AppDynamics Serverless APM for AWS Lambda

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.

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.

I work for a supply chain SaaS organization, and Blue Yonder is a global supply chain SaaS company that provides supply chain management solutions for global enterprise customers. For handling enterprise-class customers, we definitely need an enterprise-class product rather than an open-source observability or log management solution. That is why we picked Splunk AppDynamics as our strategic observability and log management solution, and the deployment was completed in a couple of weeks with the help of a third-party vendor.

Log management is the primary purpose for which Splunk AppDynamics is used.

We use Splunk AppDynamics' data collection feature, and using the OpenTelemetry standards, we were able to integrate with our existing set of systems for log management, metrics, traces, and everything that is part of the observability solution offering.

We sell our application management solutions, and the application's digital user experience in Splunk AppDynamics is really good for our global customers. When an external customer is impacted due to application slowness, my support team or my SRE team can go to Splunk AppDynamics portal where we can drill down into the problems, the SLAs, and the response times using this digital experience feature.

For infrastructure monitoring, we are not using Splunk AppDynamics, but for application monitoring, we are using it. The performance is really good and the product features are really good. We have more than 100-plus applications being monitored using Splunk AppDynamics, and for application performance monitoring, the product features are really good.

The team is still evaluating AI-related functionalities in Splunk AppDynamics, but from what I understand from the application owners, they are able to drill down into the application performance impacts during the incidents and they are able to proactively fix the incidents before application portal performance bottlenecks happen.

Splunk AppDynamics did assist me with detecting and protecting against vulnerabilities. It detects the critical vulnerabilities and the legacy things in the larger infrastructure, and it is able to address the critical vulnerabilities in the legacy systems. In that, the product was really useful.

Splunk AppDynamics did help improve my organization's business resilience by reducing the vulnerabilities and the attack surface.

For Splunk AppDynamics, the major headache is cost, and the pricing options are not very flexible. The contract negotiations or the pricing options for a multi-year commitment, along with the renewal cost options, are not very flexible.

In the long run, it is definitely beneficial for an organization like Blue Yonder, because as a supply chain SaaS organization, we are onboarding many customers every quarter, so the infrastructure grows at the backend for the SaaS infrastructure. If the pricing is flexible, we are going to buy more licenses or more quantity.

Internal solutions were developed, but not third-party products prior to adopting Splunk AppDynamics.

The deployment process of Splunk AppDynamics was done by the third-party consulting firm called HCL.

The deployment was completed in a couple of weeks with the help of a third-party vendor. The deployment process of Splunk AppDynamics was done by the third-party consulting firm called HCL.

I rate eight out of ten for the support for Splunk, and for Splunk AppDynamics, I would rate approximately nine for the support our team is getting. I would rate Splunk AppDynamics eight out of ten overall.

We have been using Splunk AppDynamics for around one year and one month and started with just APM pieces for our back-end services and, over time, expanded it to cover business transaction and database monitoring.

The most valuable feature is the end-to-end transaction tracing, which provides genuine insights by allowing users to follow a single transaction across multiple microservices to pinpoint delays or errors, thereby saving hours during major incidents.

The auto-discovery and application mapping feature automatically maps out our entire application technology, showing service dependencies accurately, saving considerable manual configuration time.

The baseline and anomaly detection feature learns what normal looks like for your app, alerting on deviations beyond static thresholds.

A few things genuinely frustrate me about Splunk AppDynamics. First, the UI, while powerful, is dense and not modern compared to products like DataDog or New Relic, requiring a learning curve for new team members. Navigating feels unnecessarily deep, often requiring additional clicks.

Second, the alerting configuration is overly complex. Setting up health roles and policies isn't intuitive, leading to potential alert storms or missed incidents if configured incorrectly.

Lastly, the CPU-based licensing model complicates understanding costs with scaling, necessitating more straightforward processes.

We have been using Splunk AppDynamics for around one year and one month.

My experience with the application performance monitoring capabilities of Splunk AppDynamics has been largely stable. Issues with Splunk AppDynamics performance itself have been minimal. The agents are very reliable once deployed, running automatically without the need for manual intervention.

We contact technical support when we do the implementation and onboarding of Splunk AppDynamics, as it is part of our enterprise contract. Sessions with the solution engineer helped us in defining the initial architecture and sizing, which was fundamental.

We used DataDog previously, which offered a more extensive collection of frameworks, about seven or so. However, we've switched to Splunk AppDynamics for its straightforwardness, simplifying our processes.

The initial deployment is very straightforward if one reads the documentation correctly. All steps are clearly outlined in the documentation, making the setup hassle-free.

