Log Observer Connect is embedded here, but we are facing some delays in centralized log collection and analysis, which can be further fastened. We are collecting all the data metrics and decision-making insights, but all these data-driven decisions coming from different applications are not connected somewhere. A consolidated form or correlation of these insights is not happening between each other due to which we feel we are missing something significant. Some generalized feedback includes that predictive alerts or alarms which can be integrated with AI-driven alarms and alerting features should be established so that there is AI-driven intelligence and anomaly detection happening with a complete systematic process in service delivery. Application dependencies are huge, and business and operational dashboards should be improved. Right now there are very interactive custom dashboards, and every now and then, the personalization of enhancements keeps happening. KPI monitoring, executive reporting, and analytics have definitely been introduced to a great extent. There are few things in cloud-native monitoring, such as integration with AWS and Azure, where we sometimes do face lags. Those things can definitely be improved upon. I have used Datadog and Dynatrace before using Splunk Observability Cloud. Datadog was definitely recommended by most of our peers because of its very strong comprehensive observability and very strong and unique dashboard systems. Dynatrace was also very good because they have offered a lot of AI-driven analysis methods and processes, which was helping our organization a lot. Since our organization has a very strong IT ecosystem for agriculture, very different kinds of customized things are required.
