Dynatrace is an APM scaled for enterprises with cloud, on-premise, and hybrid application and SaaS monitoring. Dynatrace uses AI-supported algorithms to provide continual APM self-learning and predictive alerts for proactive issue resolution.
$0
per synthetic request
Splunk Observability Cloud
Score 8.5 out of 10
N/A
Splunk Observability Cloud aims to enable operational agility and better customer experience through real-time AI-driven streaming analytics allowing accurate alerts in seconds. It is designed to shorten MTTD and MTTR by providing real-time visibility into cloud infrastructure and services.
New relic was mostly like readonly dashboard and restricted how we slice and dice the data presented to us. Ability to drill down was seriously limited.
Dynatrace UI seems better compared to splunk also DT gives better flexibility in terms of plans and costs. For logging monitoring we are using splunk and splunk is better for that purpose. But hosts and server monitoring and alerting perspective Dynatrace is better. Dynatrace …
Dynatrace gives the overall picture of the application usage and performance by default with minimal configurations whereas in Datadog a lot of manual intervention is required to analyze the application performance and troubleshooting the issues. Dynatrace is user-friendly when …
Dynatrace has three key points: ease of deployment, ease of access and a very low learning curve. Also the info provided by the DT agents are easy to understand and relate to root cause. Also the user interface is very simple and can be configured/shared to provide the data to …
We selected Dynatrace because it is much more modern and depends on AI, on auto-discovery, and other features, making it really a next-gen monitoring solution. It is not easy to on-board to Dynatrace, as it has an extremely steep learning curve. It is also possible that other …
Some of these tools we use alongside Dynatrace, and others we chose Dynatrace over. Since Ruby is not a Dynatrace supported language, we use New Relic to monitor those applications. We are an AWS shop so naturally, we use CloudWatch metrics for things like auto-scaling where it …
I have used a plethora of Application Performance Management (APM) tools, all have their niche. Dynatrace provides the best-in-class experience for support, operations, and platform engineering teams. In addition, access for my Enterprise Development teams has been critical. …
BMC was only a basic APM with not much detail or drilling into the issue. It only showed there was a problem with the host. Before Dynatrace, to troubleshoot an issue we had to log into different consoles for different applications and review logs. Now with a quick visual and a …
The Dynatrace product was much more feature-rich than New Relic. We went through multiple proofs of concepts with each vendor using our actual system. We found that both did some things the same but in other areas, the Dynatrace product was much better. There was a black box …
Dynatrace is much more expensive than Pingdom, but it does a better job of doing synthetic monitors and the credential store is much better. When it comes to availability it does a better job of creating of synthetic monitors and it can create a credential store which is a big …
I have not evaluated any other monitoring products. Our company has evaluated other products that have not stacked up against Dynatrace. Dynatrace has deeper monitoring than others and provides excellent alerting capabilities. Dynatrace was selected for those features as well …
Dynatrace provides the best insights into our environment from end to end. It provides user sessions throughout the application so, we can see exactly what users are doing and potentially not only fix problems but provide improvements before any issues arise. There is no …
Splunk is superior in many ways to these solutions when I'm comes to ingesting, storing, manipulating, and using data, but dynatraces automatic agents do make it much easier to use out of the box. Nagios seems much cheaper but does not provide as much functionality as Splunk. …
it could stack up against this version of Splunk because in this instance of having the cloud option as an available use case it furthermore has more use cases and the options for the data to always be readily available will furthermore allows for analysts to review the data in …
Datadog pushes intom proprietary ecosystem and pricing structure.Compared to self hosted prometheus and grafarna but it gave headache og managing our own monitoring infrastructure at scale.Prometheus is excellent for scraping cluster metrics but it doesnt handle distributed …
I guess scale is the main factor against grafana and ease of use against amazon elasticsearch service and also i have used signoz and ELK Stack also, but stability Splunk Observability Cloud gives is too good and also it comes with high avability and you have to maintain …
We initially chose Splunk Observability Cloud because it promised full-stack visibility and tighter integration. The other tools didn't offer this as part of the core package. Their analytics and real-time dashboards looked strong during the demo but it turned out to a lot …
I selected Splunk Observability Cloud because it focused so much on OTEL standards which will help us in future as OTEL is covering most of the observability standards. And also it has the best Kubernetes observability as I already explained it has several predefined dashboards …
Splunk Observability Cloud stood out for its real-time data ingestion, native OpenTelemetry support, and seamless correlation between metrics, traces, and logs, which gave us faster root cause analysis and better end-to-end visibility compared to Grafana setups that required …
To be honest, Datadog is very similar to Splunk and LogScale to a lesser degree, but it is just as good if you don't need too complex observability. Grafana is still growing and might reach the same level soon.
