My usual use cases with Splunk AppDynamics are primarily related to the Innova project, where we collect all assets and prepare a dashboard to display all assets and create reports for management about what assets are in place, their numbers, and their identifications.

We use Splunk AppDynamics for application performance monitoring in on-premises environments because hybrid is not an option for us, as we utilize an OT system located on the client's premises, and we do not use a hybrid or any cloud environment.

We use Splunk AppDynamics primarily for maintenance and support, especially given the current threat landscape. We validate all software and hardware lists approved by the end user and monitor for any recently added assets to ensure compliance with the approved repository.

I rate Splunk AppDynamics' line-of-code level troubleshooting feature a perfect 10 out of 10 for diagnosing performance issues, as it is very good.

The codes used for Splunk are very good, understandable, and readable, which is why I give it a high rating.

I find Splunk AppDynamics' Digital Experience Monitoring feature very good because it offers end users complete insights into their network, hardware, and software assets, along with detailed reporting on asset installation, models, and operating systems.

The Secure Application feature in Splunk AppDynamics is valuable because it links to the firewall and reports any incidents or unexpected asset discoveries, thereby preventing unauthorized access or communication within the network.

I do not believe there are areas to be improved in Splunk AppDynamics rather than the current situation, but I believe that integrating artificial intelligence and linking the software with other APIs, such as AI or machine learning, would be great.

I wish to improve the AI and machine learning capabilities in the software, which are currently used for top management reporting instead of manual reporting from the system. I believe AI could provide more insights for annual or half-yearly reports and forecast future changes in the asset landscape.

I have been working with Splunk AppDynamics for approximately two years.

I give Splunk AppDynamics a 10 out of 10 for stability and reliability since it offers full insights into the software and hardware supply list.

Both stability and reliability are excellent in Splunk AppDynamics, with my assessment reflecting its consistent performance.

I have never experienced any outages with Splunk AppDynamics; it has never stopped working abruptly.

Scalability is very good in Splunk AppDynamics as it can accommodate a wide range of asset counts, but it depends on the license schema, which may range from 250 to 10,000 assets.

I normally communicate with the technical support of Splunk AppDynamics for any incidents or issues, but we have not opened any tickets yet. We also have 40 optional support hours committed in our contract.

Currently, I have not communicated with any technical support specialists from Splunk AppDynamics because we are still in the integration phase, but if we face issues during testing, we will use the support hours we have committed.

Before using Splunk AppDynamics, I used an outdated solution, an Excel sheet, to track all assets, software, and hardware, which was challenging compared to the resilience that Splunk AppDynamics' dynamic software provides.

My experience with the initial setup and deployment of Splunk AppDynamics is that it was very easy, with our team installing it in four control centers in less than eight days, which I find to be perfect.

We requested all technical manuals and third-party documentation from Splunk AppDynamics to deliver them to the end user as part of my commitment, ensuring they receive all necessary documentation and training materials.

The pricing and licensing of Splunk AppDynamics are managed by another team called the resource team, and they handle all tool and software lists to provide us with the necessary licenses.

I consider the pricing of Splunk AppDynamics to be mid-range compared to other software, as it operates on a subscription model, and the resource team finds the best prices, ensuring that Splunk AppDynamics is an acceptable option for the end user.

I evaluated other vendors, but we chose Splunk AppDynamics because the customer provided a list of approved software that we were required to procure and install without deviations.

I have experience with IT asset management solutions, specifically with Device42, and also with asset discovery tools such as Splunk AppDynamics and other tools.

I was working in one of the projects in the Western region of Saudi Arabia at Neom city, where it is called the Innova project, and we are using Splunk AppDynamics for technical purposes there.

My role is as a delivery manager, and I am taking care of all software and hardware delivery at GE Vernova, where I have a team of integrators, network engineers, and database engineers. I ensure that everything has been delivered correctly to the end user and customer.

I am not in charge of getting into the technical details, but I follow up on the software names to ensure they are configured and in place, and I see that the automatic asset discovery feature, which automatically detects any additional hardware, is very interesting.

I think Splunk AppDynamics' data collection feature with agents or OpenTelemetry is perfect because it is installed dynamically on all servers and nodes, and all agents respond quickly to the server or master station where Splunk AppDynamics is installed, providing great insights into hardware and software discovery.

