Oct 11, 2016
Efficient bundling of similar activities – Batch Processing with Camunda
Batch Processing in business processes is the ability to execute an activity or a set of activities for several business cases simultaneously. In practice, we can observe different cases where the bundled execution of several cases is beneficial and can improve process performance. In healthcare, it is more time-efficient to first collect a set of blood samples taken from patients to deliver them to the laboratory instead of sending a nurse for each separately. In e-commerce and logistics, it is more cost-efficient to consolidate packages to be sent to the same customer instead of handling each separately. In administration, usually related sets of invoices are approved to minimize the time to get familiar with the work. Most process modeling languages…
By Luise Pufahl
Sep 28, 2016
Camunda Modeler 1.3.2 released
We are happy to announce version 1.3.2 of the Camunda Modeler! Please download the new version from camunda.org. We fixed some bugs with the patch releases 1.3.1 and 1.3.2.
By Patrick Dehn
Sep 26, 2016
Recommending CMMN Activities
The Case Management Model and Notation (CMMN) standard deals with unstructured work that is performed in the context of a so-called case. A CMMN model specifies the frame in which a case is handled. It expresses design time considerations, such as hard restrictions when an activity can be performed or not. Aside from that, there are often soft patterns that only emerge at runtime based on case workers’ experience. Detecting such patterns and providing insights to case workers can make dedicated case management with CMMN and Camunda especially useful.
Sep 23, 2016
Camunda BPM 7.6.0-alpha4 Released
Camunda 7.6.0-alpha4 is here and it is packed with new features. The highlights are: Batch Cancellation of Process Instances CMMN Monitoring in Cockpit New Home Page for the Webapplication Improved Metrics API 25 Bug Fixes The complete release notes are available in Jira. You can Download Camunda For Free or Run it with Docker.
Sep 19, 2016
BPMN and DMN-Modeler for Confluence
You are using Confluence? We as community members developed two plugins which allows you to use bpmn-js/dmn-js as full-featured modeling tool within your wiki for BPMN/DMN. Both are available on the on the Atlassian marketplace for free.
Sep 9, 2016
Camunda Modeler 1.3 released
We are happy to announce version 1.3 of the Camunda Modeler! This release comes with a new mode for DMN, morphing Expanded Sub Processes into Collapsed ones (and vice-versa) in BPMN, a new context menu for tabs. Download the new version from camunda.org.
Aug 18, 2016
KPI Monitoring with Camunda
Key performance indicators (KPIs) are the most important metric for analyzing statistical data of business processes: KPIs can not only be used to highlight efficiencies and inefficiencies in business processes, but they can help to subsequently improve specific activities in order to speed up process execution. Choosing the right KPIs and displaying the data in a simple and intuitive way is key for process improvement. One of the most common requirements for KPI monitoring is about time-sensitive business processes. The question that you might ask is ‘How can we monitor which business processes or specific steps were completed in time and which did not?’ Within this blog entry I will outline how one can make use of Camunda’s open architecture…
Aug 11, 2016
Camunda BPM 7.6.0-alpha3 Released
Camunda 7.6.0-alpha3 is here and it is packed with new features. The highlights are: Reporting for Tasks Support for Decisions with Literal Expressions CMMN Engine Improvements Rolling Upgrades 23 Bug Fixes The complete release notes are available in Jira. You can Download Camunda For Free or Run it with Docker.
Aug 8, 2016
Improving the Performance of the Camunda DMN Engine
8 Months ago, we created a benchmark for the DMN engine and measured the number of decision tables the engine can evaluate per second. Now, we had a second look at it to find a way to make the DMN engine even faster. In our benchmarks we see improvements in throughput of up to 6x.


