DataMiner Forecasting

Thomas Gunkel

DataMiner Augmented Operation. Automatic learning of the behavior and evolution of the operational system, and extending that towards the future, allowing operators to gain more in-depth insights and manage their operation more proactively.

USE CASE DETAILS

Trend display showing time series for Input Throughput on a Ciena switch, with long-term prediction by DataMiner based on autonomous learning (dashed line).

Trend display showing time series for Input Throughput on a Ciena switch, with mid-term prediction by DataMiner based on autonomous learning (dashed line).

Trend display showing time series for Total Available Memory on a HADOOP server, with long-term prediction by DataMiner based on autonomous learning (dashed line). Note the 24-hour periodicity and steady general increase forecasted.

Trend display showing time series for % Interface Utilization on a Juniper port, with mid-term prediction by DataMiner based on autonomous learning (dashed line). Note the detail on the recurring daily pattern, combined with an overall slightly lower traffic level predicted as compared to previous day.

Trend Display showing time series for CPU Idle Time on a JIRA App server, with long-term prediction by DataMiner based on autonomous learning (dashed line). Note the multiple periodicities.

Trend display showing time series for CPU Idle Time on a JIRA app server, with mid-term prediction by DataMiner based on autonomous learning (dashed line).

Trend display showing time series for memory size on a MariaDB server, with long-term prediction by DataMiner based on autonomous learning (dashed line).

Trend Display showing time series for CPU Idle Time on a JIRA App server, with mid-term prediction by DataMiner based on autonomous learning (dashed line).