Technical support, part of our enterprise contract, assisted us during the implementation and onboarding of Splunk AppDynamics. We had sessions with a solution engineer for initial architecture and sizing, which was beneficial.

Pricing for Splunk AppDynamics is higher, attributed to the additional features it offers over other tools. While the cost is significant given we have around 120 services, it remains manageable and offers the value we're seeking.

Regarding the effectiveness of the features like auto-discovery and mapping, they visualize your application ecosystem. This feature is very useful to us because we don't have to do the manual effort. Using this feature has saved us around 20 to 30% of time. We don't need many people in the environment. If you have four to five people to handle that feature for 400 or 500 products, then we need only one to two people. Thus, it is resource-efficient and saves time.

We use AI-powered features in Splunk AppDynamics such as anomaly detection and root cause analysis. We have Splunk AppDynamics plus Splunk integration apps which eliminate the need for manual checks.

Using the APM, there are features in Splunk AppDynamics which allow for easy troubleshooting of code-level issues, removing the need for manual interventions.

Regarding the downsides of Splunk AppDynamics, we did not have major dislikes; most features are well-appreciated.

Splunk AppDynamics is a solution we recommend to our customers and vendors if they're within Splunk ecosystem, as it saves time and leverages the ecosystem's features.

Our overall review rating for Splunk AppDynamics is 9 out of 10.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

I would rate this solution an 8 out of 10.

We use Splunk AppDynamics for infrastructure, application, and Kubernetes monitoring, as well as private synthetic agents. We use it for all purposes, including as an extension for log monitoring and every extension. We develop any custom extensions as needed.

At present, I am actively working on a private synthetic agent in Splunk AppDynamics, which we have deployed internally in our IKP platform. I am currently working with that by developing Python Selenium scripting.

I have experience with Splunk AppDynamics' Digital Experience Monitoring, including end-user monitoring. For the functionality part in Splunk AppDynamics, I am comfortable with it.

I find all functions valuable in Splunk AppDynamics because I am from the AppDynamics team in my current company. We help with user queries, and the value depends on the use cases, which might be different for each user.

My impression of Splunk AppDynamics' AI-powered anomaly detection is that it functions very well. The anomaly detection gives the exact root cause of what is happening on our server, and for analytics, for every application, we mostly try to configure the analytics to visualize all the things.

Splunk AppDynamics is useful for me and everything is working out fine. Previously, with log monitoring, I might have been a bit unsatisfied with that. As it is integrated with Splunk, that is also very good.

Splunk AppDynamics gives all the metrics that report to AppDynamics, and they work very well and provide precise information from the server. For application performance, it also gives all the business transactions very efficiently. If there are any other things, we can configure them by an extension or manually.

For now, all secure application features in Splunk AppDynamics are good with me. But in the future, I need to go through all of that because while I have experience, it majorly depends on the use cases. I also need to acquire more knowledge on some of the concepts of AppDynamics.

Splunk AppDynamics is very efficient in all those areas. Compared to the cost, it is also very cost-efficient, because that is the main thing for every organization. For all the things concerning metrics, it is also very good for now.

I am somewhat aware of the data collection features in Splunk AppDynamics, but for now, I have not worked on it.

For now, Splunk AppDynamics is a very efficient tool. However, we have a slight complexity where for infrastructure we have to go to one agent, for the database we have to go to one agent, and for the application we go to another agent. For applications also, depending on the type and nature of the application, we have to go to different agents. Different agents mean we need to install different agents. This is something I find a bit more complex.

I have been working with Splunk AppDynamics for two years.

I would rate the stability of Splunk AppDynamics a nine or ten because it gives efficient monitoring.

I would rate the scalability in Splunk AppDynamics an eight.

Before working with Splunk AppDynamics, I was working with Dynatrace and DataDog.

I have been working with Splunk AppDynamics for the past two years. Before, I was working with Dynatrace and DataDog. When I came to Splunk AppDynamics, I found it a bit more complex because for everything, we have to go to different agents. I found this part a bit difficult, but since I have been working with it for two years, I am becoming habituated to it.

With DataDog, the UI is very simple. If you compare Splunk AppDynamics and DataDog, the UI accessibility and all the things are very simple there. There will be only one agent present where we deploy all the things. The configuration of alerting policies, which you configure in Splunk AppDynamics, are also very easy there.

I can confirm that I am still working with Splunk AppDynamics.

I am using Splunk because it might be different from Cisco to Splunk. For now, everything is good with me. I think Splunk AppDynamics is more evolved, so for now, all things are good with me. My overall rating for this review is nine out of ten.