We use real-time application monitoring for financial applications, basically API testing. Our software runs on Red Hat Kubernetes container platform. We monitor a few thousand APIs and it's integrated with a testing tool called LoadRunner Enterprise software.

We extensively use it for banking systems in terms of how long it's taking to execute registration, user registration, or bringing up the transactions of the monthly period. If they want to see the monthly transactions, we monitor how long it's taking for this, or if they want to submit a service request, we monitor how long it's taking to get the notifications, all those kinds of things.

The real-time monitoring is what we can see for anything that is needed in terms of CPU, memory, or the connections or the sessions related. It's real-time monitoring of performance of each of the components, which is what we need and use all the time.

It's highly effective, I would say. Infrastructure visibility, transaction monitoring, to check the actual user experience in terms of the response time, MRT and all those things.

We do the component monitoring like the API performance and the connections and all those things, but we also do the business process monitoring and business transaction monitoring.

Telemetry is an area we tried to implement on the Azure cloud platform. We're still in the process and we haven't achieved any 100% success on that telemetry yet with OpenTelemetry.

We've been exploring machine learning algorithms that automatically flag unusual patterns and all those things, but we don't have the resources right now to work on those pieces. However, we are going to explore it pretty soon.

I've been using Splunk AppDynamics for a long time, more than probably 10 years, I would say. But recently, I've been using it constantly for the last three years.

We have a very robust implementation. I haven't seen any major failure or experienced catastrophic problems with Splunk AppDynamics. It has some resource usage that can be handled locally and doesn't require involvement from support, but I haven't experienced much failure.

Splunk AppDynamics is scalable. In large environments with more than 3,000 agents or 5,000 to 6,000 agents, I think they have some harder to manage. Up to 2,500 to 3,000 agents, it should be good, I would say. It depends on the scale and how much you want to scale it. There are challenges for every tool, so there are some problems with more than 3,000 or 5,000 agents.

We are ourselves self-sufficient. I don't remember calling for technical support. We do have a large team with a lot of in-house experts, so we don't rely on support. I personally never used technical support with Splunk AppDynamics. We also have a few resources from Splunk AppDynamics in our company.

I did use DataDog. I think DataDog has some features better than Splunk AppDynamics.The integration of DataDog is much easier than Splunk AppDynamics.

Scalability-wise, you need to have a lot of agents and all those things with Splunk AppDynamics. I think DataDog has a little more advantages on the larger scale for our environment. Splunk AppDynamics might have some database query analysis capabilities that are less than DataDog.

It is difficult and requires additional specific expertise with subject matter experts for Splunk AppDynamics. If you are in a Linux environment, all APM tool installation has a lot of hassle, especially in a controlled environment where there are a lot of regulations. The agents are very heavy in terms of collecting data and take a lot of resources. However, they have to use it since they don't have other options.

We are the user. We are not partners. We don't implement it. We are the customer for Splunk AppDynamics.

I think DataDog has a better pricing structure than Splunk AppDynamics.I think the maintenance cost and licensing model are a little high.

I have to use Splunk AppDynamics because the organization already implemented it. But my experience as an SME, subject matter expert on the APM tool, I would probably lean towards Datadog a little bit more than Splunk AppDynamics. That's my personal preference.

A lot of corporations already implemented Splunk AppDynamics, so getting rid of it and getting to a new one is costly. I think it could have been better, but it is worth it.

We utilize Splunk AppDynamics at the code level troubleshooting to basically display what exactly caused the root cause analysis of the problem that we see on the surface. We do use it extensively.

I would highly give them very high marks. I'm actually implementing Splunk AppDynamics right now at this point in time. My overall review rating for Splunk AppDynamics is eight out of ten.