Both stability and reliability are excellent in Splunk AppDynamics, with my assessment reflecting its consistent performance.

The alerting feature greatly impacts end-user experience since it is user-friendly and the end users are well-trained by GE, making them capable of understanding and operating the software without complications.

Splunk AppDynamics allows us to understand the mean time to resolution and decrease it by easily understanding the dependency of the full application flow map. For root cause analysis and other hidden aspects, we can see how code quality performs. SQL queries can be easily evaluated for quality, and when code quality is not good, we can identify slowness in specific classes and methods. We can see which parts of methods and SQL queries are facing slowness issues. After that, we can develop and change code, modify database queries, and easily see in the product environment without needing to debug facilities. We can see in real time whether code changes are affecting the system positively or negatively. There are many different advantages, and we can separate proactive and reactive sides.

When we collect different method parameters with the essentials of monitoring APM tools, we can easily combine business and operational development cycles in a single pane. For example, when development teams make process improvements to code to add new features to transactions, we can easily see how this feature affects customer experiences as performance metrics. If we can collect this kind of data, we can also easily combine business and operation metrics. For example, with a loan application from the customer side, such as a bank customer making a loan application over their mobile or internet banking application site, we can easily see how many successful transactions occur in real time from a business perspective, not just from the performance side. If we can collect these metrics, we can combine all performance and business metrics in a single pane, giving customer sites a very different and big picture view.

Splunk AppDynamics works for Java, .NET, .NET Core, Node.js, and PHP applications. We also work with some customers using SecureApp features, and customer feedback has been really valuable for us. From my customers' experience with this feature, the feedback is really positive. In the software development lifecycle, penetration testing or security testing before getting a project into live production environment is a very important process. You have to conduct penetration testing before going live with your project. However, this kind of penetration testing is a bit reactive and offline because you only perform this penetration testing from a synthetic point of view, for example weekly, monthly, or quarterly. With Splunk AppDynamics SecureApp solution, we can easily see our application's vulnerabilities, attacks, and exploits in real time. We can also see any vulnerability, even zero-day attacks, easily after they occur. This is a really cool and differentiating feature, though it is a very new feature in the APM market, almost two years old. Because of that, it is not well-known, but when we demonstrate it to customers in POC or demo sessions, most customers are impressed and want to try it in POC. After POC, some customers want to buy this feature while getting the APM solutions as well.

We can monitor what kind of vulnerabilities exist in the code and can easily show the business risk in the environment by making a business score, not relying on MITRE or CVE codes. The scoring also works from a business perspective. For example, if we have one vulnerability that may be medium severity, our internal scoring mechanism increases the business risk if the application touches databases or other inside applications. If the application is not communicating with other applications, databases, or other sources, the business risk may be lower than the other example because of the application's touching points. This is a really cool feature. We are not only reporting these vulnerabilities, but we are also blocking these attacks in real time. For example, when a Log4j2 vulnerability occurs on the system or any zero-day attacks happen, Splunk AppDynamics easily tags and understands this kind of attacks. If desired, it can easily block the application's attacks from the APM perspective. This is a really game-changer in my opinion.

I think one of the really strongest features of Splunk AppDynamics is the end-user experience monitoring. We have a really differentiated capability over our competitors. We can easily adapt our solution to the customer's application, internet banking solutions, or IoT devices all over the world. For example, when you get a new Volvo from any Volvo shop, that car has a built-in Splunk AppDynamics light agent to track their connected car applications. To give a specific example, Audi, Volvo, and four years ago BMW also use Splunk AppDynamics light agents to monitor IoT devices and connected car applications. Mercedes may have this kind of agreement as well. In summary, we can easily monitor mobile devices, including Android and iOS, browser-based applications, and also IoT devices. For example, in Turkey, I personally use IoT monitoring with my customers. We work with banks, and most customers monitor their ATM devices and POS devices via Splunk AppDynamics agents. I have personally implemented the IoT agent or Splunk AppDynamics agent into ATM devices and POS devices, as well as for some cinema companies' kiosk systems.

