Associate Consultant at a computer software company with 1,001-5,000 employees
Consultant
Top 10
2025-07-18T08:34:48Z
Jul 18, 2025
Customization can be automated with Logstash, but it is at the developer's disposal. The developer has to do it, not the tool as such. There is scope for optimization, but that is all outside the tool, which I have to plug into the tool. I am not able to think of any specific disadvantage of Logstash as such, but the implementation can be made more user-friendly. There can be a UI to implement with Logstash. Currently, I have to work with config files and everything.
Assistant Vice President at QualityKiosk Technologies Pvt. Ltd.
Reseller
Top 5
2025-03-11T12:25:54Z
Mar 11, 2025
Logstash lacks a graphical user interface, necessitating a strong programming background to handle it effectively. It is challenging for business users who need a skilled team for its operation. Changing pipelines is not easy because Logstash requires pipelines to be programmed and cannot just be dragged and dropped like other data solutions. Additionally, Logstash does not automatically make actions based on the data it receives; integrating automation tools is required.
Almost all the research can be very bad. We still have a problem with importing the log system. The earliest type of Syslog data requires creating ingest pipelines, and that work is very difficult for our support vendors and us. The system was created by the support vendor. After importing the log, indexes can be created. In Elasticsearch, we must create an ingest pipeline before importing log files. This is a problem for us. Some log files must be changed frequently. We need to create this long ingest pipeline set each time. That's a problem for us.
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...
Customization can be automated with Logstash, but it is at the developer's disposal. The developer has to do it, not the tool as such. There is scope for optimization, but that is all outside the tool, which I have to plug into the tool. I am not able to think of any specific disadvantage of Logstash as such, but the implementation can be made more user-friendly. There can be a UI to implement with Logstash. Currently, I have to work with config files and everything.
An enhancement we could implement is the ability to cluster Logstash to exist in more than one node.
Logstash lacks a graphical user interface, necessitating a strong programming background to handle it effectively. It is challenging for business users who need a skilled team for its operation. Changing pipelines is not easy because Logstash requires pipelines to be programmed and cannot just be dragged and dropped like other data solutions. Additionally, Logstash does not automatically make actions based on the data it receives; integrating automation tools is required.
Almost all the research can be very bad. We still have a problem with importing the log system. The earliest type of Syslog data requires creating ingest pipelines, and that work is very difficult for our support vendors and us. The system was created by the support vendor. After importing the log, indexes can be created. In Elasticsearch, we must create an ingest pipeline before importing log files. This is a problem for us. Some log files must be changed frequently. We need to create this long ingest pipeline set each time. That's a problem for us.
The product needs to improve its compatibility.