I am using Splunk AppDynamics for application support and production support. I have worked for an alert system, which monitors any failures in the application related to alerts, job failures, and any services not working, by setting up all the alerts in Splunk AppDynamics to ensure the application is running fine. If it is not running fine, we can identify which service is not running and why it is not running, allowing us to monitor every log from Splunk AppDynamics. In the first case, if you want to see logs, especially regarding what and how, just keep the keywords according to the exception, and you will get all the details related to that. It is very easy to find solutions based on those logs. Additionally, if the application is not stable and is expected not to run for another hour, we have the option to check for space-related issues or any database tablespace-related issues. Splunk AppDynamics allows you to set up every kind of alert to proactively monitor and stabilize the application.

We are using the secure application feature in Splunk AppDynamics. To explain how that affects our ability to detect and protect against vulnerabilities, if anyone attempts to send an email to UPS.com using certain keywords related to transactions, Splunk AppDynamics immediately triggers and alerts for phishing attempts. This setup was also configured by the development team. I am aware of the features, such as if anything suspicious arises, many keywords need to be inserted to receive alerts, for instance, when someone tries to break into your security or network.

I use two or three applications that can be accessed from mobile. Once I connect to any public network—such as TFL rail—my mobile disconnects immediately, preventing me from logging in for two hours, due to restrictions set up by my development team. The importance of providing my mobile's MAC address to the development team that has integrated everything into Splunk AppDynamics ensures every team member's device is monitored to track connections to public, private, or secure networks.

The most important aspect of Splunk AppDynamics is that every service can be monitored to determine if it's running or not. If there is an issue, a red pop-up appears immediately, and you receive an alert. Based on that alert, you can also set up a ticket, so you will get a ticket as well. This is the best feature because, although you can't monitor a whole application at once, Splunk AppDynamics gives you the option that if there is any failure—simple failure regarding anything set up as per our use cases—you will get an alert. That alert helps us significantly to quickly find the solution or root cause of any issue. It is very easy to understand where the issue is, which is the most beautiful feature of Splunk AppDynamics.

Splunk requires significantly more improvements compared to Splunk AppDynamics, specifically regarding the licensing aspect. Splunk renews licenses every six months, which is inconvenient. It would be better to have a one-year license to avoid needing to update keys constantly, which can only occur on weekends, making it a burdensome task. Although Splunk is better for certain use cases, Splunk AppDynamics is broader in functionality. Specifically, I want enhancements related to creating dashboards not only for logs or minor services but also for configuration levels, allowing us to check configurations immediately without manually opening the entire code when exceptions arise—a feature I wish to see improved in Splunk, although it may not be necessary for Splunk AppDynamics.

I have almost six years of experience in digital experience monitoring.

Regarding deployment, it is neither overly easy nor extremely difficult, as we spent over two months getting it set up. Initially, when nobody had prior knowledge, I joined the team and shared my documentation. While it is not simple, some familiarity with the process is necessary.

The stability of Splunk AppDynamics rates as the best, providing a minimum score of nine; ten is seldom given as there are always areas for improvement, but Splunk AppDynamics is superior to any alternative, including Dynatrace. The vast array of options available further supports this.

Splunk AppDynamics is user-friendly, with many options readily available, primarily through drag-and-drop features. Setting up configurations is straightforward in Splunk AppDynamics, as it is in Splunk. Nevertheless, app-wise, Splunk AppDynamics is superior. A crucial aspect is that when working shifts alone, you can constantly monitor Splunk AppDynamics; upon any error occurrence, you receive immediate notifications. You can click on alerts, which lead you to specific issues and guide you to find logs and services that may not be functioning. If needed, you can easily restart them. Although several nodes run simultaneously, should one fail, passing processing responsibilities to other nodes is possible with Splunk AppDynamics. In contrast, with Splunk, it requires manual checking and restart, which is a significant drawback relative to Splunk AppDynamics. It's an incredibly user-friendly tool that anyone can master in a month.

When rating the technical support, Splunk primarily serves log-related queries effectively, with limitations. It excels in returning standard log information and locating issues quickly, but Splunk AppDynamics allows for monitoring entire applications at every node, making it superior for horizontal scaling.

