Dynatrace Platform Subscription (DPS)

As a site reliability engineer, my main use case for Dynatrace is troubleshooting, configuring alerting, and setting up Dynatrace synthetics and business events to troubleshoot faster for production issues.

A specific example of how I use Dynatrace to troubleshoot or solve a production issue is by immediately looking at distributed tracers and then solving production issues by creating notebooks with Dynatrace Query Language to examine specific business events related to a transaction, tying the trace ID to the business events to get more information.

Dynatrace has positively impacted our organization by allowing us to get to root cause analysis much faster, and it has directly impacted our organization's speed at mean time to repair.

The best features Dynatrace offers are in Grail; having everything in Grail makes it so much easier to not need to click many buttons and be able to pull a very deep level of transaction information just through the query language.

Grail has specifically helped me with my day-to-day work and troubleshooting by enabling me to create general queries that tie between services, as well as gather metadata about those services such as release events, which has really helped us make custom notebooks and custom dashboards that allow us to get better use of Dynatrace with all the features it provides.

Dynatrace can be improved in that DORA metrics can still be improved; there is some beta work happening, but being able to tie in our CI events directly with Dynatrace through webhooks still needs work, and I know it is still being refined. Production troubleshooting is great, but also being able to tie back to the work done with user stories, built in the box, would be great.

I have been using Dynatrace for the last three and a half years.

Dynatrace is stable.

Dynatrace's scalability is very good.

The customer support for Dynatrace is very good. I would rate the customer support on a scale of one to ten as a nine.

I previously used Splunk as a different solution, and I switched to Dynatrace because Dynatrace has more in-house capabilities, better dashboarding, and ease of use.

Before choosing Dynatrace, I evaluated other options, specifically DataDog, but found it too expensive.

I rate Dynatrace overall a nine out of ten because there is always something you can improve on. Regarding Dynatrace's AI capabilities, I believe that its governance and security are pretty good; we work in a very compliant space and Dynatrace has checked all the boxes regarding legal, so I believe that they are ethical with governance and security.

Regarding Dynatrace's AI capabilities, it still needs work, but so far its accuracy and reliability of output have been great. My advice for others looking into using Dynatrace is to not knock it till you try it. My overall product rating for Dynatrace is nine out of ten.

Dynatrace encompasses several areas for our organization, including incident management and release management. We also use it for marketing purposes to reduce MTTD and MTTR. We use it for user journey mapping so we can understand how our customers are experiencing our portals. We have a driver to never have a customer tell us when we have an issue again, and we have achieved that by using Dynatrace with targeted alerting and a robust service management process to support it.

Our use cases focus on reducing customer outages, anticipating customer issues, fixing them before they become problems, supporting digital marketing purposes, managing incidents, and managing releases, alongside fixing some legacy issues encountered once we implemented Dynatrace. Lifting the lid on applications helped us see where we were losing business, leading to a positive return on investment. Currently, our main use case is for integration, release, incidents, and more on digital journeys.

A specific example of how Dynatrace has helped in one of those areas involves using BizEvents to map key pages and transactions within our portals, which helps us understand how long it takes for a customer to get a quote, update a quote, or do a mid-term adjustment. We can also look at the quote to buy conversion ratio...

Dynatrace has positively impacted our organization with metrics reflecting a 60% reduction in MTTD, and we continue to reduce our MTTR, aiming to bring it down another 30 or 40%. By addressing some legacy issues early on, determined to hold a quote value of around a million pounds a year, we have seen significant customer experience improvement regarding the quote journey...

The best features that Dynatrace offers, in my opinion, include distributed traces, integration with ServiceNow and Jira for automatic ticket logging, and real user monitoring, which provides significant understanding of how our customers feel when using our systems. I also find logs extremely useful for troubleshooting; logs provide brilliant information...

Improvement suggestions for Dynatrace are challenging, given its complexity and capabilities. However, I do find that some documentation can be quite tricky to read. I believe that enhancing the documentation and providing how-to videos would be beneficial...

I have been using Dynatrace for two and a half years.

I present a nine rating for Dynatrace due to several factors; primarily, the functionality within the portal is outstanding. Dynatrace support, particularly with the ESS agreement, is incredible...

In our organization, we deploy Dynatrace as a SaaS solution, complemented by an ActiveGate server on our private cloud.

We measure the reduction in MTTR and the impact on revenue by analyzing our ServiceNow statistics. We observe the time a ticket is opened and when it is closed...

We acquired Dynatrace through SCC. Our environment comprises two clouds: AWS and Azure.

My advice for others considering Dynatrace is to embrace the enterprise support agreement and engage with your consultants early on, as you will realize value quickly...

My main use case for Dynatrace is observability of production workloads. A quick specific example of how I use Dynatrace for observability in my production workloads is to monitor and observe the performance in context of various applications that our company runs.

Dynatrace has positively impacted our organization because we had various tooling before, with different teams using different tools, leading to our observability and monitoring being dispersed across several tools. We consolidated that down into a single tool being Dynatrace, bringing everybody into one platform and one pane of glass.

