As a software engineer, Splunk helps me debug issues in my microservice applications. The Splunk forwarders are efficient and quickly collect logging from multiple server instances. The timestamp resolution is precise making it easier to track down race conditions. The reporting and pivot tables are powerful ways to visualize frequency of api calls once you learn the syntax.

As a developer/operations team member i felt this tool is excellent to analyse any logs or texts

Mainly checking code for Fatal errors and application error which does not break in development environment.

As a user of Splunk, we generally used to monitor the log provided by the server clusters belonging to a tool called API Connect. As the logs are stored in Splunk, we tally the transaction count from API Connect tool and filter the log search in Splunk with a particular search query. We can download the logs of particular time and date of API Connect servers in case of transaction count issues. We create a dashboard for all the individual API's transaction count in terms of total transaction count of all API's. In this way, it makes our work easier to find out which API has the highest transaction count. We even use Splunk to know the state of the machine. Reports generated by the Splunk helps us to find out the API with the highest response time. In this way, Splunk makes our work a lot easier as it is very fast and highly secure.

Splunk has been key in sever major issue root causes by analyzing logs and from that being able to build reports and determine causes of issues. In addition being able to trend and look for the data in the many logs is very helpful.