My main use case for Dynatrace is logs and tracking metrics, mostly API latencies, to find API latency metrics and monitor whole services and microservices.

About my main use case with Dynatrace, I will add a few things: first is that we create a custom dashboard, which is very helpful for us to monitor multiple microservices, since the application relies on multiple services. Then we have a few features including error detection, such as how many 4xx error rates are coming, what 5xx error rates are coming, and what are the client-side and server-side problems. Those kinds of built-in Dynatrace alert systems we can use for latency and error classification. We can link those things into channels such as Slack, email, or mostly PagerDuty, so the on-call person will receive these alerts.

The best features Dynatrace offers include AI-based metrics collection, which impresses me a lot because it is very helpful to quickly check all the issues that come up. The first thing is end-to-end visibility across all the services. That is one thing where we can know the infrastructures, hosts, containers, VMs, and what is happening with the application. Then this automatic discovery and mapping helps a lot. Distributed tracing, which is the PurePath thing, is a very helpful feature. For root cause analysis, the recent Davis AI is something game-changing and is helping a lot, saving a lot of time. That is the main feature right now. The remaining things are the foundational features and making access to all the features so quick. Davis AI makes use of the features that exist, and now I am using those features. So that is a good thing.

The root cause analysis feature specifically helps my team save time or solve issues by providing detailed timings and external APIs and cache whenever the PurePath thing comes, to trace every subsequent call. We are not only working with our own microservices; we are working along with multiple vendors. Sometimes the latency is not from our system but from a vendor system. During those times, we see why this service is taking a lot of time because this service is waiting for a call. These small details on timings and the DB cache add so much value to the PurePath thing. The AI powered Davis detects anomalies and root cause issues across the stack, which is also a valuable feature. Application topology and network flows are also very helpful. These things are primarily helping us.

Before moving on, I would appreciate the custom dashboard and visualization part of Dynatrace, where I did not talk much about those things. The real-time charts are very helpful to monitor the health of the application. Heat maps are really cool to see, and service flow maps are really required to understand the things. The key performance indicators are very good. These are the key standpoints of my application metrics. Whenever I am the on-call person in PagerDuty, these are the things I am fundamentally looking for. This is a lookup book for me to make sure this application is in good health.

Dynatrace has positively impacted my organization by allowing us to see very quick action whenever there is an issue with production. We can quickly open the dashboard, see the error rates where it is happening, and perform a quick analysis to find the root cause. That is a huge part. The second part is improvisation; whenever we come to a stable state and have some technical debt to take, we can check what APIs are causing latency and work on those issues, asking why it is happening. Sometimes it leads to redesigning the domain, coming from the dashboards. Every time we do not know how many services exist or why a particular service is working for this domain while we are in some centralized stage. But while coming to this Dynatrace dashboard, seeing all services in one place helps us think why this service is talking to this service. We can classify domain-level and regroup the domain. This way, it is helping us by giving a mental model and a mental map to track everything. That is a huge win for us.

I think Dynatrace can be improved in dashboard creation, as this is the face of a product. Although Dynatrace may have many things, new users typically do not know the whole power of the product. To onboard new people, it would be beneficial to provide template dashboards or suggested dashboards. Organizations working with microservice architecture will follow some templates, so suggesting simple, hand-picked features that are really helpful could make a difference. Quick configurable and customizable templates would be very useful. Whenever they come into the product, they can use this template and feel that their product is applied to it. Immediately, they will think everything is online and can improve easily. This base can be provided in template form. Since Dynatrace has a lot of features now, the AI integration makes it simple, but the product itself is very huge. To understand and utilize it, maybe it would be good to index the essential features.

Previously, we used Grafana as a different solution. We switched because Dynatrace provides better overall metrics, but switching the solution is not my decision; it is an organization-wide decision, so I do not have much influence there or comment on it.

There is definitely a return on investment; I see time saving. Also, the employees working with operations do not require that level anymore, so we can reduce a few.

My experience with pricing, setup cost, and licensing indicates that it is a bit pricey, but it is very much worth it. We can maintain licenses as a product that we must own because this is an alerting system and metric system. The product I am working with is critical, having millions of users coming and going; it is the health monitor part of that product. It is essential, and it is okay to spend that money.

