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It can be more difficult and time-consuming to discover useful information within unstructured logs.
Not every parsing tool can handle the wide range of log formats your applications and services generate daily.
Manual log file parsing tends to be impractical for techs with an average number of applications.
Without the proper software, tech pros will struggle to gain insights from their unstructured log data. The logging tools in SolarWinds® Papertrail™ can automatically parse most event logs into individual data tokens to help declutter data. This feature helps users sort, filter, and search through events using a simple UI. Compared to manually configuring parsing rules for log data, this ease of access is designed to save users time. What’s more, the tool comes with built-in support for most common log types. With faster parsing of logs across a network, users can more quickly discern potential security risks, generate log files to comply with auditors, and speed up root cause analysis.
Sign up for a free planUsers often struggle to deal with the many different log formats their servers and applications generate daily. The Papertrail automatic log parsing feature is compatible with many types of log data including Apache, Nginx, JSON, and more. This format flexibility allows users to receive features like statistical analysis on value fields, faceted search, filters, and more. For situations when automated parsing is unavailable for specific logs, users can run full text searches to view specific logs. Additionally, Papertrail has a “show logs” feature, which allows users to jump straight from a log analysis view to view parsed logs from various sources.
Sign up for a free planIn server- and application-heavy environments, large volumes of log data are constantly generated and need to be parsed quickly. This can often be taxing for networks unprepared for the increased workload. Luckily, Papertrail offers a cloud storage feature to help you offload log storage. As log volume grows, the cloud storage allotment can be scaled automatically according to your needs. With this flexibility, aggregating and parsing large loads shouldn’t affect normal application performance. Customizable scaling can also help prevent unauthorized users from reading log data during the parsing process, when syslog traffic is at its highest and needs to be isolated.
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