Request Metrics vs. Splunk Application Performance Monitoring (APM)

Request Metrics is great for small web development teams that want to make fast web applications. It was quick for us to get started and we could use the reports right away without having to read through documentation. If you just need to get some performance metrics, Request Metrics is perfect. It would not be so good for a larger team or a complex backend application as it is pretty limited in what it can measure.

One area in which Splunk Application Performance Monitoring was able to help our organization was when we transitioned one of our applications to the cloud. It allowed our team to understand how different factors impacted our application once it was moved to the cloud. This visibility gave us some incite on changes that were required in order to make our application perform better.

Incentivized

• Performance charts are really simple and easy for us to understand what is happening
• It was easy to get started and doesn't need administration or training
• It's affordable for our team
• It's fast

• Splunk Application Performance Monitoring integrated all layers of traffic and logs and gave a single panel of troubleshooting
• Splunk Application Performance Monitoring help a lot to address layer 7 (Application layer) of network traffics

Incentivized

• I wish that it could also do uptime checking of the site
• There is not enough detail to drill into individual users

• Sometimes the OS process takes lots of CPU and Memory. When we have to restart that Splunk process on those local hosts
• More user friendly Web interface will be nice to have
• a PDF format option will be good

Incentivized

Splunk is a great tool for log mining. It is less time-consuming and easy to use. It provides high security, it has customisable dashboards. Furthermore, it acts as a search head, and it gives real-time status. It has the ability to collect data from any source and multiple sources, and it can correlate them.

Incentivized

We also consider Speedcurve and Calibre for monitoring. Speedcurve was really nice, but the reports were slow. We had to wait a lot to get information. It was also out of our budget and would require extra justification to use it. Calibre was also nice, but the numbers were based on synthetic rather than real user performance. We felt that this wasn't as helpful for us.

It is good that the correlation analysis and the cause of the failure can be analyzed more extensively through the collection of many data. It is good because it provides a user interface (usability) well and can be used conveniently.
It is good because it can utilize anomaly detection through various AI-based ML models.

Incentivized

• The launch of our project dashboard was much smoother and more successful because we could fix problems earlier
• It fit without our existing operations budget

• The ability to resolve issues in real time increased for us.
• The ability to see the issues before they start to happen by monitoring trends improved our uptime.
• The visual component increases team collaboration

Incentivized