I can mention two different things. First, Splunk AppDynamics is mostly compared with the Dynatrace solution because they are a really good solution. They offer on-premises options as well. I know Datadog is another good solution, but it only works with SaaS solutions. New Relic and Grafana are also good solutions, but Splunk AppDynamics and Dynatrace are the only on-premises options in the marketplace. Because of that, I want to compare with Dynatrace. Dynatrace has a OneAgent mechanism, while Splunk AppDynamics has a smart agent mechanism. The idea is quite similar, but when you use the Dynatrace OneAgent solution, because you are giving administrator and root rights, it is a bit easier but unsafe. For Splunk AppDynamics, you do not need to give the agent administrator or root privilege, but because of that, its capabilities are a bit limited. I cannot directly say this is a negative thing because it depends on the perspective. For example, if you really stick to security mechanisms, security teams can say that Dynatrace is easy to install and monitor, but from the security perspective, it is terrible and awful because you are giving full administrator and root privileges to Dynatrace. Splunk AppDynamics could improve their installation process, which would be an incredible thing on Splunk AppDynamics' side.

Second, most products, even Dynatrace, Splunk AppDynamics, and Datadog, are always saying they are making AIOps, root cause analysis, and anomaly detection features, but even Splunk AppDynamics, these kinds of features are not working fine because of the nature of the metrics. Most of the customers are not supplying the hygiene of metrics. If you do not supply or make your environment's metrics hygienic, you cannot give the AIOps perspective to customers. The statement that these vendors can make root cause analysis automatically or have automatic detection features and capabilities cannot be truthfully said. To sum this up, this is not only a Splunk AppDynamics problem. From my personal perspective, this is all APM vendors' problem. The features that all these APM vendors need to improve are the AIOps features. These are really at the beginning of the AIOps era. Everyone is talking about AI, and it turns out to be a common hype in the technology market. We may see the real effect of this AIOps era maybe two or three years from today.

It is almost at the beginning of the story. When I started with Splunk AppDynamics, there was no acquisition between Splunk and AppDynamics, and AppDynamics was also its own company. This has been 14 years.

Implementation can be divided into two different parts. One part of the implementation process goes over the controller side, which can also be called the control plane side. One engineer is enough to install and prepare within two hours. However, the agent side is a bit more complicated because it depends on the customer's situation. If the customer has more than 100 or 1,000 different servers, mostly in production environments, we need to agree on when we deploy agents because we need to restart their applications. This creates some outages in their production environment. First, we need to agree on the timeline and project plan. It depends on the customer's decision. If we have a chance, at one time, we can also deploy more than 500 different agents at the same time, maybe within half a day, because we have really good playbooks and automation scripts working over Ansible, Chef, Puppet, or different automation tools that we can easily integrate. Implementation is easy, but the agent side depends on the customer's decision based on their project coverage or decision. It can take two days, or maybe two weeks or two months, depending on how big their environment is and how many licenses they get. For example, if they get more than 1,000 licenses for more than 1,000 hosts, it depends on their decision and project plan. It can take two months, one month, three weeks, or two weeks. It is a very variable thing.

I am working for my own business. Previously, I was in my former company, but I quit and built my own company. We are operating in the same area, and nothing has changed significantly in my life.

Over the last 14 years, we have made maybe more than 500 different installations, maybe much more than that. I do not know exactly, but in the last four years, we have prepared our own scripts and playbooks. It is really very simple to build a Splunk AppDynamics platform over the on-premises data center. Even if the customer wants to use the high availability option, if they have a limited environment or limited hardware resources, we can easily build all these components in one server. Because of that, it can be very simple when working only with one server. However, most customers in Turkey, including fintech-based, banking, government, and some really huge enterprises, need to use the high availability options, which means using more than six different separate servers. With our playbook and the solution's flexibility, Splunk AppDynamics is very flexible for this kind of model, and it takes no more than two, three, or four hours.

I would rate this solution an 8 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.

Splunk AppDynamics is currently being used in my organization for APM, application performance monitoring. We have Java-based and .NET-based agents that fetch the APM metrics onto Splunk AppDynamics. We have a Splunk AppDynamics SaaS offering that is ongoing. A few years ago, approximately two to two and a half years ago, we also used Splunk AppDynamics for platform monitoring and cloud platform monitoring. However, right now, it is mostly APM.