Dynatrace is also a highly popular product alongside Splunk AppDynamics. Earlier, we utilized Splunk, but it has some limitations when compared to Splunk AppDynamics. We previously switched to Splunk AppDynamics due to the limitations faced with Splunk. Splunk AppDynamics supports monitoring six to seven applications simultaneously on a single dashboard without needing to create numerous dashboards for different applications, which is a real advantage. Dynatrace, while similar to Splunk AppDynamics, does not exhibit clear superiority over it, as they are competitive products.

The purchase was made directly from Splunk AppDynamics, as we have direct licenses from our vendors, including Quest software and Microsoft.

In my team, there are nine members who utilize Splunk AppDynamics.

Time is the most valuable aspect as I work in the banking sector. When issues are rectified promptly, we save money. In the production environment of a bank, timing is critical, especially with a one-hour SLA, and analyzing issues takes time. Splunk AppDynamics significantly aids us because as soon as we identify a problem, we immediately receive API call insights through the AI version currently in use, suggesting resolution pathways and options such as restarting the server or application. I estimate a minimum of 30 to 40% time savings, as if one person is working a shift independently, they do not need to rely on others due to the dedication to specific issues. Immediately upon discovering an issue, Splunk AppDynamics AI provides numerous solutions. We typically find about 40 to 50% of solutions instantly after identifying an issue, plus alerts guide us to the precise location of the problem. Overall, as a production gatekeeper, we achieve at least 50% efficiency immediately, with potential savings ranging from 60 to 70% as well, reinforcing why it is a popular tool in the banking industry.

I consider Splunk AppDynamics to be cost-efficient.

I have been using Splunk AppDynamics for more than six years. Regarding the data collection feature with agents or open telemetry, I know the functions and setup, but we have a development team responsible for that specific area. As production support, we usually do not handle these configuration-related tasks, but I am aware of the features. If I were to configure Splunk AppDynamics myself according to the requirements, I can manage some special cases, but I'm not highly proficient in that part.

For the monitoring capabilities in hybrid and on-prem environments, my experience is that it is hybrid only, as all our applications are based on Azure. Nowadays, every application primarily operates in the cloud, with most servers and infrastructure services utilizing Azure. All the services we use in Splunk AppDynamics are Azure-based.

Regarding transaction monitoring, you get all the details in one place. If anything related to payments is stuck somewhere, within this monitoring tool we can identify which transaction is handed off or not, whether it is payment sent outside or coming back to settlement, allowing us to monitor it easily.

The AI-powered anomaly detection and root cause analysis for diagnosing issues was enabled in my system about six months ago, which eliminates the need to worry about locating errors. You only need to provide the exact statement for the error, and AI will identify the log information for you, showing where to go to find the log. With this AI functionality, it becomes easy to analyze the path of the error. We manage eight hosts, and prior to this AI being enabled, we had to check every host repeatedly. Now, AI tells you which host has the error, simplifying issue resolution.

I provide an overall solution rating of nine out of ten for Splunk AppDynamics, as improvements are always needed. Sometimes, while fetching details, Splunk AppDynamics provides answers within a minute, but it can occasionally take seven or eight minutes, which can be problematic when time is limited.

As a customer using Splunk AppDynamics at UBS Bank, I provide production support for seven payment-related applications, including e-banking, e-trader, and core banking among others. All of these applications are monitored through Splunk AppDynamics. The impressive part is that with a single click, connecting directly to the application dashboard is possible, allowing for streamlined monitoring without manual checks of each application.

The root cause analysis they have is exceptional. It is a satisfying product, especially the smart agent collectors, which help us significantly.

The real user monitoring and digital experience monitoring effectively track actual user experience with the applications, including page loading, interaction time for both desktop and mobile applications.

AppDynamics' AI-powered anomaly detection and root cause analysis in diagnosing performance issues is good. It doesn't have many false positives.

They have one aspect that needs improvement. They should combine the cloud and EPM on-premises together and provide a unified single pane of glass for all their modules because they currently have different modules for infrastructure monitoring. My expectation is to unify the management console into one single pane of glass console to manage everything and have all visibility from one place.

