Splunk AppDynamics Reviews

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.

Negative

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.

We are currently using Splunk AppDynamics for AI automation enhancement in the agriculture ecosystem. In our ecosystem, there is a significant role in monitoring, optimizing, and securing the digital platforms used for agriculture scaling, especially for our large-scale programs including government programs and private programs. In this context, there are many digitized learning modules and learning management system portals, evaluation systems, training portals, and candidate registration portals. All these different clientele applications and software are being used for conducting various activities. Unifying all of them at one place and extracting data insights from them is very critical. That is why we are using Splunk AppDynamics.

Splunk AppDynamics is definitely used for our real-time monitoring because earlier there was a lag in terms of the monitoring and real-time monitoring of the data and platform. Now we are able to monitor the performance of candidate registration portals, our learning management system platforms, assessment applications, evaluation systems, and certification systems. Because we are digesting a large amount of data on cloud-native applications, there is often a problem of slow response time, lag, or application crashes, with the majority of candidate reports showing login failures and server outages. Post-deployment of Splunk AppDynamics, all these detections are done in a very proactive manner and any kind of system anomalies are flagged proactively. Splunk AppDynamics is ensuring uninterrupted access for all of us.

There is a huge and tremendous amount of data being digested and used in the system. For every software, application performance is one of the critical factors through which we generate realistic outcomes, and that was not possible earlier because it is not humanly possible to do this manually, and performance ratings were very difficult for us. We needed visibility as we moved from processing high amounts of data to individual mapping of functionalities, which is being done through this solution. Performance monitoring, taking all the data and monitoring it in real-time and trying to match whether the organizational KPIs are aligning or not, was really important. We are doing real-time monitoring, digitization of our monitoring systems, and using Splunk AppDynamics for analyzing the user journeys because it is a very important experience. We have candidate experience monitoring systems in place, which are being monitored very well by Splunk AppDynamics. Infrastructure and cloud visibility is another critical point. We are absolutely delighted because the deployment of this monitoring of cloud-hosted applications and servers is supporting and supplementing the agriculture skilling programs, which became very easy. Now we can track our memory consumption and network latency, monitor our database performance, and the usage of storage. All these infrastructure monitoring and the security and compliance monitoring are done in a great way.

In the last six months, we are using Splunk AppDynamics for a very strong compliance and security monitoring aspect, where we can detect unusual activities such as unauthorized logins or multiple login attempts, any kind of data manipulation, or tampering with our training and assessment data. These compliance requirements are very critical, and all these things are happening. Additionally, we are using data analytics for program management, monitoring how many active candidates there are, what the assessment completion rate is, training completion rate, and everything. We can now use these things additionally for the last six months, and because of that, a lot of good habits have developed in the system where AI-powered anomaly detection is helping us auto-remediate systems or predictively resolve issues instead of reactively. Things are done in a very proactive way, which is really promising for our clients and internal team.

After the deployment of Splunk AppDynamics, we had very good customer experience. Our clientele experience has improved multifold, and we are not facing any kind of latency or lag time. Downtime performance issues have reduced to a great extent. The performance of various applications has improved multifold, and there is faster issue resolution with a twenty-four-seven resolution system in place through chatbots and tracking systems, which help us a lot. Improved user experience and satisfaction are definitely critical for us because ultimately these last-mile beneficiaries share their experiences, helping us to scale up. Now with compliance and security monitoring in place, we are better audit-ready, and all kinds of anomaly detection or threat detection are happening in a very advanced manner. There is reduced manpower-driven manual monitoring, and now the system does automatic red flags and alerts us of any incoming threat. Real-time dashboard visibility gives us real-time data insights. All these things are great features of Splunk AppDynamics.