It's able to quickly detect and resolve issues across the entire spectrum of deployments including on-premises, public cloud, private cloud, hybrid cloud and multicloud
The above applications have their own use cases. Thousand Eyes or Sitescope is used for URL monitoring and Splunk is used for application monitoring. Appdynamics is also used for application monitoring and can monitor the server very well but it lacks when searching in logs …
SQL is a great tool for smaller quick checks. When trying to monitor several different environments, applications, APIs, several thousand devices, connections, and technology, it just doesn't stand up to what you need. Splunk Infrastructure Monitoring has really stood out …
We are having other monitoring tools like AppDynamics, Dynatrace, Datadog and already using their end-user monitoring capability. Most of our customers are looking for agent-free monitoring where they don't want to instrument any agent on their client-side (as it might …
Splunk Infrastructure Monitoring provides far superior options for anybody using a complex hybrid multi-cloud environment and allows both your SOC and NOC to work together on the same data while driving their own insights.
We found other products are still in the old world view …
Dynatrace is well suited to a number of tasks. It is important to determine who the end users are and gather good information to tailor their experience accordingly. For instance, business/marketing should not have access to some of the more technical data, and business metrics can be a distraction for IT operations personnel.
Good for below cases 1. There is a front end and need to correlate data with front end data 2. multiple microservices and need to check the health of each system 3. correlate data from various sources 4. Application performance is a key to be captured 5. application performance is a key metric.
We loved Dynatrace's ability to show the data flow - from the front end points through the back end points straight to the database and various API's. It was advanced in its data visualization. This is useful for debugging - showing when/where the errors are. It can even enable non-technical individuals in the corporation to help debug
Dynatrace has some great highly customizable integration options as well as monitoring. You can configure your layout & integration options to create custom monitoring alerts for your applications performance. Further you can increase the extensibility of using a REST API on your architecture.
Some advanced dev-ops systems are utilizing Kubernetes/docker aswell as Node.JS - Dynatrace was able to log and help understand all of our dev-ops needs. It gave us native alerts based off of deviations from the baseline that we set during initial configuration. These metrics are priceless.
The first one is its Kubernetes container monitoring.
I really like this features because as we know how much K8s is vast and to manually monitor each part of the Kubernetes it takes so much time but Splunk Observability Cloud makes it easier. And even once we integrate K8s with Splunk Observability Cloud it gives us some prebuilt dashboards which gives holistic view of our Cluster and its nodes, pods, etc.
The dashbaord feature of Splunk Observability Cloud, it gives us full flexibility to customize our dashboard with a wide range of predefined chart types.
Now it also supports OTEL, which is a plus point for observability. As now everyone is moving towards Otel and in current market there are only few tools who supports OTEL based integrations, Splunk Observability Cloud is one out of them.
Dynatrace does not monitor easily on a C-based application.
The way DPGR is addressed by Dynatrace is not very complete, and not clear. One thing is to mask the IP and request attributes but is not enough, the replay session feature is great but raises serious questions about user tracking.
An indicator for errors on the navigations pane so that we don't have to go through each tab.
As we go more and more cloud maybe you guys can implement a pay-as-you-use strategy so that small companies using it not frequently can also afford it.
That's it can't think of any and it wont let me skip to next question. Thanks
We have got tremendous support and response from the dynatrace support team as well as the larger community. We still have issues like the lack of role based administration, but we are told that it may be coming in a future release. The team is very supportive and has assisted us in several tough situations.
Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net
Dynatrace is great to use once you understand how to use it correctly and get used to the layout of it. While I do not actively use it every day, whenever I do use it, I do have to get refamiliarized with it. However, once you have your dashboards setup correctly with the data that you want to see when you first login to Dynatrace, it's amazing.
Overall a great tool to have in your toolbox, It is very intuitive and our entire staff uses the tool. It is easy to use and cost is very reasonable. Splunk also has excellent support team and very easy to work with. Every time we had a challenge, support team was able to help us with the end result.
I wish I could have given the ten points but based on my experience in past I am reducing by two points as the penalty. But I am sure that it will have improved in the past few months. They need some improvement on ticket handling. Overall I appreciate some of the support folks who responded quickly and also were ready to jump on the Webex and get the problem understood to fix it.
Like I mentioned earlier, Dynatrace is a great tool but comes with a heavy price tag. On the other hand, Foglight offers a slightly lower level of expertise in application monitoring but fulfils almost all the requirements you would commonly have. The only major feature lacking in Foglight is the predictive monitoring feature. If you are an SME struggling with budgets, then predictive monitoring is something you can certainly live without.
To be honest, Datadog is very similar to Splunk and LogScale to a lesser degree, but it is just as good if you don't need too complex observability. Grafana is still growing and might reach the same level soon.