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Top 5 Most Common Ways of Using Log Data for Performance Management

Trevor Parsons

Logentries identified the top five most common ways that log data is used for monitoring and analyzing system performance.

Our research team looked across more than 25,000 log management and analytics users, tracking more than 200,000 shared patterns, and identified the top five areas that are most frequently analyzed for performance-related issues. The top five pattern categories for performance monitoring included:

1. Slow Response Times

Response times are one of the most common and useful performance measures that are available from your log data. They give you an immediate understanding of how long a request is taking to be returned.

2. Memory Issues and Garbage Collection

Out-of-memory errors can be catastrophic when they occur as they often result in an application crashing due to lack of resources.

3. Deadlocks and Threading Issues

Deadlocks can occur in many shapes and sizes and can have negative effects when they occur - from bringing your system to a complete halt to simply slowing it down.

4. High Resource Usage (CPU/Disk/ Network)

In many cases, lower system performance may not be a result of any major software flaw, but can be a simple case of system load increasing without increasing resources available to manage the increased demand.

5. Database Issues and Slow Queries

One of the most common areas for slow system performance can be a result of long-running database queries. Once identified, these queries can be optimized for significant performance improvements. Setting acceptable thresholds for query time and reporting on anything that exceeds these thresholds can help you quickly identify when your users experience is being effected.

Trevor Parsons, PhD, is Co-founder and Chief Scientist of Logentries.

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Top 5 Most Common Ways of Using Log Data for Performance Management

Trevor Parsons

Logentries identified the top five most common ways that log data is used for monitoring and analyzing system performance.

Our research team looked across more than 25,000 log management and analytics users, tracking more than 200,000 shared patterns, and identified the top five areas that are most frequently analyzed for performance-related issues. The top five pattern categories for performance monitoring included:

1. Slow Response Times

Response times are one of the most common and useful performance measures that are available from your log data. They give you an immediate understanding of how long a request is taking to be returned.

2. Memory Issues and Garbage Collection

Out-of-memory errors can be catastrophic when they occur as they often result in an application crashing due to lack of resources.

3. Deadlocks and Threading Issues

Deadlocks can occur in many shapes and sizes and can have negative effects when they occur - from bringing your system to a complete halt to simply slowing it down.

4. High Resource Usage (CPU/Disk/ Network)

In many cases, lower system performance may not be a result of any major software flaw, but can be a simple case of system load increasing without increasing resources available to manage the increased demand.

5. Database Issues and Slow Queries

One of the most common areas for slow system performance can be a result of long-running database queries. Once identified, these queries can be optimized for significant performance improvements. Setting acceptable thresholds for query time and reporting on anything that exceeds these thresholds can help you quickly identify when your users experience is being effected.

Trevor Parsons, PhD, is Co-founder and Chief Scientist of Logentries.

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Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

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Azul

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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