The strategic use cases and value proposition were the main advanced features which have helped us multifold. There is increasing reliance on digital platforms for training, assessment, certification, apprenticeship, and candidate lifecycle management, and Splunk AppDynamics has acted as a comprehensive application performance monitoring solution for us. This has brought a lot of business intelligence. The business intelligence for supporting and scaling it was earlier lacking, and we were unable to finalize action plans for our future. Now it has changed the way we work and think. It has definitely helped in terms of visibility because we have end-to-end visibility across any kind of skilling journey, monitoring every stage. There are approximately ten critical stages including candidate registration, training phase, assessment phase, and certification phase, all of which are being monitored critically, and we have been able to improve compliance and reduce processing days. Now we can monitor real-time status of the batches and improved evidence upload success rate, and certification pending cases have reduced. Visibility has improved so much that we track login patterns, starting time of programs, validation across various stages, training and assessment completion rates and timelines; everything is monitored critically. The system is also embedded with early warning systems for alerts wherever delays happen or mismatches in processes. Earlier, these things were hidden, causing a lack of transparency in the entire process, but after this implementation, it is amazing to monitor APIs and their response times, functioning, failure rates, synchronization delays, or data integrity issues. These critical areas were highlighted by clients, impacting our success and failure significantly. Now, they are the foundation of the entire monitoring, and it has become possible after the deployment of Splunk AppDynamics, with these parameters providing confidence and credibility in the market.

The foundational pillars of Splunk AppDynamics are very strong, and we do not have any issues. However, there are standardization challenges with limited visibility on some parameters when the system is integrated with multiple platforms because of differing technology stacks. Many applications function on different technologies, making fetching data difficult. We have discussed this with the business team, and they have said that they will offer a standardized application architecture through which APIs can be made more stable and accommodating. We have also requested a centralized monitoring framework and network, as many clients operate out of India and have requested centralized systems for real-time performance monitoring with just one click. Improvements and enhancements are happening weekly, and there are requests for regular training and orientation. I believe those things can be incorporated, but otherwise, everything is fantastic.

For the agriculture ecosystem, there are many areas in remote or rural areas where connectivity constraints are huge. Limited internet bandwidth makes real-time monitoring difficult. We have requested the team to develop a hybrid model for real-time monitoring on lower bandwidth as well. Deploying offline-first or low-bandwidth solutions would strengthen synchronization. Additionally, mobile applications for rural environments would be beneficial. In data quality and governance, sometimes the system gives duplicate records, and there is inconsistency when checking data fields. It is not frequent, but we believe a complete solution can be developed here.

Almost two years

Splunk AppDynamics is very much stable. We have faced no server lag or data capture issues. I can confidently say it is stable and scalable for our large-scale government operations. We are using it for two years without facing any downtime or outages.

Improved platform availability and reliability highlights improved performance management. Our operational efficiency increases multifold, and service delivery has contributed to revenue growth and business expansion. Earlier, we worked across thirteen to fourteen states, but now we have expanded to twenty-nine states due to improved scheme execution and fund utilization. There is increased candidate confidence, and real-time monitoring ensures timely completion of our project milestones. Previously, I was able to complete only one or two projects in a year, but now I manage three to four similar projects simultaneously without hassle. Reduced delays have boosted our people's confidence, leading to more productivity enhancements and better resource planning.

Customer support is excellent, and I would give it ten out of ten. The twenty-four-seven customer support is very good, resolving tickets in twenty-four to forty-eight hours. It could improve to twenty-four hours maximum since many applications offer swift responses. The chatbot system is well-structured and does not provide shallow answers. It dives deep into questions, leading to effective solutions, often making it feel that a human is resolving issues at the back end. I give them ten out of ten for these reasons.

We used another solution, one of the most comprehensive APMs, back in twenty twenty-one. We were trying out multiple platforms. We used New Relic and Grafana, which were affordable and also good. We stopped due to compliance objections and found New Relic great for budget-conscious organizations.