Before choosing Dynatrace, we evaluated Grafana, and we considered moving from Grafana to Dynatrace because of specific benefits. We had our own trade-offs, and ultimately, we chose Dynatrace.

I would advise others looking into using Dynatrace to set up as many metrics for the product they are using as possible, and I ask them to create dashboards to monitor.

Overall, Dynatrace is a good product; I will definitely suggest it. It offers strong usage while addressing production issues and health monitoring. It is a very good product. I rate this product an eight out of ten.

My main use case for Dynatrace is for observability monitoring, specifically to know performance, end-to-end monitoring, and root cause analysis.

From the application side, we need monitoring for the latency, error rate, and request count for the transaction, and also for the digital experience; we want to monitor the analytics of user application. Additionally, for the infrastructure, we want to monitor the utilization of CPU, memory, disk, and network.

For monitoring transactional, it means how many transactions come to our customers in banking.

The best feature Dynatrace offers is APM. When I mention APM, I am referring to Application Behavior Monitoring, and database monitoring is what makes that feature stand out for me.

Database monitoring is very helpful to know the performance of query performance, meaning how much latency there is for the query once called from the application side, and if there is an error from the query, it indicates issues such as ORA errors from Oracle or other errors from PostgreSQL and MySQL or any DBMS.

Dynatrace positively impacts our organization because it is a unified monitoring solution that centralizes the performance of infrastructure, application, and database.

Dynatrace can be improved from the security side because other observability products are enhancing security features, while Dynatrace has room for improvement in this area.

For integration, Dynatrace can improve with WebMethod because it is quite common among our customers using that platform, and they want to monitor their transactions for ESB, which is middleware.

Dynatrace could improve its recommendations, which are not only for cause analysis but also for application performance, infrastructure, and database, including database tuning for the query. I would rate Dynatrace an eight for these reasons.

I have been using Dynatrace for around six to seven years.

Dynatrace is stable.

The scalability of Dynatrace is very significant, especially considering the current improvements in their features, and there is a big opportunity from Indonesia with many use cases for Dynatrace.

The customer support from Dynatrace is very helpful, as they assist our customers effectively when there are problems on the platform side.

I have previously used different solutions such as Datadog and Instana because our customers are selling three products of observability.

For the investment, Dynatrace is very helpful for our customers because they can see the transactions through Dynatrace and save money by identifying problems, thereby reducing monetary losses on their application side.

For pricing, we use the Classic model, specifically DPS, which stands for platform subscription. The cost can be controlled from our side, and it is very transparent with Dynatrace regarding DPS and licensing.

The first time we used Dynatrace, we did not evaluate other options, but later considered Datadog, Instana, and Elastic APM.

My advice for others looking into using Dynatrace is that recommendations are very helpful for our customers, as many products provide numerous recommendations. However, Dynatrace focuses mainly on monitoring operations and providing root cause analysis without offering much in the way of recommendations, which I believe is important for observability products.

Our company has a business relationship with Dynatrace beyond being just a customer; we are both a partner for local support and a reseller for licensing. I rate this product an eight out of ten.

Dynatrace's main use case for our organization is incident management, primarily driving alerts, traces, and incident management for production servers on both Linux and Windows 2016 servers.

A specific example of how I use Dynatrace for incident management is that it provides our support team members with alerts if a certain service on a server is not working, there is a failure of a particular service, or the server is not performing as needed. We receive an incident for that and trace the server's services uptime using Dynatrace, which helps us diagnose the issue for both Linux and Windows servers.

Our main focus is maintaining the servers' uptime, and Dynatrace helps us minimize server downtime while providing applications and other services to our end user team.

Dynatrace's best features include alerts and the ability to monitor server health, such as CPU utilization, memory utilization, disk space utilization, as well as network services, and it also helps with application performance monitoring (APM).

I find server health check resources utilization, network monitoring, and APM most valuable for our team, as it helps our other cross-functional teams that require that data to track network health and application health. Dynatrace helps all of us in development and operations support, which makes it a really valuable tool.

Dynatrace has positively impacted our organization by helping us reduce downtime, as it was much higher before using Dynatrace. We are now able to minimize downtime for the servers and applications and easily trace and diagnose issues at the infrastructure level using Dynatrace, which is definitely helpful for enterprises using IT systems.

I give it a nine because the one percent improvement is required in itself, since if I provide a ten, then there is no room for improvement.