This consolidation to one platform has affected my team's efficiency and collaboration by showing the biggest improvement in cross-team collaboration and visibility. The NOC is able to see across the various products and services during live issues without having to jump into different tools to see the context; it is all there on that single pane of glass, which greatly improves efficiency and reduces our mean time to resolve.

The best features Dynatrace offers are the ease of administration and configuration, the single pane of glass, the contextual view of logs, metrics, and traces, and overall, it is a well-balanced product.

The single pane of glass and contextual views have helped me and my team day-to-day by making things easier when we are troubleshooting issues in production because we get the context of one application versus the other applications in the environment, which is easier for pinpointing root cause analysis. Having the various metrics, logs, and traces all in a single pane of glass provides comprehensive visibility.

For me, the main area for improving Dynatrace is in the architectural overview map that they provide; it would be beneficial if it were simpler to use because it is currently a little cumbersome.

The tool that I refer to when discussing needed improvements is called Smartscape. I find that it is a little overwhelming and cluttered when I access it, so simplifying that Smartscape tool would be of great advantage.

I have been using Dynatrace for two years.

Regarding Dynatrace's AI capabilities, we do not use the governance and security model at this stage. Regarding Dynatrace's AI capabilities, its accuracy and reliability of output seem solid.

Dynatrace is deployed in our organization using public cloud, on-premises, and we utilize the SaaS offering from Dynatrace. We use GCP, AWS, and Azure as our cloud providers. I do not think we purchased Dynatrace through the AWS marketplace.

The advice I would give to others looking into using Dynatrace is that it offers the ability to have more than one tenant, so I would always recommend setting up a sandbox environment alongside the production environment and possibly even a non-production environment, just to split up the various environments and provide the technical teams with a sandbox in which they can confidently configure and change things without impacting production. I would rate Dynatrace a nine out of ten.

My main use case for Dynatrace is that we find it to be a good tool for working with establishing analytic models for our customers' front ends or providing dashboarding for customers in relationship to their operations.

Regarding my main use case with Dynatrace, it helps with the ability to formulate a single pane of glass in regards to working with automation and operations, including DevOps into an API or an MQTT model, which allows you to monitor the orchestration of how updates are being managed and handled, how effectively those deployments are progressing time-wise and personnel-wise, and to expedite the course of upgrades and so on without introducing infrastructure overhead while allowing everyone to see what is happening at once.

Dynatrace has positively impacted my organization because reporting is ongoing and constantly evolving to adapt to the new technologies that are being introduced, such as AI and other standard protocols of reporting and metadata. The key advantage here is that Dynatrace has a good position in this space by being flexible enough to accept variations and bring in unknown footprints of AI and APIs that will introduce new data sources, giving it a chance to be very flexible in receiving those new standards with very little overhead. Not everything can come in quickly, but many things have, and Dynatrace is particularly good at that.

Specific outcomes or metrics that show how Dynatrace has helped my organization include its helpfulness with RCA reporting for incident response. The key details here are that you have to understand when something does happen, whether it is a fault on the service side or a fault on the customer's side, and understand the brief hiccups that cause outages and impacts. The RCA reporting process for determining the cause, conducting a causal analysis, recovery causal analysis, and measuring the effectiveness of that response to justify and explain when things happen, specifically in the incident report response, has been valuable. When this is done holistically within the reporting analytics tool, it can greatly reduce the investigation time period to completion. The key detail here is that when an RCA investigator report is initiated, all of the top skill sets are engaged in that process, which represents a great deal of money and time that is lost because all team members, in their own capacity and relationship to the investigation, have to stop, do the analysis, reach a conclusion, do a follow-up corrective action item planning model, and schedule an ETA to get that accomplished. Those are very important details that take a lot of time, and Dynatrace helps reduce that time frame.

The best features Dynatrace offers are somewhat subjective as it does not do anything functionally unique compared to others. However, it does work very well with integrating into other environments or working in tandem with other environments. A reporting tool like Atlassian allows you to generate analytics reports for leadership structures and documentation in regards to that kind of support. This is valued because when we work with tools such as DataDog or New Relic and other major monitoring platforms, we can send all of that information into a very condensed leadership equivalency level reporting matrix that the leadership of your company can actually read, understand, and take steps with and act on because of the way that the tool comes in reporting-wise effectively up into the consolidated enterprise reporting metric systems, such as Atlassian.

Regarding the features, Dynatrace works in two different environments. Its siloed version, the older version, is usually hosted on local infrastructure, whereas its new possible format, the SaaS version of Dynatrace, offers additional value as well as beginning to solidify the AI models that will be under the hood for the Dynatrace engine SaaS model, which adds value opposed to looking at something the server version of the older release of Dynatrace. The value is that SaaS gives you that level of freedom, and of course, the MRU and SLA agreements that you have in place to support Dynatrace SaaS services give you an added level of security that your own siloed environments do not offer.