There are unique cases where we are attracting high-performance centers to our sector, which was not the case earlier as the transparency has increased so much in the system. People see our strong processes and are attracted to us, becoming clients and users. Because of a focus on our quality system, we are recognized in the market for our quality delivery. Many people are coming to us and participating in programs, leading to increased revenue. Our organization revenue has doubled after the introduction of Splunk AppDynamics and other features. We have been able to do a lot of justice to the entire systems. Additionally, our costs and expenses have reduced multifold because earlier we had four to five applications for monitoring and reporting. Now everything is done in a unified way through Splunk AppDynamics, providing a lot of benefits and reducing burdens. Our leadership position has improved in the ecosystem, and because of increased business observability beyond technical monitoring, improvements in business outcomes have resulted in people depending on our system to get their main tasks done. All in all, it is a great time and a win-win solution for anyone becoming part of our system.

We studied a few platforms to check their application monitoring, observability, analytics, and business intelligence capabilities against our requirements. We evaluated New Relic and Grafana and also considered Dynatrace, an AI-powered solution widely used in large government and enterprise ecosystems. However, our governing board did not approve it. We also looked into Datadog, recommended for cloud-native monitoring analytics, which was useful as we had multi-cloud systems. There was another solution called Site 24/7, which was also good for large-scale deployments, but we were not looking into that at the time. After evaluating these options, we decided to switch to Cisco's Splunk AppDynamics.

Splunk AppDynamics is a powerful and reliable solution for application performance monitoring and strengthening compliance requirements. Every organization has different priorities; for us, strong APM was the priority. This solution was outstanding, and even during the trial, we were sure we would choose it. It is slightly higher on the pricing front, but it is very reliable. If you go for it, have your trial, discuss customization with your team, and if it meets your business needs, you should definitely proceed with it.

Cybersecurity and compliance monitoring features are highly rated because we deal with large volumes of personal data under data protection and policy acts. We are advised that the personal data of millions of Indians should not be leaked. That is why cybersecurity and compliance are critical for our system. Through security monitoring, we can detect unauthorized accesses including credential misuse, data leakage attempts, suspicious activity, or data leaks occurring in the ecosystem. All these are monitored critically, and we receive alerts and red flags. Additional compliance requirements improve data governance processes. We use AI-powered operational intelligence embedded with predictive analytics for forecasting priorities, identifying system failures, overloads, and bottlenecks. Root cause analysis is performed, leading to the removal of server issues, application issues, and database bottlenecks, greatly helping us. I give this solution a rating of nine out of ten.

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.

I have been using Splunk AppDynamics for almost four to five years now.

My main use case for Splunk AppDynamics was initially a very limited requirement for monitoring the performance of different applications we have, aiming to achieve real-time full stack observability of all platforms and their impact on our business productivity and client requirements. Currently, we are using it widely for innovating agricultural use cases, actively automating our supply chain in agriculture, utilizing IoT sensor networks, and securing our precision farming platforms. These tools handle massive amounts of machine-generated data within the Indian agricultural ecosystem, and Splunk AppDynamics has proven its worth every year.

A specific example of using Splunk AppDynamics in one of our agriculture projects relates to optimizing crop yields and preventing equipment downtime in farm mechanization. Through Splunk Apps, we streamline our extensive sensor networks, which are crucial for precision agriculture. Soil moisture, temperature, and humidity must be regulated, as failure to do so can lead to disastrous outcomes, and Splunk AppDynamics monitors these conditions twenty-four hours a day, seven days a week. It aggregates data, tracks environmental conditions, and provides customized insights tailored to specific soil and states, achieving prediction accuracy of approximately ninety-five to ninety-nine percent.

Furthermore, we monitor our digital dashboards and mobile apps for controlling irrigation systems and tracking crop health, which helps ensure compliance with food control environmental regulations mandated by the CAG audit in India, making Splunk AppDynamics truly a savior for our organization.

