Splunk AppDynamics Reviews

The use case for Splunk AppDynamics is mostly for performance monitoring.

I've been using it since 2019, and Splunk AppDynamics has been a very good tool from the beginning. While I haven't seen many new features, it has improved in various places, particularly in identifying transactions and pinpointing the nodes and other applications it uses, such as Apache Kafka or other third-party applications. It clearly creates a mapping of the transaction. It is also more dependable and reliable. I have also seen a couple of extra features for analyzing the transaction. It goes more in-depth in some areas.

The effectiveness of the auto-discovery and mapping in visualizing my application ecosystem is almost perfect. Although it could be improved further, it is currently in very good shape, allowing performance testers to check exactly what is going on, where the transaction is going, where it's spending time, or failing.

My experience with the application performance monitoring capabilities of Splunk AppDynamics has been very good because it gives me all the data I need and provides a very friendly interface, allowing me to showcase any issues to the customer with ease. The feature to copy a hyperlink to the specific timeframe or transaction I want also makes my job easier by allowing me to pinpoint something to an architect or any participant, who can open it up on their screen and easily understand the issue due to the friendly user interface.

Line-of-code-level troubleshooting feature is very helpful. I have used it a couple of times, and it allowed us to diagnose which part of the code seemed to have the issue, although it did make mistakes and didn't pinpoint the errors exactly in some cases. Overall, it's a very nice feature.

Splunk AppDynamics' digital experience monitoring affects my ability to optimize user experience in a very good way because the results I get often need to be transferred to other stakeholders of the project. The friendly and good user interface allows me to show them what I mean by the results and my analysis.

Splunk AppDynamics’ infrastructure monitoring is very good at correlating infrastructure and application performance.

The best feature of about Splunk AppDynamics is its interface, which allows me to see the full transaction, exactly what is happening, from where it starts to where the call is going, all the services involved in a call, and exactly the time it took from each node to each node along with the network delays. It pretty much provides everything a performance tester would need to do profiling of their results.

Splunk AppDynamics has enormous capabilities that allow me to see the memory and CPU usage, along with the garbage collections. In the case of performance issues, it allows me to dig through the transactions and find out what exactly the issue was to alert the architects and developers to address that issue. I am very happy with Splunk AppDynamics.

I don't really use AI-powered anomaly detection and root cause analysis for diagnosing performance issues because it makes many mistakes in my case, due to the nature of my work.  I prefer to do it manually and be aware of what is going on, rather than relying on that.

If it could have a sub-tool for monitoring Apache Kafka lag, it would save me even more time. There are ways to do it now, but a direct way would be faster and better. 

It would be much better if there were a way to search for specific transactions, similar to how Splunk allows, which aids in filtering transactions that show a huge increase in time.

I have been using Splunk AppDynamics since 2019.

In the early years, we had a couple of issues. It is more stable now. I don't see any of those issues anymore. There are no downtimes. I would rate the stability of Splunk AppDynamics as a nine out of ten.

I would rate the scalability of Splunk AppDynamics as a nine out of ten. A few features could be added to reach a perfect score of ten.

Our environment includes multiple locations and multiple departments. In my company, there are many users working with Splunk AppDynamics.

I haven't worked with them directly. I remember the developers contacted them once, and they received answers within one or two days. I would rate their technical support as good.

I have experience with other solutions, but I see Splunk AppDynamics as a top-tier option, with the rest I've worked with falling far below it.

Splunk AppDynamics stands out in the freedom it provides you to visualize everything. You can pretty much monitor anything that comes to your mind. It doesn't specify a way or how to do it. That's very important for me because it makes my job easier. I can configure it or work in thousands of ways. Along with Splunk, you can even see the logs in-depth. You can see exactly what happened at which transaction and where. Other tools don't provide this much depth or this much freedom to do things you want.

Developers did the deployment, not me. As far as I remember, it was done in less than two days. 

The company I work for now has an enterprise solution.

It does require maintenance, but it's not my job. That's other department's responsibility.

We have seen a return on investment from Splunk AppDynamics. To understand the magnitude of it, without it five people would be needed to do the analysis that Splunk AppDynamics enables me to do. Splunk AppDynamics has definitely saved me many hours per week, approximately 50% of the time.

