AppDynamics Serverless APM for AWS Lambda

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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.