We have completed three years with Splunk AppDynamics.

It is good.

The scalability is fine. Many people are using it. We are a system integration company selling this to clients. Our clients are medium to large-sized businesses, typically ranging from 800 to 8,000 users.

I would rate them an eight out of ten.

It's a bit complex; it's not exactly easy. It's moderate in difficulty. You need some experience to implement it.

It is a good solution. It has strong capabilities. You cannot compare Splunk AppDynamics with others. If you want quality, you need to pay, so the cost is justified.

I would recommend it for financial institutions and banks, as well as any companies that rely heavily on online applications, like e-commerce service providers.

I would rate Splunk AppDynamics an eight 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.

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.

My main use cases for Splunk AppDynamics include APM, application performance monitoring.

The features of Splunk AppDynamics that I appreciate most are the business processes. These features benefit my organization by providing a bigger picture, not only of their own systems, however, how it influences other parts of the environment and how we are being influenced by other parts. For its time, Splunk AppDynamics helped improve my organization's business resilience quite a bit.

To improve Splunk AppDynamics, it should migrate seamlessly into observability Splunk, which is called Splunk Observability Cloud.

I have been using Splunk AppDynamics for around 15 years.

The stability and reliability of Splunk AppDynamics were okay. I did not experience unusual downtime, crashes, or performance issues; no software is perfect, but it was within the expected parameters.

Splunk AppDynamics had some confusion about the SaaS, no SaaS, only SaaS strategy, which wasn't clear. Some time ago, they committed again to on-premises, however, it was too late.

I evaluate customer service and technical support as good, seven out of ten.

Prior to adopting Splunk AppDynamics, I was not using another solution to address similar needs; this was our first step into the APM world.

My experience with pricing, setup costs, and licensing is that it was very expensive.

Sadly, I did not see return on investment with Splunk AppDynamics.

The solution I was using prior was Grafana Cloud.

What caused me to stop using the solution is that we failed to bring the product to our DevOps teams so that they could easily use it and learn how to use it, this is something we had to learn again. I would advise other organizations considering Splunk AppDynamics to take a sharp look at the whole Splunk product portfolio and how they merge to observability cloud, integrating many AppDynamics features; this is very interesting, but I don't know whether or not they are already there.

On a scale of one to ten, I would rate Splunk AppDynamics seven out of ten.

We had several applications that were facing performance issues. To improve our observability, alerting, and monitoring of these performance problems, we onboarded the applications onto Splunk AppDynamics. This allowed us to gain better insights into the issues and identify the business transactions that were causing the problems.

I haven't used the APM feature. It's primarily been configuring database collectors on a database.

Splunk AppDynamics has been effective in auto-discovery and mapping and visualizing our application ecosystem. There have been instances where we've needed to fine-tune the auto discovery feature. When we installed it on Unix and Windows applications, it retrieved a substantial amount of information. We then had to configure the information to meet our specific needs. The tool goes out and summarizes all the business transactions, but we need to limit or filter out the excess data. This is particularly important for gaining visibility into application performance and proactively resolving issues.

Using Splunk AppDynamics for business transaction monitoring significantly impacts my ability to prioritize transactions such as logins or checkouts, and it has improved the process.

I've worked on an application where users book trades into a system. Each booking translates into a transaction. Similarly, users query these trades, which corresponds to other transactions. I can see the speed of these transactions and identify issues when trying to write them into the database. I can also monitor when transactions are being queried. Additionally, there are other applications accessing the database, and I can observe their interactions as well. Overall, it enhances my ability to visualize what’s happening behind the scenes.

I find Splunk AppDynamics' AI-powered anomaly detection and root cause analysis to be very effective in diagnosing performance issues. I can quickly identify if there's any blocking on the database. Using the APM tool or the graphical user interface, I can track slow SQL queries. I can sort all those transactions to see which ones are consuming a lot of CPU and identify the long-running queries. This allows me to quickly assess the situation and understand what is going on.