I would recommend Splunk AppDynamics to other users because it has helped me in many ways. It is a very stable and solid tool. It never has false results. I have seen other tools producing wrong results. That's not the case with Splunk AppDynamics. It either works and provides solid results, or it doesn't work and requires maintenance, which is a very important distinction. It has a very nice graphical user interface. It allows someone to interpret things easily. It provides freedom to the user to use it as they want. These are the reasons I would recommend it.

I would rate Splunk AppDynamics a ten out of ten.

In the financial sector, banks primarily use Splunk AppDynamics for monitoring their digital apps, such as mobile banking and internet banking applications. These client-facing applications are the primary usage of this tool.

The main use case with Splunk AppDynamics is infrastructure monitoring. End user monitoring is also considered, but infrastructure is the main component.

The main benefit is that for application performance, sometimes banks face issues related to databases or performance problems. Splunk AppDynamics helps them identify the root cause. Sometimes external calls going to services such as NADRA in Pakistan or other verification services face delays in getting responses from their side. These types of issues are easily identified, and they can pinpoint where the problem lies.

AI-based features were checked in Splunk AppDynamics. The feature is helpful, but unfortunately, the financial sector is not using the full feature cloud version. Mostly deployment is on-premises.

End-user monitoring (EUM) is another area that customers are normally interested in, and it is very helpful.

Saving time is definitely the main point with Splunk AppDynamics for quickly resolving problems. Whenever they are facing an issue, they quickly identify the root cause and can proceed with fixing it. Sometimes if performance issues arise, they can pinpoint where the problem is. These things help with better performance and customer experience is actually better. This definitely helps them to get more financial benefits. If the users and customers are comfortable and happy with the banking apps, they are more loyal to that particular bank. Everyone now, almost all banks, are looking for APM tools. Initially, three or four years back, people were not considering this tool as one of the essential components for their infrastructure, but now everyone is looking for these types of tools.

In terms of improvement potential for Splunk AppDynamics, there is one point that competitors are exploiting, which is the smart agent type of thing. Dynatrace is saying they have a single agent for all types of applications, which is easy to deploy. Splunk AppDynamics still requires different agents for different applications. Splunk AppDynamics has added the feature of the smart agent, but it is not very effective, as my engineers informed. They still need different agents and community-based agents to manage the different applications. Another challenge we are facing is that for some legacy applications, such as those customized applications developed by customers or their local software partners that are built on C++ or other languages, we face issues in monitoring these applications because we don't have any agent. In some cases, we lose deals just because we are not able to monitor the application developed in C++. These types of support should be there in Splunk AppDynamics.

From a functionality standpoint, Splunk AppDynamics is good. There may be some improvements required, especially for dashboarding. People are also using Elastic or Grafana for dashboarding, and they find their dashboarding more appropriate in displaying information in reporting or dashboarding. Splunk AppDynamics can focus on enhancing reporting and dashboarding. They could enhance or integrate with Grafana or any other reporting tools. One customer required historical reporting the way other network monitoring tools provide it in PDF format. They have a historical report that they can generate and present to their management. However, in Splunk AppDynamics, the approach is different. If someone wants historical data, the dashboard is dynamic, so they can identify the time slot, and it is the same dashboard that they got. If they go back to historical data, the same dashboard generates the report, taking a snapshot of that dashboard. There is no detailed reporting in PDF or Excel format as other tools provide. This is another area that requires improvement. The reporting should be detailed in PDF format; right now it is the same interface that the customer is getting on the dashboard.

I have been working with Splunk AppDynamics for three to four years.

I would rate the stability of Splunk AppDynamics as an 8.

For the ability to scale and expand with Splunk AppDynamics, I would rate it 7 or 8. Sometimes customers face resource issues because they have to enhance their infrastructure as local logs and local storage fill up quickly, so they have to clean up.

Technical support for Splunk AppDynamics is fine, so I rate it 10. We are not facing any issues.

Initially, the setup process for Splunk AppDynamics is complex, and teams are facing some challenges in the initial setup. However, now that the team is used to it, it does not look very complex. Splunk AppDynamics can focus on making it smoother.

The main competitors on the market for Splunk AppDynamics are Dynatrace and Elastic.