I have additional insights into our main use cases with Splunk AppDynamics. Previously, we lagged in real-time data insights and observability of farmers' applications. Earlier, we experienced reporting and log analytics issues, especially regarding security. However, since implementing Splunk AppDynamics, we are effectively managing farm-level execution with end-to-end operational visibility. There is no lag in data information travel, ensuring seamless data logs from farm to lab. This transparency has fostered client confidence and satisfaction, creating a win-win situation for both users and implementers.

In terms of features, Splunk AppDynamics excels in application performance monitoring, competing favorably with platforms like Datadog and New Relic. It stands out for tracking end-to-end user requests across various environments, which previously posed challenges in mapping and fetching data. The usability and navigability are also noteworthy; business users provide positive feedback about the platform's accessibility without needing extensive training. The automated security features have helped protect our significant cloud investment from threats, identifying potential risks and providing remediation options, making it a reliable choice for our organization's needs.

All the features I highlighted are vital, but performance metrics particularly stand out as they aid in troubleshooting processes by allowing us to identify root causes effectively. This capability ensures recurring issues are addressed at their source. Additionally, we now correlate performance metrics with business outcomes, providing clear visualizations. The deployment of Splunk AppDynamics was smooth and quick, successfully integrating into our business processes and standard operating procedures within a fifteen-day period, which we appreciate.

Splunk AppDynamics positively impacts our organization by allowing real-time performance monitoring, enabling us to optimize various business applications and visibly enhance their performance. We realized the extensive market demand for compliance and governance, especially given potential IoT threats we encountered. Splunk AppDynamics helps monitor performance, diagnose root causes, and streamline the use of complex software applications, improving the experience for users who manage different applications. Client satisfaction has also significantly increased as the application functions seamlessly on both web and mobile platforms, mapping the complete user journey. This streamlined approach in our precision farming sector has resulted in substantial cost savings—approximately one to two crore this year—through effective monitoring.

Regarding areas for improvement, I have not encountered any significant issues with the features we have tested from Splunk AppDynamics; however, we do believe their twenty-four hour, seven days a week chat support could be enhanced and integrated with phone and email options. The automated chat system often fails to resolve issues promptly in a single interaction, which could improve customer experience and support.

To ensure continued improvement, real-time data insights and performance-related dashboard reporting must strengthen decision-making processes. We have requested an anomaly detection dashboard for identifying potential threats, which is vital but has yet to materialize. Increasing dashboard visibility and analytics would significantly benefit our operations.

Splunk AppDynamics proves stable; we have not experienced any outages or significant issues. While minor downtimes may occur, particularly at night, the app remains reliable and effective, even on weekends.

Its scalability has been impressive, accommodating our organization's growth as we expand digital applications and leverage IoT for supply chain management. Our integration of Splunk AppDynamics aids in generating valuable data insights and allows proactive troubleshooting on a larger scale, enhancing operational effectiveness in agriculture.

Customer support from Splunk AppDynamics is fair but requires enhancements in ticket resolution times. We often encounter long wait times for issue resolution, highlighting a need for improved service efficiency as our business volume grows.

Before adopting Splunk AppDynamics, we used Datadog for several years, initially seen as a strong market player. However, the high costs prompted us to search for more affordable solutions, leading us to switch.

The deployment of Splunk AppDynamics was smooth and quick, successfully integrating into our business processes and standard operating procedures within a fifteen-day period, which we appreciate.

In evaluating options before choosing Splunk AppDynamics, we considered New Relic and tested Datadog. The performance consistency and favorable peer feedback heavily influenced our decision in favor of Splunk AppDynamics.

My advice for those considering Splunk AppDynamics is to actively explore its capabilities. It stands out from other platforms, providing real-time monitoring and significant data insights. I urge organizations, particularly in agriculture, to leverage the potential of Splunk AppDynamics to empower their operations further. I would rate this solution a nine out of ten.

My usual use cases for Splunk AppDynamics involve monitoring application performance issues.