Based on the issues we observe in Splunk AppDynamics, we know where to focus or where to spend money in improving the application. It gives us that flexibility to be able to improve and know where to focus our spending power.

I like the fact that you can self discover business transactions. It's easy to onboard your applications and configure your collectors or your agents.

The ability to monitor transactions and identify slow SQL queries in a database is valuable. We can detect issues such as blocking. It allows me to visually analyze the database's performance and understand its current state. Additionally, users can configure a dashboard to provide an overview of the database activities.

When I onboard applications onto AppDynamics, I configure database agents or collectors to gather metrics and monitor business transactions. This setup enables me to see what is occurring within the database environment. I have extensive experience in configuring agents and collectors for databases, as well as for Windows and Unix machines.

I would probably suggest making the tool more real-time and allowing for integration with a wider range of DevOps tools. This is particularly relevant when comparing it to something like Genius, which I recognize is a different tool altogether. Ideally, I would prefer a situation where I don't have to use two or three different observability tools, allowing me to focus on just one.

When you self-discover observable business transactions, there should be a better way to focus on the specific transactions that matter to us. In our environment, we have numerous business transactions, but not all of them are relevant for monitoring. It would be helpful to easily identify and target the business transactions we want to concentrate on without it being too cumbersome.

I've been using Splunk AppDynamics for about three to four years.

It has gotten a lot more stable over the years in comparison to when I first started using it. I would rate it a seven out of ten for stability.

It's easily scalable. I would rate it a seven out of ten for stability.

There are approximately 100 global users in my organization who work with Splunk AppDynamics.

The technical support for Splunk AppDynamics deserves a solid eight out of ten.

It's down to the complexity of our environment. We've got a lot of legacy applications, so it is a little bit complex trying to implement it. We had about 200 machines or databases. It took some time to get it implemented. It took a couple of months.

From an end user's perspective, I often need to coordinate with my infrastructure team. Ideally, I would like to implement it without having to rely on them. For example, if I don’t have full access to a database, I have to reach out to my infrastructure team to gain full access or to create a collector on the database. It would be much more efficient if I could log into the database and create a collector myself. In my experience, having to wait for administrators with full access to take action slows down the implementation process.

The only maintenance I could think of is having to make sure that the accounts are onboarded and the password is reset because the password sometimes expires. That's the only issue. It's quite straightforward. Once you reset those passwords, you're good.

I estimate it saves 10% to 15% in various resources.

Genius is likely more intuitive and offers greater functionality. It can be easily integrated with many other DevOps tools. In comparison to AppDynamics, Genius provides much more flexibility. However, one downside of Genius is that it does not automatically discover business transactions. From that perspective, AppDynamics has an advantage due to its self-discovery feature for transactions.

I would rate Splunk AppDynamics a seven out of ten.

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.

I get information related to application transactions on a day-to-day basis and manage their capacity augmentation according to transaction details. We collect errors and exceptions from end-user applications, and we share the details with the application development team that works on the application errors and exceptions to resolve and create enhanced performance with the help of Splunk AppDynamics. We have been working with Splunk AppDynamics for the last six years.

The main feature for Splunk AppDynamics is the application drill-down, and the application users utilize it with the help of the next blank panel on their application. An application developer, with the help of Splunk AppDynamics, collects data to get the correct information related to their application code and how the application code performs under low load and high load. Once they get the correct information through Splunk AppDynamics, they will enhance their code to perform better under high load.

It is a very user-friendly tool, and I have used multiple tools related to APM technology, not only Splunk AppDynamics. We have multiple tools, but end users prefer to use Splunk AppDynamics because their portal navigation is very simple and clear.

Application owners build down their application performance through Splunk AppDynamics. Based on the information related to daily, weekly, and monthly metrics, the application development team receives related information for their application performance, and they try to resolve application errors and exceptions, which is achieved via Splunk AppDynamics to enhance their performance.