Dynatrace provides regular upgrades as a software used to provide server health checks, network monitoring, and application performance monitoring, so the team looking into Dynatrace's development provides regular updates. I don't think I can provide any improvements to Dynatrace as an end user.

I have been using Dynatrace for the last two plus years.

In my experience, Dynatrace is very stable and we don't need to do much additional work once it is installed and set up along with its configuration. There is nothing additional to manage about Dynatrace.

Dynatrace is scalable.

Customer support for Dynatrace is well-equipped, and they try to resolve queries if we contact them with any particular issue. They provide quick resolutions.

When I joined my client project work, they were already using Dynatrace, so I don't have any idea of what they were using before that.

Time is definitely saved with Dynatrace, as without it, it is very difficult for support team members to find out where the exact fault has occurred. With Dynatrace, we receive direct alerts on our Dynatrace console, allowing for much faster resolutions, so it definitely saves cost, efforts, and time.

Downtime has been reduced by almost thirty to forty percent in tracking and resolving issues, as Dynatrace logs, alerts, and traces help us go straight to the issue and try to fix it. Regarding cost savings, it has resulted in cost savings of mostly around twenty to twenty-five percent.

I don't have any idea about whether my organization evaluated other options before choosing Dynatrace.

I will definitely recommend Dynatrace as an APM, server health check, and network performance monitoring tool to be used by large-scale or mid-range organizations. I have no additional thoughts about Dynatrace. My review rating for Dynatrace is nine.

I currently work as a Principal Consultant specialising in observability platforms at a technology consulting firm, AI OK. My role involves providing expert consulting on APM and observability tools, including Dynatrace, Datadog, and Splunk.

Previously, at Infosys and Ericsson, I led initiatives focused on observability platform adoption. Since February 2020, I have been designing and implementing centralized log management and observability solutions, with extensive hands-on experience in Dynatrace SaaS for performance monitoring and service reliability.

The problem detection and problem lifecycle presentation in Dynatrace is excellent. For example, when traffic increases from ten requests per minute to fifty requests per minute or even one thousand to twenty thousand requests per minute, I can see how the services' response time changes according to the traffic change and what the CPU time is for that particular request or API. This gives insight into all the components responsible for response time.

Another valuable feature is the ability to compare performance data from one week earlier or from the same time window on a previous day. This performance comparison capability is very helpful.

The ease of use is remarkable. While we have similar compute monitoring on Azure side such as Azure Monitoring and Azure App Services with compute utilization, Dynatrace links compute with services and services with code and other components. This makes problem management, alert management, and identifying what needs to be fixed for the development team much easier.

Through Dynatrace feedback, we were able to figure out bottlenecks, plan performance user stories, optimize execution time, and make numerous corrections. The problem lifecycle management is improved, and MTTR is very positive. For MTTD, or mean time to detect, it was previously taking hours and hours, but after implementing Dynatrace, even the L1 team can help detect and pinpoint bottlenecks. Not only has the time decreased, but the accuracy and quality of monitoring have improved significantly.

Problem detection has improved very positively, and the quality of monitoring has improved with the help of Dynatrace. We are saving time, saving workforce, and visibility has increased. Both technical and non-technical teams have greater visibility into how the application is performing.

One significant complaint I have raised with Dynatrace as a consultant is the availability of raw data for logs. While this capability exists, it is quite costly. The free allocation is five gigabytes, but comparing this with other tools such as DataDog, Splunk, or New Relic, the raw data availability on Dynatrace and the export of reports and UI aggregation features could add more value if enhanced.

Cost is a differentiator for Dynatrace. Additionally, security is becoming a feature, and AI-enabled security capabilities will add more improvement areas for Dynatrace.

Feature-wise, Dynatrace rates ten out of ten. However, when comparing feature versus cost, it rates eight out of ten. Not every client is one hundred percent on public cloud. There are hybrid scenarios with some on-premises and some private compute environments. In cases where compute is more CPU intensive, Dynatrace can be costly. Dynatrace is the best fit for customers using runtime compute, which covers approximately eighty percent of customers.

I have been using Dynatrace since February 2020.

There are no stability issues with Dynatrace. One limitation I found concerns agent installation. Although Dynatrace is a SaaS product with frequent agent management updates, installing the agent across all networks would benefit from more centralized management capabilities on Dynatrace.