I have used Splunk AppDynamics for business transaction monitoring. It helps us in prioritizing business transactions such as logins or checkouts because we can see the transactions, what problems they have, and what we need to do to fix them.

The most valuable features of Splunk AppDynamics that I have found so far include it being a deep-in monitoring solution for applications such as Java and databases. You can dig into the log information and performance information that is within the application. For a very easy setup, you have all the information that you need.

My impression of Splunk AppDynamics' AI-powered anomaly detection and root cause analysis in diagnosing performance issues is that it works and does the job. It's acceptable.

Regarding Splunk AppDynamics' line-of-code-level troubleshooting feature, specifically in diagnosing performance issues down to specific code lines, it relates to the database agent. The help is quite deep and quite useful. You get the code line error, and you are very fast on track to resolve the problem because you will be pinpointed into the real problem where the real problem is using Splunk AppDynamics for databases, for example. That's quite good.

My experience with the application performance monitoring capabilities of Splunk AppDynamics, particularly in on-premises environments, is that it works well for us. We can see that the best benefit is the service dependency mapping regarding different kinds of services. That's key—dependency mapping.

Splunk AppDynamics could be improved or enhanced as they are on track because they have the tools working with OTel. That is one thing I can mention since that has forced us to use other tools to monitor because of the price. Price is the key part here.

I have been working with Splunk AppDynamics for more than five years.

Based on my experience, Splunk AppDynamics has been very stable and reliable for us. As I have mentioned, we have run it for over five years, six or seven years I would say, and I think it's very stable with no problems with the agent or the setup.

I do not think we have counted on the scalability because our setup is not so large; it's quite a small setup, and that depends on the cost. We want to expand, but the cost is quite high.

I do not often communicate with the technical support. I think it's one or two times per year or something similar because it's so stable.

Based on my encounters with the technical support, I rate them at least seven, seven to eight. It depends on the technical question that we asked, but I think the support has been quite acceptable, more than acceptable. From my point of view, it's a seven to eight, which is more than acceptable.

Positive

Before Splunk AppDynamics, I used a different solution for these use cases.

The previous solution consisted of a number of different kinds of tools; I cannot go into details on that, but we used different kinds of other tools.

I participated in the initial setup and deployment of Splunk AppDynamics.

The process was very straightforward; there were a few components and steps that we documented and added internally because we are using Splunk AppDynamics as a SaaS solution. The setup is quite straightforward. Therefore, the setup is not an issue; it's working as designed.

Splunk AppDynamics provided technical help that assisted us in this process.

Regarding whether I have seen any return on investment so far regardless of expenses, I think we can say so because of the problems we had in the past and the fast way we solve problems with the tool. The technical person that is using this is quite happy when they know what to fix.

The overall positive impact and benefits I have seen from using Splunk AppDynamics so far is that the overall function is acceptable. Unfortunately, the setup is quite expensive, which is the bad part of it because I want to spread my agent across the IT landscape, but that's very expensive.

Overall, I consider Splunk AppDynamics an expensive product; it's very expensive.

Before choosing Splunk AppDynamics, I evaluated other options and other vendors.

I chose Splunk AppDynamics instead of the other options I had because of the deep insight you get with agents, especially for the databases and other application frameworks such as Java and .NET. You get quite useful information with a quite easy setup.

I am not using the secure application feature in Splunk AppDynamics.

I don't think we have tested Splunk AppDynamics' digital experience monitoring, so that's nothing.

I would rate this review overall as a six.

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.

Positive

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.

Regarding Splunk AppDynamics, I was exposed to it in 2023, though I did not work extensively with it. It was used for application performance monitoring for an e-commerce client with a vast application setup. They aimed to quantify metrics such as footprint, latency, and performance, so we deployed it in a cloud-based setup covering both SaaS and on-premises applications.

We also utilized a feature to detect high-level vulnerabilities, providing a risk score. However, we focused more on the application layer performance monitoring rather than network performance.