Still, I think Splunk AppDynamics is better, but slowly and gradually over this last year, I can see that Dynatrace is also gaining penetration in this market. Maybe worldwide, they are also progressing because with every customer now, we are actually facing competition with Dynatrace. Out of four to five customer bases, they are able to get one deal if we are competing in five. Still, we are getting more deals, but they are starting to penetrate into this market.

The features that Splunk AppDynamics is providing are really helpful, but in the Pakistani market especially, it is a costly proposition for the customer. Customers are using third-party tools for security, and Splunk AppDynamics is not very popular here for security.

The main use case for Splunk AppDynamics will be legacy application observability.

Splunk AppDynamics is useful for helping my clients improve business resilience. If you combine Splunk and AppDynamics, the features missing in AppDynamics can be supplemented by Splunk. By streaming telemetry from AppDynamics into the Splunk data lake, you can apply missing AI analysis and provide better service management and predictive analysis, which helps reduce the meantime to resolution.

Combining Splunk and AppDynamics allows for improved features and predictive analysis by streaming telemetry from AppDynamics to Splunk.

None of the features or functions in AppDynamics are very useful or unique nowadays. AppDynamics has stopped in time at least five years ago, so there's nothing unique from Splunk or from AppDynamics nowadays.

The OpenTelemetry part of AppDynamics is not good for a specific reason: AppDynamics is not a native OpenTelemetry. They have collectors that convert OpenTelemetry to be indexed, causing performance problems. Most of the instances of AppDynamics experience outages, especially the larger ones, and I am not happy with that since it cannot cope with current trends.

It is not a question of lacking key functions in AppDynamics; they have all the functions, but the back-end architecture needs a complete update. AppDynamics has existed for many years, and a drastic restructuring is necessary. I have suggested to Cisco or Splunk that they should merge AppDynamics functionalities with Splunk Observability to simplify things.

My thoughts about infrastructure monitoring and the correlation with application performance in AppDynamics is that it is pretty basic with their health rules. It involves human capability to understand the impact on applications, but when it comes to proper observability and root cause analysis, it is non-existent in AppDynamics.

I have been working with AppDynamics for ten years.

For stability in Splunk AppDynamics, I would rate it as a six.

Regarding scalability, I would rate it as a five.

I would rate Splunk's vendor support as an eight. While some staff are not as helpful, there are many who are good and provide a lot of help.

Positive

I currently still work with Splunk, so I have not moved to another vendor.

The setup process depends on whether it is a SaaS or on-premises solution. For SaaS, which is common, I would say it has mid-difficulty since Splunk does most of the setup, but issues arise with needing multiple agents for each technology, making automation challenging.

Regarding pricing for AppDynamics, I would rate it as high cost, but this is primarily because the ROI is very low today rather than the license costs. I work for an MSP and have a massive discount, yet I see better ROI in competitors like Dynatrace, where the benefits to customers are higher.

In my opinion, the main competitors in the market for Splunk AppDynamics are Dynatrace and DataDog, though I do not even consider them serious competitors anymore.

In my opinion, AppDynamics does not have any AI capabilities at all. Anomaly detection is based on an algorithm and is not AI; it is machine learning, which are two different things. They do provide basic anomaly detection based on metrics, not logs, but there is no large language model implemented in LogicMonitor.

My feedback about Splunk AppDynamics Digital Experience Monitoring is that it is adequate and follows standard Digital Experience Monitoring practices. They allow you to combine data from ThousandEyes into the Digital Experience Monitoring or user monitoring, which is a useful feature that helps with root cause analysis when there is an issue affecting user experience. However, there are no enhanced features; it is pretty much out of the box.

In my opinion, the Security Application feature in AppDynamics is quite good. The DevSecOps section is ahead of their main competitors, but not for long. They offered very good code-level monitoring when they launched, but they have not evolved the product, and competitors like Dynatrace and DataDog are catching up.

My final recommendation for Splunk AppDynamics is to decommission it and merge it with Splunk Observability. I would give it a rating of six out of ten. I would not improve anything in AppDynamics; instead, I would decommission it and prefer the functionalities to be merged with Splunk Observability.

I use Splunk AppDynamics for monitoring the infrastructure and the applications, their health and performance, and any bottlenecks on memory or disk, as we have defined many KPIs. There are specific use cases where we need to send data out very fast, and to ensure we are not breaching the SLA, we monitor closely, especially if we need to tune something on our application side. It is primarily for infrastructure monitoring and application monitoring.

