How do you analyze log data for relevant information?

Log files can contain enormous amounts of potentially useful information, but without log data analysis and log filtering, it can be difficult to sort, prioritize and read.

In order for an IT professional to analyze log data effectively, it's important to find details, events or activities of interest. Fortunately, even the most rudimentary log tools and viewers can provide log filtering and search capabilities.

IT pros rely on logs to collect data that informs troubleshooting, optimization, systems management, enterprise security and regulatory compliance. But logs can become enormous files that contain a bewildering amount of information. Sorting through log files can be cumbersome and time-consuming, so it's critical to analyze log data with log filters.

Consider the importance of unique identifiers, such as user IDs, which could be a user's email name or another username associated with logged transactions. Administrators can analyze log data with log filters to search against unique identifiers to find specific actions or events associated with a particular user, system or another identifier in a select period of time.

IT staff can quickly examine what a particular user or system has done. For example, IT staff can see if a user tried to access a restricted file or system, or find if a specific system or device isn't responding or returns unexpected errors.

Aggregation and analytics enhance log filtering

The power of log filtering and searching against unique identifiers is even more effective when IT staff analyze log data across multiple aggregate logs. Log aggregation and analytics tools can enable the same search to locate corresponding log activities taking place in other systems, services and applications, as long as those respective logs are available for aggregation. This way, IT staff can obtain a much more detailed cause-and-effect view of user activities and responses.

Everything you need to know about effective logging

Design a logging strategy that focuses on business needs to prioritize data collection. Consolidate and store those logs to streamline use and access, but also keep best practices in mind. Use logging standards to reinforce security and performance policies.

Log analytics tools can also add custom labels or tags. Tags offer a convenient way to identify specific or important events in the environment.

Log tools that support tagging can apply a tag to a more complex or involved query. This means tags aren't simply a way to highlight a particular log entry, but they can be used to spot important combinations of activities or events that are relevant to the organization, such as a storage latency warning on a critical storage volume. IT staff can then search or filter against tags to quickly locate instances of corresponding events, or even receive alerts when specific tagged events occur.

Analyze log data with log filters that use identifiers and tags to accelerate analysis and troubleshooting. This will help identify issues and resolve problems much faster.

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