Dynatrace can be improved by focusing on the model because when you say single pane of glass, it means different things for different people. When you have a single pane of glass for your customer base, and let's say you have 190 customers, technically speaking, that is 190 dashboards that exist and at least a template format with some optimized additional monitoring requirements added to them. However, that is not the same as a single pane of glass for infrastructure, which Dynatrace also serves. There is also a single pane of glass for executive leadership of IT operations and environments, including automation and the SRE Director of Operations role. This is not the same as a single pane of glass for executive management, such as the CIO and CEO, which require a completely different type of set of tools. The preparation of FinOps for finance, SecOps for security, and for automation and operational roles needs to address the company requirements specifically in regards to grid systems or distribution systems. Each of these will have its own version of a single pane of glass, and that is something that Dynatrace needs to be more flexible on going forward.

I would also like to note that Dynatrace needs to have the ability to import additional types of imports beyond standard containers, images, and animations. Animation value does carry significance here and it would be valuable to be able to add that because animation is an initiator. Most companies that use animation in their environments tend to get faster responses and response times as opposed to simply using red, green, and yellow. This can add value to that discussion.

Other improvements needed for Dynatrace include understanding that one tool usually cannot meet all the requirements you need. Being aware of that means being more pragmatic about your approach. By introducing an additional tool or two to cover all the aspects and attributes, technology is always evolving, and you may find a lesser-level vendor who can monitor something newer than what your overall environment is monitoring with something such as Dynatrace. Dynatrace is not really a bad tool when working with other similar services, such as DataDog, New Relic, or Checkmk. Dispersing your resources in multiple baskets provides more reliability, sustainability, and better control of cost factors because you have an easier way of gauging costs between vendors versus services. The key thing is to ensure you have internal and external viewpoints and multiple potential tools such as Dynatrace to help you achieve 100 percent accountability and reliability.

I have been using monitoring tools for about six years, which includes Dynatrace.

Dynatrace is stable.

Dynatrace's scalability is to be determined since we are on SaaS and we have not had a scale event yet, but that is something we will be looking into as we develop the business continuity model.

Customer support for Dynatrace is good, and I have no issues. They have provided good services for our needs. I would rate the customer support an eight.

I previously used many solutions out there. The biggest driving force for me has been getting the most value for the investment for compatibility, integrability, and serviceability to a single pane of glass based on my requirements. This is an evolutionary thing, and while we may be using Dynatrace now, we might switch to something else such as New Relic or another type of tool or even progress to an open-source tool to better control costs in the future. However, all in all, Dynatrace is doing a good job, and we are using it for that reason.

I have seen a return on investment, as my example of ROI is that using a tool such as Dynatrace is an investment that reinforces the customer's desire to want to stay with us. This is crucial because as you integrate these processes, you also want to integrate the investigation process, what we call the RCA process. It is important to move forward with the least amount of time and man hours as necessary while keeping your involvement with other employees as minimal as possible. This enables you to complete the investigation as soon as possible, ultimately saving in operational overhead, productivity, and personnel resources.

Regarding my experience with pricing, setup cost, and licensing, the setup costs and licensing were not a problem for Dynatrace and have not been a problem for most monitoring services. The key issues that were upfront were information processing, data source processing, and housing. We understand that Dynatrace is in business to be in business, but these areas specifically are where you have runaway costs. Your initial investment in licensing costs pales in comparison to the question of why you would charge a license fee and usage for a tool if you are going to be three times higher in processing the data you are sending via the agents. It is really important to know that if you come across costs on the actual operational side, you can use other vendors to help offset that to a small degree, ensuring they do not have a cost covering from something such as data processing or data storage. Alternatively, you could use your infrastructure and local data centers to have an Amazon repository for logs and alerts to get those costs under control. Cost control is very important when using these tools.

I evaluated other options before choosing Dynatrace.

Regarding Dynatrace's AI capabilities, I think its governance and security are only as good as the leadership and the infosec overhead involved. Dynatrace has good templates to meet the AI compatible capabilities, but it always comes down to the human element in the environment. Proper correspondence and response are required at the human level to fully bring the power and capacity of the AI capabilities into its full effect.

The accuracy and reliability of output from Dynatrace are based on two very critical details. One is the contiguous articulation of input that comes in from all sources without interruption. Secondly, an overall average gives you the average reliability with said accuracy. This basically means that if you are tracking everything effectively, when you do have hiccups or impacts, using those capabilities will help identify where you have what we call black holes. The black holes deregulate and devalue the nature of the reliability of this kind of solution because the processing agent configurations may not be monitoring everything necessary, and the importance of the AI capabilities is to ensure they are identified, quantified, stood up, and put in place to help boost accuracy and reliability. That does not always happen and it is human-dependent and must be monitored to make sure that it is done correctly.

Dynatrace is deployed in my organization in both on-premises and some in public cloud that is also deployed with two other monitoring tools, both of which are SaaS-based. We use a SaaS provider for the public cloud deployment.

My advice to others looking into using Dynatrace is to document every application and every infrastructure resource that you have and ensure you place those into a central repository or a wiki. This will allow you to have that information in place to do a comparative design model and see if you even need Dynatrace in the first place. Small to mid-sized companies may or may not have a need for Dynatrace, but this is the most effective way to approach it. I give this review an overall rating of nine.