The best features of Splunk AppDynamics that I appreciate include the ability to drill down to a specific transaction, which is very useful for analyzing situations. For example, we might have 10,000 transactions in one hour, but if there is only one transaction taking five seconds while all others are processed within nanoseconds, we can drill down into that transaction and see the details, which is very useful for us.

I appreciate the speed and the details that Splunk AppDynamics provides, and the visualization is also good for anybody who is not technical enough to understand where the data is coming from, whether it is a transaction on an API, a web service request, or JMS. Splunk AppDynamics has very good visualization that allows a non-technical person to grasp some basics, such as understanding where we are receiving something from and how it flows.

My thoughts on the AI-powered anomaly detection and root cause analysis in Splunk AppDynamics are that in the first two or three years, it was not very great, possibly because it lacked sufficient data. However, now it suggests possible reasons since it has enough data to identify potential issues, so we do not have to look everywhere. Based on the input we receive from the agent or dashboard, we focus on selected areas, saving us time during investigations and reducing the time from four hours to just one hour.

The time saved is significant as we have gone from four hours to one hour, which means we are saving a lot of time. If there is an issue requiring root cause analysis, we typically look into 10 areas, but Splunk AppDynamics helps us focus on about three or four areas, where we find 95% of the issues based on its suggestions, making it an effective time-saver.

Splunk AppDynamics has indeed helped improve our business resilience by allowing us to carry out proactive maintenance and identifying problems beforehand. We monitor application heap memory thresholds and take corrective actions before any crashes occur, which definitely indicates its effectiveness.

If I consider what can be improved in Splunk AppDynamics, I would point out that it could enhance its reporting capabilities, as it remains very technical. Some business users struggle to create their own dashboards or reports because they are not technical and do not want to dive into the complexities, so making it more user-friendly in the manner of Tableau would be beneficial.

My experience with Splunk AppDynamics is approximately five years.

In comparing Splunk AppDynamics with other vendors, I find that for conjunction monitoring of infrastructure and applications, it is one of the best. However, for pure infrastructure monitoring, tools such as Dynatrace and BMC might be better suited, so the choice depends on your specific use case.

Regarding pricing, I reiterate that I think it is right on target and it is cheaper than Dynatrace.

Regarding how Splunk AppDynamics' digital experience monitoring affects user experience, I think it is similar to other tools such as Dynatrace. From a user experience perspective, all of these applications, including BMC Remedy, have essentially the same layout, so I would not say it has any standout advantage in user experience.

When I assess the infrastructure monitoring of Splunk AppDynamics in correlating infrastructure and application performance, I find it to be better compared to tools such as Dynatrace or BMC Remedy. Splunk AppDynamics excels in monitoring both infrastructure and applications together, offering better insights than when using just infrastructure monitoring tools.

I would recommend Splunk AppDynamics, but my advice is that it depends on what you are trying to monitor. It is best for monitoring both infrastructure and applications together, but if you are monitoring just infrastructure, it might not be right for you, as it is situated in a competitive space alongside tools such as Dynatrace and BMC Patrol. I would rate this product as an 8 out of 10.

We have been using Splunk AppDynamics for around one year and one month and started with just APM pieces for our back-end services and, over time, expanded it to cover business transaction and database monitoring.

The most valuable feature is the end-to-end transaction tracing, which provides genuine insights by allowing users to follow a single transaction across multiple microservices to pinpoint delays or errors, thereby saving hours during major incidents.

The auto-discovery and application mapping feature automatically maps out our entire application technology, showing service dependencies accurately, saving considerable manual configuration time.

The baseline and anomaly detection feature learns what normal looks like for your app, alerting on deviations beyond static thresholds.

A few things genuinely frustrate me about Splunk AppDynamics. First, the UI, while powerful, is dense and not modern compared to products like DataDog or New Relic, requiring a learning curve for new team members. Navigating feels unnecessarily deep, often requiring additional clicks.

Second, the alerting configuration is overly complex. Setting up health roles and policies isn't intuitive, leading to potential alert storms or missed incidents if configured incorrectly.

Lastly, the CPU-based licensing model complicates understanding costs with scaling, necessitating more straightforward processes.

We have been using Splunk AppDynamics for around one year and one month.

