming in real time. It offers a log categorization view within the UI to help you identify similar logs and see trends, eradicating the need for a manual search. Like the other two, it also groups events together based on messages and formats, making them easy to analyze.
Analysis and Visualization: With Loggly, you can analyze and visualize your data to create charts for log event counts, averages, percentiles, and more. Answer key questions, spot trends, and track SLA compliance using filters for structured, unstructured, and semi-structured log data to fit your monitoring needs. The instinctive log velocity analytics tool in Papertrail provides a quick visualization of log throughput for new or saved searches. You can identify patterns or anomalies capable of causing a spike in the last 10 minutes, spot trends over the previous two weeks, or jump to a specific time (in two clicks), reducing the amount of time it takes to troubleshoot errors. Leverage Kibana to unravel the visualization capabilities in Logstash and centralize, parse, and transform your data. Elasticsearch and Kibana can be used in combination with Logstash to create an interactive dashboard from raw data and derive relevant value.
Notifications and Alerts: Loggly allows you to specify which circumstances you want to trigger an alert. You can also leverage the saved search feature, which describes each condition you want to monitor. Papertrail also lets you save search queries and create custom alerts for them, allowing you to differentiate an exceptional error from the sea of regular error notifications. To derive relevant alerts, Logstash has to be used in collaboration with Kibana to see, search, and filter your alerts from a central location. Doing so also allows you to customize triggers on the dashboard for a holistic view.
Most log management systems come with their own set of properties but offer similar features (i.e., aggregating logs in a unified format on a dashboard and highlighting errors and exceptions for resolution). The onus lies with the team to identify and zero in on the tool best suited to their requirements. While Loggly provides a unified log analysis and monitoring solution with extensive monitoring and analysis capabilities, Papertrail offers ease of use, an intuitive interface, and a customizable display with a long-term archive. On the other hand, the open-source nature of Logstash brings with it an ever-growing plug-in environment with highly available and flexible documentation and design. At different price points, it’s up to each organization to figure out which standout feature they value the most.
*As of June 2020