We performed a comparison between BigPanda and Dynatrace based on real PeerSpot user reviews.
Find out in this report how the two AIOps solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution is user-friendly and has good performance and certification."
"The event correlation is really good and it is able to reduce the noise. It is a good tool for anomaly detection."
"We have also made extensive use of the outbound integrations to ticketing systems (JIRA) and collaboration tools (Slack). The main driver for us has been getting all alerting into a single UI and enabling us to streamline our incident management process."
"The program is very stable."
"One of the most valuable features of BigPanda is its user-friendly interface."
"Alert aggregation was the primary requirement. BigPanda pulls all this together into a single UI for us, allowing us to see related alerts grouped together into an incident, and enables us to easily create a JIRA ticket and Slack channel to manage an issue."
"The most valuable features of BigPanda are the API integration was good. It enables us to do faster onboarding."
"Easy integration - We've had challenges in the past integrating all of our various monitoring sources and tools into one central system. BigPanda, with the integrations that it already has, as well as offering webhook/REST API, has made it very easy for us to plug everything in."
"In terms of explaining to a customer how their data works, it has been a great tool. Instead of trying to draw it out, then hoping that is exactly where the data goes."
"Since things are getting more complicated, it is nice to have artificial intelligence to correlate issues and events to come up with root cause."
"Since we have been receiving alerts from Dynatrace, we go ahead and fix them without the user knowing about them."
"Dynatrace has reduced our total headcount in operations and the mean time to detect and resolve problems. As a result, those challenging offline times are much shorter, if not non-existent, because of this solution."
"Data analytics help us to find us issues in the short-term or long-term."
"Dynatrace shows the customer path, common errors on desktop and mobile, and allows us to achieve faster page loads."
"Global overview of all app layers, including web servers."
"We setup triggers for certain critical events. When these events happen, alert notifications are sent to the support team to take immediate action."
"BigPanda could improve by syncing its threshold settings with Dynatrace to align with users' familiarity."
"Our infrastructure is quite large - tens of thousands of servers, often with 30-plus checks running on each host with one minute intervals. This generates a lot of data often in bursts (when we have a large scale failure). This has caused some delay in the ingestion pipeline."
"BigPanda can improve the correlations. We didn't see any big value. It is still good at the same event deduplication, event processing, and ticket creation, but I was more looking at event analysis and event correlation. In that area, it is still no big difference between the other solutions on the market. All of them, are in the same immature stage."
"The usability needs to improve, because it is a pure code environment."
"The observability can be enriched with regards to infrastructure and the application-integrated environment. The dashboard and reports could be improved."
"The UI for this solution could be improved. It is very hard to find what you are looking for."
"Analytics is an area for improvement, being able to break down the actions that are being taken by users of BigPanda, as well as the auto-magical work that is being done by BigPanda."
"The cost of this product is too high compared to New Relic."
"Documentation is slightly in error as far as directory set ups and guidance. We came to our own solution for distributing the disk loads."
"The web interface, in some cases, is a little ambiguous to use."
"Where we are struggling is being able to pull that information out and combine it with other contextual information that we have in other sources. Mining that data in a big-data environment, and joining it together and coming up with larger types of analysis on it."
"The initial setup was relatively complex because we were trying to implement into environments that they did not yet support."
"The plugin architecture is not very flexible, which makes it difficult to add the custom monitoring not available through Dynatrace, specifically around file monitoring."
"The thing that is preventing us from moving forward with Dynatrace right now is that we can't tag our customer traffic with a customizable tag. All of our students have a unique identifier and in AppMon we tag that and we can search by it very easily and it's very useful. But in Dynatrace, you can't yet customize and find people like that, so that's really preventing us. I heard that it's being worked on but I'm not sure when it's coming out."
"In the next release, I would like to see some new reports and more tiles on the Dashboard."
"Waiting for the session replay needs improvement."
BigPanda is ranked 15th in AIOps with 12 reviews while Dynatrace is ranked 2nd in AIOps with 342 reviews. BigPanda is rated 7.2, while Dynatrace is rated 8.8. The top reviewer of BigPanda writes "Offers comprehensive alert monitoring and a user-friendly interface but requires manual validation to provide accurate alerts". On the other hand, the top reviewer of Dynatrace writes "AI identifies all the components of a response-time issue or failure, hugely benefiting our triage efforts". BigPanda is most compared with ServiceNow, Moogsoft, PagerDuty Operations Cloud, ServiceNow IT Operations Management and Datadog, whereas Dynatrace is most compared with Datadog, New Relic, AppDynamics, Splunk Enterprise Security and Azure Monitor. See our BigPanda vs. Dynatrace report.
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There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitoring. We maintain critical processing on our mainframe so there was a desire to include this in our transaction trace. Due to a highly mature ELK implementation, we are not trying to incorporate log analytics into solution buy may consider in the future. We had AppD, Dynatrace, New Relic, and CA Wily all in house at the time of our evaluation. We eliminated Datadog due to a lack of real user monitoring and AppD based on experience and licensing. Between Dynatrace and New Relic, Dynatrace won based on the automation, integrated AI, support for "old" techs, and confidence we could eliminate multiple APM and infra monitoring tools.
I would not include products like BigPanda, MoogSoft, in this analysis. They are not monitoring solutions but event correlation solutions. You will need additional monitoring products to capture data and feed them. Having said that if you cannot consolidate tools you will likely need to purchase an event solution to make sense of all the alarms. We did evaluate these products but with Dynatrace AI did not feel the business value was there for the investment.
Here's a quick pro/con list on Dynatrace & New Relic from our analysis.
New Relic Pros: Insights is an awesome product and capability. Lots of capabilities and plugins to extend data collection. The APM dashboard is aesthetically pleasing and intuitive. Good training and documentation are available to support the product.
New Relic Cons: Requires lots of manual configurations to implement and support. Insights product requires an investment of time to achieve value. Licensing is a nightmare as there is virtually no transparency in what you are being charged for. Lack of solution to consolidate alerts across implementation other than significant investment in insights to manually achieve this.
Dynatrace Pros: Very simple to implement and maintain with out of the box automation which supports modern (cloud/Kubernetes) and "old" (mainframe). In-app chat is helpful. High integration of infra and APM data for full-stack observability and engineering. Topology and trace discovery is more reliable than other products or our CMDB. Synthetics are easy to set up for any user. AI-assisted problem analysis on the trace discovery streamlines troubleshooting. AI includes "events" in an analysis like VMotion, deployment events. Have not done yet but looking to leverage monitoring as code for a fully integrated and automated delivery pipeline. See keptn.sh open source project.
Dynatrace Cons: User SQL lacks some functions of NRQL for user analysis. Host, process, and service data is not available to query within the product. Alarm processing lacks some granular controls. The Plug-in library is less robust.
Good luck with your decision!
We are currently going through a paper-based analysis to select an Enterprise APM solution.
Our Contenders are
1. Dynatrace
2. Cisco(AppDynamics)
3. Broadcom DX-APM
Shortlisted based on existing relationships with other products and services they provide.
We discounted New Relic- despite their growing capability - as they are yet to enter the enterprise APM solution scene.
With regards to your response "We eliminated Datadog due to a lack of real user monitoring and AppD based on experience and licensing .." :
Will you be willing to expand on Appd - what was your experience and issues w.r.t licensing. These could help us with our evaluation. Much appreciated. Regards Adrian
Could you please share your requirements ? There are a lot tools can be added to the list. I spent almost 6 months to test and check many tools then I select eG enterprise.
Thanks