"It makes organizing work easier based on its relevance to specific projects and teams."
"The solution is stable and reliable."
"It is a good tool. It allows you to set alerts for application and infrastructure monitoring, and it allows you to create dashboards."
"I like the fact that Splunk APM makes it easy to connect to the application database and run queries against the data."
"Detectors are a powerful feature."
"Splunk APM has helped us to standardize logging and monitoring procedures."
"This solution is very quick to deploy as it is a SaaS solution and integrates with tools like ServiceNow."
"The most valuable features are troubleshooting and optimizing application performance."
"The most beneficial aspect of Slunk APM is the ATM, which is the map displaying the inbound and outbound relationships of the microservices, as well as the traffic between these dependencies. This feature provides us with valuable insights and helps us understand the interactions between different microservices."
"For anomaly detection, the product provides only the last three weeks of data, while some competitors can analyze a more extended data history."
"The cardinality is pretty low."
"The UI enhancements could be a way to improve the solution in the future."
"Splunk APM's performance could be improved - at the moment, it's very slow and takes forever to give me what I want."
"The licensing model is expensive. We need to monitor the amount of data ingested because the cost is based on the data collected."
"There are some predefined metrics.......we may want to create customized metrics."
"Primarily, the logs in Slunk APM can be challenging to navigate and comprehend, making it difficult to understand the details within each log. Compared to other tools like LogDNA, which are more intuitive in this aspect, the logs in Slunk APM can require more effort to understand."
"The UI enhancements could be a way to improve the solution in the future."
"Splunk APM should include a better correlation between resources and infrastructure monitoring."
Monte Carlo is ranked 1st in Data Observability with 1 review while Splunk APM is ranked 13th in Application Performance Monitoring (APM) and Observability with 13 reviews. Monte Carlo is rated 9.0, while Splunk APM is rated 8.2. The top reviewer of Monte Carlo writes "Provides centralized data observability features and has an easy-to-use user interface. ". On the other hand, the top reviewer of Splunk APM writes "Provides great visibility, analysis, and data telemetry". Monte Carlo is most compared with Datadog, Grafana, Dynatrace, Acceldata and Unravel Data, whereas Splunk APM is most compared with Splunk ITSI (IT Service Intelligence), Sentry, Elastic Observability, Dynatrace and Observe.
We monitor all Data Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
