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Structured Log Data as Base for KPI Monitoring

Within industrial applications key performance indicators (KPI) play an essential role to assess the effectiveness of a machine or plant and to detect performance reductions and malfunctions immedieately.

Complex systems generate lots of log data, where it is not easy to still see the full picture of the system. A centralized data sink improves within this situation.

Seq from datalust.com is a data bank based log system for structured log data. The platform provides numerous of libraries and plugins for modern log APIs for several programming languages and interfaces (e.g. for Serilog, Microsoft.Extensions.Logging, Java, Python and HTTP) and builds a centralized data sink for a complex landscape of applications and microservices.


  • Increased plant effectiveness (OEE) due to optimizations based on the available data base
  • Fast localization of malfunctions and performance deviations in complex landscapes of applications and microservices
  • Web based user interface
  • Slack, Teams, mail and further notification services to detect deviations due to predefined conditions
  • Flexible and simple configuration of additional queries and diagrams by the operator
  • Data retention handled by Seq
  • Data export for report creation

Structured log data is the base to visualize key performance indicators. Seq prepares structured log data into customized diagrams, such as pie, timeline or bar charts and provides live updates if configured.

Seq: Timeline chart of produced items per exit

Structured Log Data

The base of efficient generation of diagrams and reports is provided by structured log data. The following example log extract shows the data fields of a structured log entry:

Extract of a structured log entry in Seq

The key word query filters the structured log data. The following example below shows a query filtered by InvokeId = 28317742. This view allows reducing the log entries to the relevant data and assists in following single flows throughout a complex landscape of several applications and services. Presupposed the structured log entries contain the key word InvokeId with its corresponding value.

Filtering on key words shows all log entries corrensponding with the specified InvokeId.

Data Retention

In data bank based systems increasing data records lead in slow queries and views if data retention is not handled properly. Seq is equiped with automatic data cleaning mechanisms. Data retention policies allow to set individual data storage periods due to its log severities. For instance, detailed log entries on debug level are storable throughout a shorter period to provide a deeper view in trouble shooting situations. Wheras log data on info level (e. g. to log serial numbers of produced items) is storable over a longer period to allow visualizations of monthly or yearly reports.

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Sofel supports you in optimizing overall equipment effectiveness (OEE) with statistic analysis and visualized key performance indicators.

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