Splunk APM is a robust tool with many capabilities. There are always areas for potential improvement to enhance its functionality and user experience. For Splunk APM, there could be simplified navigation, like streamlining the user interface to make navigation more intuitive for our users, especially those new to APM, which can enhance usability. We can provide more customization options for dashboards and visualizations to help users tailor the platform to their specific needs. There could be more integration capabilities with a wider range of third-party tools and platforms would also be beneficial. By focusing on these areas, Splunk APM can enhance its value proposition, improve user satisfaction, and better meet the evolving needs of organizations monitoring their application performance.
In our company's case, we have some very high throughput services, so they might be getting 10,000 requests per second. Currently, Splunk APM and Splunk Observability want to do things in a way that wants you to send every single span for every single request that is a part of the 10,000 requests per second. The process may give you all the data in the back end, but a lot of data, including CPU memory and network costs, is involved in sending data to Splunk. My feeling is that it would be nice if there were an easier way to send only a sample of my traces, which means that I send 10 percent or 5 percent, and then Splunk would extrapolate on the back end. It is obvious that with 10 percent of traces, the real metrics are something like ten times with a plus or minus margin of error. I am okay with the plus or minus margin of error because I think when you have a high enough request rate, you will see such problems appear even in a lower sample population. The process is political polling. You don't call all 150,000,000 people in the US and ask them who they are going to vote for, and I feel it is better if you choose to take a sample of maybe 10,000 and then extrapolate your findings to the rest. I feel the same should be applicable to trace something in Splunk APM.
We currently lack log analysis capabilities in Splunk APM. Implementing this functionality would be very beneficial. With log analysis, we could eliminate our dependence on Splunk Enterprise and rely solely on APM. The user interface design of APM seems intuitive, which would likely simplify setting up log-level alerts. Currently, all log-level alerting is done through Splunk Enterprise, while infrastructure-level alerting has already transitioned to Splunk APM. The Splunk APM documentation on the official Splunk website could benefit from additional resources. Specifically, including more examples of adapter creation and management using real-world use cases would be helpful. During our setup process, we found the documentation lacked specific implementation details. While some general information was available on public platforms like Google and YouTube, it wasn't comprehensive. This suggests that others using Splunk APM in the future might face similar challenges due to the limited information available on social media. It's important to remember that many users rely on social media for setup guidance these days.
Enhancing system availability and optimizing service performance are crucial. It is essential for the monitoring tool to deliver quick response times when generating analytical reports, instead of prolonged delays.
Works at a tech company with 1,001-5,000 employees
Real User
Top 10
2023-07-14T14:16:00Z
Jul 14, 2023
They can improve the flow system and the keyword language. It has predefined keywords, but they can be improved. I also use LogMeIn where I can use predefined keywords to see the logs. They should give us the option to use our own language to search. For example, I should be able to search for an ID name along with an error or status code.
Splunk APM's performance could be improved - at the moment, it's very slow and takes forever to give me what I want. Its documentation and accessibility to end-users could also be better.
Manager IT Solutions at a pharma/biotech company with 10,001+ employees
Real User
Top 20
2023-03-09T22:09:48Z
Mar 9, 2023
We can't really configure the solution. The UI enhancements could be a way to improve the solution in the future. We'd like the solution to be better integrated with Splunk Cloud.
Splunk APM is a comprehensive application performance monitoring solution that provides real-time insights into the performance and availability of your applications.
It offers end-to-end visibility across the entire application stack, from the front-end user experience to the back-end infrastructure. With Splunk APM, you can proactively identify and resolve performance issues, optimize application performance, and ensure a seamless user experience.
Splunk APM leverages...
Splunk APM is a robust tool with many capabilities. There are always areas for potential improvement to enhance its functionality and user experience. For Splunk APM, there could be simplified navigation, like streamlining the user interface to make navigation more intuitive for our users, especially those new to APM, which can enhance usability. We can provide more customization options for dashboards and visualizations to help users tailor the platform to their specific needs. There could be more integration capabilities with a wider range of third-party tools and platforms would also be beneficial. By focusing on these areas, Splunk APM can enhance its value proposition, improve user satisfaction, and better meet the evolving needs of organizations monitoring their application performance.
In our company's case, we have some very high throughput services, so they might be getting 10,000 requests per second. Currently, Splunk APM and Splunk Observability want to do things in a way that wants you to send every single span for every single request that is a part of the 10,000 requests per second. The process may give you all the data in the back end, but a lot of data, including CPU memory and network costs, is involved in sending data to Splunk. My feeling is that it would be nice if there were an easier way to send only a sample of my traces, which means that I send 10 percent or 5 percent, and then Splunk would extrapolate on the back end. It is obvious that with 10 percent of traces, the real metrics are something like ten times with a plus or minus margin of error. I am okay with the plus or minus margin of error because I think when you have a high enough request rate, you will see such problems appear even in a lower sample population. The process is political polling. You don't call all 150,000,000 people in the US and ask them who they are going to vote for, and I feel it is better if you choose to take a sample of maybe 10,000 and then extrapolate your findings to the rest. I feel the same should be applicable to trace something in Splunk APM.
Splunk's functionality could be improved by adding database connectors for other platforms like AWS and Azure.
We currently lack log analysis capabilities in Splunk APM. Implementing this functionality would be very beneficial. With log analysis, we could eliminate our dependence on Splunk Enterprise and rely solely on APM. The user interface design of APM seems intuitive, which would likely simplify setting up log-level alerts. Currently, all log-level alerting is done through Splunk Enterprise, while infrastructure-level alerting has already transitioned to Splunk APM. The Splunk APM documentation on the official Splunk website could benefit from additional resources. Specifically, including more examples of adapter creation and management using real-world use cases would be helpful. During our setup process, we found the documentation lacked specific implementation details. While some general information was available on public platforms like Google and YouTube, it wasn't comprehensive. This suggests that others using Splunk APM in the future might face similar challenges due to the limited information available on social media. It's important to remember that many users rely on social media for setup guidance these days.
The licensing model is expensive. We need to monitor the amount of data ingested because the cost is based on the data collected.
Enhancing system availability and optimizing service performance are crucial. It is essential for the monitoring tool to deliver quick response times when generating analytical reports, instead of prolonged delays.
They can improve the flow system and the keyword language. It has predefined keywords, but they can be improved. I also use LogMeIn where I can use predefined keywords to see the logs. They should give us the option to use our own language to search. For example, I should be able to search for an ID name along with an error or status code.
Splunk APM's performance could be improved - at the moment, it's very slow and takes forever to give me what I want. Its documentation and accessibility to end-users could also be better.
We can't really configure the solution. The UI enhancements could be a way to improve the solution in the future. We'd like the solution to be better integrated with Splunk Cloud.
It's a little bit technical. The cardinality is pretty low. They need to expand their reach.
The monitoring of workloads when using SignalFx could be improved.