We also utilized it for Digital Experience Monitoring, observing how the application performed across various endpoints, such as laptops, mobile phones, or web browsers. It provided observability and insights into potential breaches in SLAs, helping us understand performance issues across different layers. Moreover, it assisted in monitoring applications interacting with AI models, performing anomaly-based detection for latency spikes or performance reductions.

The app teams believe Splunk AppDynamics enhances business resilience by providing insights into the application context, though I primarily focus on infrastructure metrics. Application teams benefit from it as it distinguishes whether an issue is application or infrastructure-related. It aids infrastructure teams in pointing out application-specific problems when the underlying network layer is clean.

This differentiation is crucial, especially when everything is built on one server, such as the front-end, back-end, and databases.

Splunk AppDynamics is known for its comprehensive capabilities and functionality, providing a 360-degree view of application performance. It assists in adaptive Digital Experience Monitoring and evaluating SLAs to prevent performance degradation.

The platform's performance monitoring feature captures telemetry across various endpoints and scenarios, even including API-specific context. It helps identify whether performance issues are at the application layer by sampling data over time and generating alerts for deviations, facilitating anomaly-based detection. Additionally, it calculates thresholds and notifies any critical performance issues.

Although it does not primarily focus on network performance, it excels at monitoring application performance, especially in API evaluation, time to first byte, mean latency, and other metrics. Splunk AppDynamics also monitors apps interacting with AI models, which is a unique offering compared to competitors.

Splunk AppDynamics, although feature-rich, is known to be expensive. There is an overlap of functionalities with other traditional products, which may lead to redundancies, especially for infrastructure teams who might find it superfluous.

Despite its robust vulnerabilities detection feature, it is not a full-fledged VMDR tool like Qualys or Nessus. For companies already invested in such tools, the noise and overlap from Splunk AppDynamics' vulnerability detection might be unnecessary. It is better suited for smaller enterprises without dedicated vulnerability management solutions.

Overall, although the platform stability and customer support are strong, the added features might not justify the cost for all enterprises.

Platform stability is good. Splunk always had great customer support, an operations team, and technical assistance. Now it is consumed by Cisco, and they are equally doing a fantastic job there.

The support is awesome. After Cisco came in, the overall support and service have become much better, showcasing a notable improvement. It works the way they claim it works, or it is supposed to work. Overall, I rate them as 8.5 out of 10.

We used some professional services because we wanted to implement it quickly. They helped with optimization and setting everything up according to our needs.

Regarding ROI, the reduction in turnaround time, particularly in performance degradation detection and response, improved by around 17 to 18 percent. This improvement helped justify the cost of acquisition, especially for our client, who served APIs consumed by third parties with strict SLAs having financial implications for service degradation.

There are other vendors in application performance monitoring, such as Dynatrace, which are less premium-priced than Splunk AppDynamics. Splunk AppDynamics has always been expensive, and while it leads in functionality, other solutions are available for different budgets.

Splunk AppDynamics is not doing anything uniquely that competitors such as Elastic are not doing. We use PRTG for network monitoring and rely on other tools for network performance telemetry.

We did not utilize its vulnerability management feature extensively due to its overlap and noise, as we already have robust VMDR solutions. Different enterprises may find value in this for small setups needing a packaged vulnerability tool.

Splunk AppDynamics documentation is excellent, and the deployment process is straightforward, especially for existing Splunk AppDynamics clients. Knowing where APIs are is crucial, and the setup typically involves agent and API integrations.

While invaluable for application teams, it might be less valuable for infrastructure professionals focusing on underlying parameters, except as a tool to differentiate application versus infrastructure issues.

Given Cisco's integration, this solution has improved with robust customer support, functioning as expected despite facing high costs and similar alternative solutions. I rate this solution a 9 overall.

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.

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

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

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

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

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

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

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

I have been working with AppDynamics for ten years.

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

Regarding scalability, I would rate it as a five.

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

Positive

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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