Operations | Monitoring | ITSM | DevOps | Cloud

One of the benefits of using Logstash in your data pipelines is the ability to transform the data into the desired format according to the needs of your system and organization. There are many ways of transforming data in Logstash, one of them is using the mutate filter plugin. This Logstash filter plugin allows you to force fields into specific data types and add, copy, and update specific fields to make them compatible across the environment.

In the previous post, we discussed the various environments that Log360 helps you audit and secure. Having established the ease of Log360’s use and the breadth of its auditing scope, now we’ll examine some of the critical areas it can help you monitor. With over 1,000 predefined reports and alerts for several crucial types of network activity, Log360 provides comprehensive network auditing.

The use cases and requirements of a logging platform in an organization varies between teams and job functions. The problem isn’t in collecting log data (we are a logging company after all), but in deciding how to manage these logs for each team. For example, our backend developers need detailed, short-lived logs in order to build and test new features; while our infrastructure team needs lengthy retention periods for auditing and compliance.

Looking to learn about Logstash as quickly as possible? This Logstash Tutorial is for you: we’ll install Logstash and push some Apache logs to Elasticsearch in less than 5 minutes. Logstash is a good (if not the) swiss-army knife for logs. It works by reading data from many sources, processing it in various ways, then sending it to one or more destinations, the most popular one being Elasticsearch.

Over the past few years, and coupled with the growing adoption of microservices, distributed tracing has emerged as one of the most commonly used monitoring and troubleshooting methodologies. New tracing tools and frameworks are increasingly being introduced, driving adoption even further. One of these tools is Jaeger, a popular open source tracing tool. This article explores the integration of Jaeger with the ELK Stack for analysis and visualization of traces.

Apache Tomcat is the most popular application server for serving Java applications. Widely-used, mature and well documented, Tomcat can probably be defined as the de-facto industry standard. Some sources put Tomcat’s market share at over 60%! Tomcat is particularly popular for serving smaller applications since it doesn’t require the full Java EE platform. It consumes a relatively small amount of resources and provides users with simpler admin features.

Every developer’s worst nightmare is having to dig through a huge log file trying to pinpoint problems. The troubleshooting most likely won’t stop there. They’ll either have to follow the trail to multiple other log files and possibly on other servers. The log files may even be in different formats. This may go on until one loses themselves completely. Log aggregation is what you need to stop this seemingly never-ending cycle.