Senior Application Engineer at a comms service provider with 11-50 employees
Real User
Top 5
2025-06-20T11:54:48Z
Jun 20, 2025
A use case for using Logstash that we have involves integration servers that log in files in a non-transformed way. We have more than four servers that log in files, and when we have an issue, we can't determine whether it originated in IS1, IS2, or IS3. To address this, I installed Filebeat, which is the agent that installs in servers that log. Filebeat sends the logs to Logstash, and the role of Logstash here is taking the logs and transforming these logs in a better way. For example, if we have a request and response, it puts a request field in a separate field, the email and user in a separate field, and the execution time in a separate field. All these separations or transformations of logs help the operation teams investigate issues to determine the root cause and also help management extract reports, insights, and analytics, which aid us in reporting.
Business Unit Head at Cyber Knight Technologies FZ LLC
Reseller
Top 20
2025-03-11T12:25:54Z
Mar 11, 2025
I am considered an expert in Elastic Observability ( /products/elastic-observability-reviews ) in the Middle East. During my experience, I have worked heavily on Logstash ( /products/logstash-38586-reviews ). As the official distributor for Elastic in the Middle East, I have integrated Logstash ( /products/logstash-38586-reviews ) with various systems.
We already use the Elasticsearch system. Our system is faster than version seven. Version seven does not have very special functions. We don't have the Elastic Agent. We are now using Beats, and it's not very good for importing data. We must upgrade to version eight. The system is quite large. We have three or four Logstash servers for high availability.
I use Logstash primarily for connecting logs from hardware. This is the main use case. The second use case involves making correlations between logs from various sources.
Log Management is the practice of collecting, storing, and analyzing log data from various sources within an IT environment to improve security, compliance, and operational efficiency.
Efficient Log Management allows organizations to detect anomalies, troubleshoot issues, and ensure compliance with industry regulations. Logs come from diverse sources, including servers, applications, and network devices. Handling and analyzing this data effectively can offer significant insights into system...
A use case for using Logstash that we have involves integration servers that log in files in a non-transformed way. We have more than four servers that log in files, and when we have an issue, we can't determine whether it originated in IS1, IS2, or IS3. To address this, I installed Filebeat, which is the agent that installs in servers that log. Filebeat sends the logs to Logstash, and the role of Logstash here is taking the logs and transforming these logs in a better way. For example, if we have a request and response, it puts a request field in a separate field, the email and user in a separate field, and the execution time in a separate field. All these separations or transformations of logs help the operation teams investigate issues to determine the root cause and also help management extract reports, insights, and analytics, which aid us in reporting.
I am considered an expert in Elastic Observability ( /products/elastic-observability-reviews ) in the Middle East. During my experience, I have worked heavily on Logstash ( /products/logstash-38586-reviews ). As the official distributor for Elastic in the Middle East, I have integrated Logstash ( /products/logstash-38586-reviews ) with various systems.
We already use the Elasticsearch system. Our system is faster than version seven. Version seven does not have very special functions. We don't have the Elastic Agent. We are now using Beats, and it's not very good for importing data. We must upgrade to version eight. The system is quite large. We have three or four Logstash servers for high availability.
I use Logstash primarily for connecting logs from hardware. This is the main use case. The second use case involves making correlations between logs from various sources.