There is a policy related to dynamic performance to baseline, and end users check their application performance according to their baseline, gathering information about their performance. Based on that information, they take corrective measures related to their applications and resolve issues and errors.

Dynatrace has multiple functions compared to Splunk AppDynamics, so Splunk AppDynamics should add those functions, which are not available as of now. Dynatrace has a universal agent that collects all information related to their CI, and if one CI has multiple languages, then there is no need to instrument multiple agents.

However, Splunk AppDynamics requires multiple agents; if I have one server with multiple applications in different languages, then I need to instrument different agents for each application.

Splunk AppDynamics should work with Dynatrace with one single universal agent that works with all application languages, eliminating the need for multiple implementations.

Regarding stability, it is a very nice and good tool. There are no issues or bugs with the 20.4 version; it is very stable with no functionality or operational issues. I would give it ten out of ten.

The support team for Splunk AppDynamics is very helpful, and they help us resolve any issues raised by our team relating to operations, application instrumentation, or any other issues. I would give them a nine out of ten.

The new version is very straightforward. I would give it a ten out of nine, and there are no issues related to deployment; it is very easy and straightforward to deploy.

There are multiple benefits related to the APM market, but we experience benefits related to application performance only. According to errors, exceptions, and code-level details related to their application performance on a daily basis, the application development team tries to help with Splunk AppDynamics to reduce errors and exceptions, which helps the end users get application availability and feel more confident.

I rate Splunk AppDynamics 10 out of 10.

Our use case is in the lower environment. We are not using it in the production environment. We are part of the performance testing team, so we monitor the users on this server through performance testing, and during that time, we use all the agents, install them on the server, and monitor any bottlenecks. We use Splunk AppDynamics for deep dive analysis and provide inputs to the team. That is our use case.

We are using it only for the on-premises environment, but we are exploring options for Azure-hosted applications and AWS-hosted applications.

Splunk AppDynamics helps us in identifying bottlenecks and providing fine-tuning recommendations. We have many sites. We do deployments and analyze products. Before, as a performance testing team, we were not in a position to tell the team where the issue was happening, only able to provide numbers. With Splunk AppDynamics, we can pinpoint exactly where we need to concentrate and provide recommendations for fine-tuning. Without it, it was a nightmare. We wouldn't have been able to provide this information.

The metrics browser is very useful, and the deep dive feature is very useful for us.

Product-wise, everything is good, but the main concern is the extensions and their documentation, particularly for the installation of Azure app services. It is lacking some documentation, which is why we are always with the AppDynamics team for support to get the details.

Additionally, whenever they upgrade or add new features, we do not get notifications, which makes it very hard for us to find out new information. If they could fix this, it would be helpful, and our satisfaction score would increase.

We have been using Splunk AppDynamics for almost three years.

We are using the cloud version only and not an on-premises installation. I am not sure what to expect on the scalability front, but it is useful for us. We have tried it with a maximum of 500 concurrent users, and it provided all the required information.

Initially, we had some hiccups getting technical support. After some time, we got a contact, an account manager, to work directly with for technical support. He immediately finds a resource and assigns it to us.

We haven't done that exercise. We are working on a mix of applications, such as SaaS, AWS-hosted, Azure, and on-premises applications. It's very hard to find ROI because we are currently focused only on the on-premises applications. In a year, we work on about 20 projects, but we get only two or three projects using Splunk AppDynamics. For the others, because they are vendor-hosted, we don't utilize it. We are still trying it, and maybe once we develop that capability, we'll start finding ROI. Currently, we are not performing any exercise on calculating ROI.

We find its pricing reasonable and competitive. After it was acquired by Cisco, we found it acceptable.

I would rate Splunk AppDynamics an eight out of ten.

The main use cases for it are similar to APM from Broadcom.

Splunk AppDynamics is very similar to APM. The part of the database is interesting since users can do many things with this dashboard, and the business dashboards are also very interesting. The main dashboard, showing all communication between components or business transactions, is very interesting as well.