The auto-discovery and anomaly detection features are particularly valuable to us. The baseline variance methodology for anomaly detection in APM monitoring has helped us troubleshoot and triage problems where applications experience high surges of traffic and go down suddenly. This kind of view has been very helpful to us in the past when we ran into issues.

We have used Splunk AppDynamics for business transaction monitoring. The business transactions feature is the feature I applaud the most in Splunk AppDynamics. The business transactions feature has helped us stay current with the trends in traffic. We were able to separate successful transactions from non-successful transactions, such as transactions with 200 error codes and 500 error codes. This capability has been very beneficial to us.

I like the view of business transactions timeline that Splunk AppDynamics provides. This view has helped me troubleshoot many production issues. When you select an application, there is a business transactions view that I find very valuable.

The auto-discovery and anomaly detection features are outstanding. The baseline variance methodology for anomaly detection in APM monitoring has helped us troubleshoot and triage problems where applications have high surges of traffic and go down suddenly.

I have not used Splunk AppDynamics rigorously in the past one year for platform monitoring. For application monitoring, we are quite satisfied. The reason why we have not used it for platform monitoring is because we have a VMware product called Tanzu, and they do not integrate very well with Tanzu. I think the reason behind this is that VMware has their own monitoring solution and they wanted to promote it, which is a business and political consideration rather than a feature issue. Therefore, I have not explored the various dashboard features of Splunk AppDynamics. I would think Splunk AppDynamics could do a better job in creating out-of-box dashboards for Kubernetes-based cloud applications. This is something I would recommend.

The user interface is great and good. If you could provide more out-of-the-box dashboards, as other monitoring systems do, that would be a really good addition to the solution.

For SaaS, we have not experienced stability issues. After we moved to SaaS, we have not had any problems. Earlier, we used to do agent updates, but now that we have moved to SaaS, we no longer need to.

Regarding scalability, I cannot really comment on it. I have not really scaled up recently with our Splunk AppDynamics solution. It has been pretty stagnant. However, based on my interactions, it was pretty decent. I would rate it around six or seven.

We did have to contact technical support regarding a specific issue when we were doing blue-green deployments. When the app changed from blue to green, the app name changes, but the subsequent app name change was not reflected on our Splunk AppDynamics console unless we restarted the app. We worked with the vendor and it turned out the metric being sent out by our nozzle to Splunk AppDynamics was the problem. The vendor was very helpful and we had great vendor interaction whenever we worked with them.

I have used Dynatrace, ELK, Elastic APM, Grafana, and Arya. These are all other observability products I have used. When I compare them, I still prefer Splunk AppDynamics for baseline detection, baseline anomaly detection, and business transactions. However, I prefer Grafana dashboards that come out of the box for Kubernetes or virtual machine-based cloud offerings.

The initial deployment of Splunk AppDynamics was easy.

The vendor worked with us hand in hand during the implementation. Overall, we were able to complete it in less than two days.

One person can do the deployment as it is not that complex. Once we have the template and configuration everything set, it flows pretty smoothly.

We do not use OpenTelemetry.

We have not used Splunk AppDynamics for any code reviewing.

I have not used logins and checkouts for business transactions.

I have never tried using it in diagnosing any performance issues.

I am not aware of the pricing as that is above my level of involvement.

My overall review rating for Splunk AppDynamics is eight out of ten.

I use Splunk AppDynamics as our monitoring tool, and it has been effectively used in the last five years to identify major issues and rectify them without causing a major impact to the website.

Splunk AppDynamics tells us what the top 10 queries are which are actually contributing to the load on the database, and it gives us the view of what exactly the query does, whether it uses more DB CPU or is contributing to the roll-up contention on the database. These details provide great insights, making it one of the good features from Splunk AppDynamics.

When it comes to the front end with my Node.js and React.js applications, it doesn't capture much of the details. The improvements I made were mainly around the Java agent side in our app layer, but it was lacking detailed information on the front-end layer. This is a disadvantage, and it could be improved from Splunk AppDynamics' perspective.

I have been working with this solution for the last five years.

It has a cost associated with it, but it is scalable only from a scalability perspective. It is scalable.