Platform engineering and observability represent a journey through various tools. I started with open source and on-premises solutions involving flat file processing with the ELK stack. I then moved to using Azure Monitor, and subsequently adopted Dynatrace because of its focus on performance and APM capabilities. Dynatrace's APM features were highly recommendable, which is why I moved to this solution. Since cloud-native was important, I explored Azure Monitor as well.

The ROI is good. Compared with other tools such as DataDog or New Relic, both have their pros and cons with no complaints. However, Dynatrace is performing very well overall in terms of ROI versus investment.

When comparing tools such as DataDog or New Relic, both have their pros and cons with no complaints. Dynatrace is performing very well in terms of ROI versus investment.

If someone is looking for application fine-tuning and bottleneck identification on the UI side, services side, or network side, and they are using cloud as a platform, Dynatrace is the best tool to have everything in one place. I would rate this product eight out of ten overall.

Our primary use case for Dynatrace is full-stack monitoring. We use it to monitor the performance and availability of our applications, infrastructure, and services. It helps us quickly detect issues, analyze user behavior, and perform root cause analysis using AI-powered insights.

Dynatrace has significantly improved our organization by providing full-stack visibility and automated root cause analysis. It helps us detect and resolve issues faster, reduce downtime, and improve user experience. The OneAgent simplifies deployment, and the AI-powered insights allow our team to focus on innovation instead of firefighting.

We use Dynatrace full-stack monitoring because it allows us to trace issues across the entire stack — from user interactions to backend infrastructure. It’s very effective for identifying where problems occur, making it highly valuable for end-to-end observability.

Dynatrace's user behavior monitoring and analysis also works well. It provides powerful insights into user interaction patterns, session behavior, and user experience metrics, which help us understand how our applications are being used.

One of the features I appreciate most is the OneAgent. We only need to install a single agent per host, and it automatically collects metrics, logs, traces, events, and more — without requiring multiple separate tools or manual instrumentation.

We also benefit from Dynatrace’s AI-powered anomaly detection. The Davis AI engine detects unusual patterns, performs root cause analysis, and sends smart alerts — all automatically, which significantly improves our incident response time.

More customizable dashboards

Better log search and retention features

Easier tagging and permission management at scale

Improved mobile app monitoring support

reduction in costpricing

I have been working with Dynatrace monitoring and other monitoring systems for about three years. During this time, I’ve gained hands-on experience with full-stack observability, user behavior analysis, anomaly detection, and automated root cause analysis using Dynatrace.

Dynatrace is very stable and reliable. Its OneAgent runs with minimal impact on system performance, and the platform itself experiences very few outages. Regular updates and proactive monitoring by Dynatrace ensure high availability and consistent performance, which is critical for our continuous monitoring needs.

Dynatrace scales very well across different environments, from small setups to large enterprise systems. Its automatic discovery and instrumentation make it easy to manage thousands of hosts, containers, and services without significant overhead. The platform handles high data volumes efficiently and maintains performance, making it suitable for dynamic cloud-native and hybrid environments.

My experience with Dynatrace customer service and support has been positive. The support team is responsive and knowledgeable, providing timely assistance for technical issues. Additionally, the available documentation and community resources help resolve many questions quickly. Occasionally, complex issues may require escalation, but overall, the support experience is reliable.

We previously used a full monitoring system with Zabbix, which worked well but required a lot of manual configuration and maintenance. With Dynatrace, we benefit from extensive automation tools that significantly reduce manual effort. This automation is a key difference that sets Dynatrace apart from Zabbix and other monitoring solutions.

The initial setup of Dynatrace is generally straightforward thanks to the OneAgent, which automates discovery and instrumentation across the environment. However, configuring advanced features, custom dashboards, and integrations can be more complex and may require some learning and planning. Overall, the automation significantly reduces manual effort compared to traditional monitoring tools.

Dynatrace is ideal for clients who need advanced, automated monitoring. However, some clients may not fully understand its value and might not need to invest in a high-end solution if their requirements can be met with free tools like Zabbix.

The SaaS version of Dynatrace is typically suitable only for proof of concept (POC) purposes. When customers commit to Dynatrace, they usually opt for the managed version for production use.

Overall, I would rate Dynatrace 9 out of 10 as a product solution.