My experience with the application performance monitoring capabilities of Splunk AppDynamics has been largely stable. Issues with Splunk AppDynamics performance itself have been minimal. The agents are very reliable once deployed, running automatically without the need for manual intervention.

We contact technical support when we do the implementation and onboarding of Splunk AppDynamics, as it is part of our enterprise contract. Sessions with the solution engineer helped us in defining the initial architecture and sizing, which was fundamental.

We used DataDog previously, which offered a more extensive collection of frameworks, about seven or so. However, we've switched to Splunk AppDynamics for its straightforwardness, simplifying our processes.

The initial deployment is very straightforward if one reads the documentation correctly. All steps are clearly outlined in the documentation, making the setup hassle-free.

Technical support, part of our enterprise contract, assisted us during the implementation and onboarding of Splunk AppDynamics. We had sessions with a solution engineer for initial architecture and sizing, which was beneficial.

Pricing for Splunk AppDynamics is higher, attributed to the additional features it offers over other tools. While the cost is significant given we have around 120 services, it remains manageable and offers the value we're seeking.

Regarding the effectiveness of the features like auto-discovery and mapping, they visualize your application ecosystem. This feature is very useful to us because we don't have to do the manual effort. Using this feature has saved us around 20 to 30% of time. We don't need many people in the environment. If you have four to five people to handle that feature for 400 or 500 products, then we need only one to two people. Thus, it is resource-efficient and saves time.

We use AI-powered features in Splunk AppDynamics such as anomaly detection and root cause analysis. We have Splunk AppDynamics plus Splunk integration apps which eliminate the need for manual checks.

Using the APM, there are features in Splunk AppDynamics which allow for easy troubleshooting of code-level issues, removing the need for manual interventions.

Regarding the downsides of Splunk AppDynamics, we did not have major dislikes; most features are well-appreciated.

Splunk AppDynamics is a solution we recommend to our customers and vendors if they're within Splunk ecosystem, as it saves time and leverages the ecosystem's features.

Our overall review rating for Splunk AppDynamics is 9 out of 10.

We use Splunk AppDynamics for infrastructure, application, and Kubernetes monitoring, as well as private synthetic agents. We use it for all purposes, including as an extension for log monitoring and every extension. We develop any custom extensions as needed.

At present, I am actively working on a private synthetic agent in Splunk AppDynamics, which we have deployed internally in our IKP platform. I am currently working with that by developing Python Selenium scripting.

I have experience with Splunk AppDynamics' Digital Experience Monitoring, including end-user monitoring. For the functionality part in Splunk AppDynamics, I am comfortable with it.

I find all functions valuable in Splunk AppDynamics because I am from the AppDynamics team in my current company. We help with user queries, and the value depends on the use cases, which might be different for each user.

My impression of Splunk AppDynamics' AI-powered anomaly detection is that it functions very well. The anomaly detection gives the exact root cause of what is happening on our server, and for analytics, for every application, we mostly try to configure the analytics to visualize all the things.

Splunk AppDynamics is useful for me and everything is working out fine. Previously, with log monitoring, I might have been a bit unsatisfied with that. As it is integrated with Splunk, that is also very good.

Splunk AppDynamics gives all the metrics that report to AppDynamics, and they work very well and provide precise information from the server. For application performance, it also gives all the business transactions very efficiently. If there are any other things, we can configure them by an extension or manually.

For now, all secure application features in Splunk AppDynamics are good with me. But in the future, I need to go through all of that because while I have experience, it majorly depends on the use cases. I also need to acquire more knowledge on some of the concepts of AppDynamics.

Splunk AppDynamics is very efficient in all those areas. Compared to the cost, it is also very cost-efficient, because that is the main thing for every organization. For all the things concerning metrics, it is also very good for now.

I am somewhat aware of the data collection features in Splunk AppDynamics, but for now, I have not worked on it.

For now, Splunk AppDynamics is a very efficient tool. However, we have a slight complexity where for infrastructure we have to go to one agent, for the database we have to go to one agent, and for the application we go to another agent. For applications also, depending on the type and nature of the application, we have to go to different agents. Different agents mean we need to install different agents. This is something I find a bit more complex.

I have been working with Splunk AppDynamics for two years.

I would rate the stability of Splunk AppDynamics a nine or ten because it gives efficient monitoring.