I have two different types of technologies used in my project. One of the projects was using a different monitoring tool called Dynatrace, a major competitor for Splunk AppDynamics. Discussions were going on whether I wanted to replace Splunk AppDynamics with Dynatrace, and a decision was made to replace Dynatrace with Splunk AppDynamics because of the capability it has with custom metrics and Java agents. However, discussions are now ongoing about potentially replacing Splunk AppDynamics with Dynatrace. I am using these two major tools in my ecosystem: Splunk AppDynamics and Dynatrace.

I monitor all the business transactions such as basket and add to basket via Splunk AppDynamics. I have set up and diagnosed those transactions.

For the others, they get captured as part of the catch-all transaction itself. In case I need them to be investigated, I use filters to identify the transaction specific to the particular BT.

I have not used auto-discovery as a tool such as analytics and the tracing, trace component, and diagnostic traces much. However, I use historical data to understand where exactly the issue is and try to rectify it.

I have not used the anomaly detection and root cause features.

I have not used troubleshooting as a feature.

Regarding Digital Experience Monitoring, I will lose the limit, causing licensing issues. I identified what pages and applications I don't want to monitor and removed them to cope with licensing. Going beyond the license means paying additionally.

I was not using the Secure Application feature.

Currently, I am not using an on-premises environment, so I cannot comment more on the on-premises side of things as I am using a cloud-based application in all areas.

My overall rating for Splunk AppDynamics is 9 out of 10.

I use Splunk AppDynamics' data collection features with agent-based collection.

I am using application performance monitoring with the agent-based application which is injected into the Java application or .NET application to see the response time, the business transaction itself, and snapshots for each business transaction.

I have used Splunk AppDynamics for business transaction monitoring and we are totally depending on application performance monitoring using Splunk AppDynamics.

I am seeing each service in our mobile app, from the login service, CD redemptions, and fund transfer, balance transfer impacting what I can prioritize.

The features I find most valuable in Splunk AppDynamics are Database Visibility, Server Visibility, and Application Visibility.

I see room for improvement in Splunk AppDynamics, specifically in correlation between transactions.

I would appreciate more flexibility for the dashboards because we have more flexibility in the dashboards and real-time capabilities with Splunk, but I didn't find this feature in Splunk AppDynamics. Splunk AppDynamics is collecting data for sampling, not all data, for at least five minutes.

I would appreciate alerting on time, not for sampling, and robust correlation between business transactions as functionalities in the future.

More widgets for dashboards would enhance the experience.

I have been using Splunk AppDynamics since four years ago and Splunk since one year.

I am using Splunk AppDynamics with a staff of 25,000 people in my company now.

For Splunk AppDynamics, I need twelve administrators.

I would rate their technical support from one to ten as seven.

I think they could improve resolution time, as they are fast in response, but they take too much time to fix the problem.

Before Splunk AppDynamics, I worked with Broadcom APM.

I am responsible for administrating Splunk AppDynamics as a team, engineering team, and developing new dashboards while onboarding new applications. We already have in our organization a monitoring team which has detected alarms and reported this instance to the concerned people.

I have seen a return on investment with Splunk AppDynamics, as we are investing more and more for Splunk AppDynamics because we have many tools and many applications in our organization.

I find the pricing of Splunk AppDynamics reasonable for its features.

I switched to Splunk AppDynamics because of the support, as Broadcom does not have good support, but the tool itself is good.

Splunk is a separate environment from Splunk AppDynamics, but Splunk AppDynamics is called by the engineers Splunk AppDynamics or Cisco AppDynamics because Splunk is acquiring Splunk AppDynamics.

I don't have experience with Splunk AppDynamics in hybrid environments, as I only use it on-premises.

I am not using Splunk AppDynamics' AI-powered anomaly detection and root cause analysis right now.

My experience with Splunk AppDynamics' line-of-code level troubleshooting feature in diagnosing performance issues is that we are using many tools for detecting the issues, but Splunk AppDynamics is the majority for detecting issues. When the issue is related to the network or infrastructure, we switch to another tool.

We are not using Splunk AppDynamics' digital experience monitoring because we are stopped by information security due to downloading the SDK with the mobile app itself and then collecting the user experience while having confidential data for our end customers.

I am not familiar with the Secure Application feature in Splunk AppDynamics and I am not using it.

I would recommend the product to other companies. I gave this review a rating of eight out of ten.

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 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.