This is similar to APM from Broadcom. The most important thing is managing the performance of the application for critical business in organizations, and it's very important to do this with the solution you want. If you don't have this kind of application, it's impossible to know what happened with your critical business.

It's similar to ABM from Broadcom. It's important to have. You need to be able to manage the performance of the applications that are critical for business in an organization. If you don't have this kind of application, it's impossible to know what's happening with your critical business aspects.

With Splunk AppDynamics, the database part is interesting. Users can do many things with this dashboard, and the business dashboards are also very interesting. The main dashboard, showing all communication between components or business transactions, is very interesting as well. For example, the baseline of all metrics in the Splunk AppDynamics database is very interesting. It can send alarms or alerts when the database baseline is not correct.

The effectiveness of the Splunk AppDynamics auto-discovery and mapping is similar. It's maybe a little better than APM from Broadcom. However, it's not the best. Users need to modify or configure many things to get good information from discovery. It's good, yet there is something to improve.

Business transaction monitoring is the more interesting part of Splunk AppDynamics since it has automatic discovery of business transactions and many different kinds. For example, for web services or different kinds of components, such as in Java. Users can configure business sections in their environment, and it's possible for customers to configure different sources for the name of the class, the name of the method, or the name of the web service, which is very interesting.

I work with the AI-powered anomaly detection and root cause analysis for troubleshooting. Users can see the error and the message with the error on the dashboard, and they can see exactly what error they are encountering.

The user experience is good. Its impact is very high. It's crucial to be easy to manage for the customer's user experience.

The discovery is acceptable, however, users need to configure many things if they want good discovery. These points are candidates for improvement.

A good integration with the CMDB would be beneficial, so users can see a good view of the final services automatically. A good integration with Splunk would be very interesting, as Splunk is a good product for logs, and that part is currently missing in Splunk AppDynamics. If Cisco can achieve a solid integrated solution, it would be very beneficial.

I have used Splunk only for the security part, not with the APM part - only with the security and management of logs. I have used Splunk AppDynamics for approximately five years.

The solution is stable.

The solution is scalable.

We have had a good experience with Splunk AppDynamics compared to APM from Broadcom. AppDynamics if much more helpful.

Support is generally okay, and the support is knowledgeable.

We have experience with another solution, with performance, with application performance, with infrastructure, alongside the other product we are working with.

It's very different. The most important aspect is that the discovery of Splunk AppDynamics is better than APM from Broadcom, along with the dashboard and many other features.

It's very complex regarding pricing, setup costs, and licensing of Splunk AppDynamics. Normally, when we have to do a quote for a customer, we talk with Cisco, and it is very complex. For me, it is more complex than APM from Broadcom, which is easier. Cisco being complex depends on the part of the solution, the agent, and many things.

The solution is better in on-premises environments.

Splunk is only SaaS, and in two years, or when these solutions are integrated, maybe it will be a better SaaS solution. Right now, for on-premises environments, it's the best.

There is maintenance needed, and it's important to do the maintenance work. We have to do a lot of things to maintain it properly. It's not difficult. However, you do need to do a bit of work - more so than APM Broadcom.

Ten years ago, it was good, however, now it's complex in Cisco. We tried to integrate Splunk with Splunk AppDynamics, and maybe in the future, it will be a good solution. Right now, it's two separate solutions, and it's not a good integration.

Splunk AppDynamics' infrastructure monitoring is satisfactory. Users have a main dashboard with all information. If there is a problem with memory, CPU, or something else in a server, users get a red alert, and they can click on that component to see the specific metric related to that CPU, memory, or network problem, and the correlation is very good.

It optimizes the user experience for customers.

My experience is more from Java and .NET applications. I don't have security skills, however, customers find it acceptable to see this information in the global context regarding their applications.

It depends on the integration with Splunk that I mentioned before. I prefer to wait to see what happens with that, but Splunk AppDynamics is a very good solution, and I believe that integrating Splunk will yield excellent results.

On a scale of one to ten, I'd rate it a seven.