I would rate the scalability in Splunk AppDynamics an eight.

Before working with Splunk AppDynamics, I was working with Dynatrace and DataDog.

I have been working with Splunk AppDynamics for the past two years. Before, I was working with Dynatrace and DataDog. When I came to Splunk AppDynamics, I found it a bit more complex because for everything, we have to go to different agents. I found this part a bit difficult, but since I have been working with it for two years, I am becoming habituated to it.

With DataDog, the UI is very simple. If you compare Splunk AppDynamics and DataDog, the UI accessibility and all the things are very simple there. There will be only one agent present where we deploy all the things. The configuration of alerting policies, which you configure in Splunk AppDynamics, are also very easy there.

I can confirm that I am still working with Splunk AppDynamics.

I am using Splunk because it might be different from Cisco to Splunk. For now, everything is good with me. I think Splunk AppDynamics is more evolved, so for now, all things are good with me. My overall rating for this review is nine out of ten.

Our main use cases for Splunk AppDynamics involve monitoring our web stores.

Splunk AppDynamics has helped improve my organization's business resilience.

The features of Splunk AppDynamics that I prefer most are the monitoring aspect, making sure we can drill down and find problems. Splunk AppDynamics features benefit our organization by being effective; we use it consistently, and it is definitely utilized.

My impressions of Splunk AppDynamics' ability to predict, identify, and solve problems in real-time are that we've been using synthetic monitoring, and that's been really helpful, allowing us to see issues before customers experience them.

AppDynamics helped improve our organization's business resilience.

Splunk AppDynamics can be improved. I install it frequently and sometimes when they fix something, they break something else, so better QA is needed to ensure the quality of their fixes. There aren't any additional features that should be included in the next release because everything they're discussing at the conference is what we want to make the software better, so I appreciate that aspect of what they're doing.

I have been using Splunk AppDynamics for two years.

I assess the stability and reliability of Splunk AppDynamics as generally reliable, and we don't have issues accessing it, being SaaS.

I assess how Splunk AppDynamics scales with the growing needs of my organization as good, since we are growing and adding more servers. I have not expanded usage currently because we're in a freeze, and we don't try to update anything. Before the freeze, I did expand usage. The expansion process was pretty smooth.

I would evaluate customer service and technical support with Splunk AppDynamics as generally good since they usually respond to us within 24 hours.

Positive

The initial deployment wasn't so good. Smart agents didn't work. Trying to upgrade didn't work. On Linux, there are a lot of locking issues. You gotta make sure that libraries aren't getting updated. So there's always some type of conflict. When we do get to work, it works great, however, you have to go through all these steps before you can make it work properly. We spend hours, days trying to figure out what's wrong with it. Then, we contact support and go back and forth.

I have not seen ROI with Splunk AppDynamics from my level.

My experience with pricing, setup costs, and licensing for Splunk AppDynamics is that it's extremely expensive, and we completed a three-year deal for Splunk and for AppDynamics, which costs millions of dollars.

My impression of Splunk AppDynamics' AI-powered anomaly detection and root cause analysis in diagnosing performance issues is that we don't have the latest versions to get all that functionality, however, we're working on it, and we have an issue with smart agents.

I assess Splunk AppDynamics' infrastructure monitoring as doing the job in correlating infrastructure and application performance, and it has been around for a long time.

My advice to other organizations considering Splunk AppDynamics is that they demonstrate how everything's interconnected immediately, but there's substantial customization required around your own business, and out of the box, you need to configure it to make it work better for you. We spent significant money on professional services to help us accomplish that.

On a scale of one to ten, I would rate Splunk AppDynamics overall a nine.

A main use case for Splunk AppDynamics is monitoring the applications in production environment. We are doing infrastructure monitoring and application monitoring.

For all the applications, we monitor the infrastructure such as CPU, disk, and memory. If there are any issues with CPU, memory, or processes, we send alerts to the teams. Similarly, we do application monitoring for JVM and server availability.

We are using Splunk AppDynamics for troubleshooting predominantly, and sometimes for capacity planning as well.

The best feature about Splunk AppDynamics are the Business Transactions. It automatically detects and captures them, which helps most of the application teams.

Whatever the important business transactions are, it automatically captures them and their performance as well. If there are any performance issues, business transactions will help point out exactly where the performance has been degraded. This helps the development team to troubleshoot and rectify if there are any modifications required in their code.

