Splunk AppDynamics Reviews

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.

On-premises

Other

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.

Private Cloud

Microsoft Azure

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.

Positive

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.

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.

On-premises

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.

On-premises

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.

On-premises

Other

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.

On-premises

Other

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.

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.

On-premises

Amazon Web Services (AWS)

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.