One of the best things about Splunk Cloud Platform is that any type of data can be brought into one platform and worked on. This flexibility is very useful in real-world scenarios. For example, logs are ingested from multiple sources, and then dashboards are built for visibility. Alerts can be created for incidents, and meaningful custom dashboards can be created depending on the client's requirements. Trends can be tracked easily, such as trends of servers. Insights can be shared with teams. Since it is cloud-based, infrastructure does not need to be managed as Splunk handles back-end operations. This saves time, effort, and cost. For Enterprise, a particular infrastructure responsibility would normally need to be handed over to a particular team or person, but that team could be negligible by using Splunk Cloud Platform. Splunk indexes logs as they are ingested, and by using the SPL language, Splunk Processing Language, particular data can be searched from the indexed data. Indexed logs are stored bucket-wise, so there is never randomness of the data. When searching for a particular type of data, that same type of data is always obtained from the particular span being searched for. For proactive solutions, if log ingestion drops suddenly or a data source stops sending logs, alerts are configured to trigger when data drops by 70 to 80 percent. Notifications are received via email or any other configured platform for alerting. ServiceNow tickets can also be created for a particular issue. This helps transition from reactive to proactive monitoring. For ingestion in Splunk Cloud Platform, the main aspect is data inputs. Infrastructure does not need to be managed as it is already managed by the Splunk teams. Data input ingestion is very easy as it has vast ingestion apps. Custom universal forwarders can also be used. Splunk has a universal forwarder product that can be installed at a particular server or application, which brings data to Splunk Cloud Platform. This universal forwarder product is a great choice for data ingestion as it gives customizable ingestion to any kind of application or server. For visualization, customized dashboards can be built, and pre-built dashboards from apps can also be used. For example, the AWS app has pre-built dashboards that can be used for monitoring AWS servers. Many applications are available.