Splunk AppDynamics monitoring is helping our organization. Because of this tool, we have reactive monitoring. Whenever there are any issues, the application will get the ServiceNow ticket. This is the policy in our organization. If the threshold criteria is exceeded, it creates a ticket and assigns it to the application team. The application team investigates that issue, and in that way, we avoid downtime. Apart from that, if there are any application performance issues, with the help of business transactions or memory leak functionality, the development team will be able to drill down that issue and fix it faster than the traditional way.

We have seen application availability increase. There is a twenty-five percent reduction of the application downtime.

With Splunk AppDynamics mapping, it captures the business transactions and provides the feature to add business transactions or eliminate those which are not necessary. This auto-mapping helps most of the applications.

With the help of infrastructure monitoring in Splunk AppDynamics, server availability is one of the key features. It captures the memory, CPU, and disk. These are helping my organization to keep all the applications up and running with minimal downtime.

We are looking for some more common extensions and custom extensions. Specifically, we are doing log monitoring, URL monitoring, and port monitoring. We are looking for cloud monitoring if there are any features available in Splunk AppDynamics.

Splunk AppDynamics can be improved specifically by providing the log monitoring feature that is currently not available, centralized log monitoring. I know that is available in Splunk. Apart from that, we are seeking to address a couple of issues in Splunk AppDynamics. Specifically, machine agents are not reporting, or we have to restart our machine agents. Another issue is with disk utilization. For disk utilization, it will automatically detect the mount path, but we have seen for many mount paths, even though they are mounted, the data is not reported in Splunk AppDynamics. If the Splunk AppDynamics tech team fixes these issues, that is going to help significantly. Additionally, there is one more feature regarding how we can do cloud monitoring with the help of Splunk AppDynamics. Regarding the market trending with AI, how will Splunk AppDynamics help with artificial intelligence?

In the technology stack, I believe Python is going to be heavily used in AI applications. I'm not certain about this. We currently monitor Python, but it is not as extensive as Java monitoring. If Splunk AppDynamics provides more information on Python monitoring or artificial intelligence application monitoring, that will be helpful.

Customer support takes time. Whenever we face any issues, we have to open the vendor case and then there will be back and forth happening. I can see there is an opportunity to improve the customer support in Splunk AppDynamics.

I have been using Splunk AppDynamics for the last four years.

We have not seen any issues with Splunk AppDynamics. It is stable. We haven't seen any outages.

We have not seen any issues with scalability. We were able to scale up as the number of applications increased.

Customer support takes time. Whenever we face any issues, we have to open the vendor case and then there will be back and forth happening. I can see there is an opportunity to improve the customer support in Splunk AppDynamics.

Positive

Earlier we were using some other monitoring tool, and troubleshooting in that monitoring tool was difficult. We switched to Splunk AppDynamics because of the business transaction feature specifically and other customized extensions available.

Before choosing Splunk AppDynamics, we evaluated some other tools as well. Specifically, we tried our hands with the Tivoli monitoring tool. We are still using OpenText as well, which is also a monitoring tool. We have used some other tools as well, but we chose Splunk AppDynamics because of its user-friendly UI and because it is easy to understand.

Splunk AppDynamics is user-friendly and it's easy to monitor applications and troubleshoot. This helps the entire organization.

It requires minimal training to get onboarded for the application team as well as the support team.

Recently we are exploring how Splunk AppDynamics can be integrated with OpenTelemetry, but we are in a very initial stage.

Depending on the organization's requirement, we will definitely recommend Splunk AppDynamics because of its features, specifically all the custom extensions, and to maintain the application uptime. Splunk AppDynamics will help. It requires minimal training to get onboarded for the application team as well as the support team.

I think with the current era, we can see Splunk AppDynamics being a costlier tool. Most of our clients have shown an inclination toward open source tools, such as DataDog. Many applications and many organizations are using Grafana, and there are other tools available, so they are exploring that possibility because of the pricing.

There were a few issues that we have noticed with Splunk AppDynamics. Data is not reporting, and custom extensions are not readily available. That is why I have chosen seven out of ten.

This metric is not currently available on top of my head.

I believe you have covered all the points, and I am satisfied. My overall review rating for Splunk AppDynamics is seven out of ten.