Where and how Flowable runs in production: containers, Kubernetes, the REST application, Spring Boot starters, supported databases and the pipeline that deploys process definitions.
Standing up Flowable REST in containers from the project's Compose configurations: the PostgreSQL setup, the HAProxy load-balanced variant, default credentials to change, and moving from a demo stack to production settings.
Deploying Flowable engines on Kubernetes: container images, database connectivity and pooling, several pods sharing one database through the async executor, health probes with Spring Boot actuator, and rolling updates.
Deploying flowable-rest.war on Tomcat 10 or later: switching from H2 to MySQL or PostgreSQL, adding JDBC drivers, externalized configuration, REST app properties and authentication mode.
Picking between the all-engines starter, single-engine starters for process, CMMN or DMN, REST starters and the actuator starter, and what each choice means for footprint, tables and exposed endpoints.
Using PostgreSQL as the Flowable database: JDBC settings, schema creation, connection pool sizing for the async executor, backups, and the history tables that grow fastest.
What changes when Flowable runs on Oracle, Microsoft SQL Server or DB2: supported drivers, empty string tenant handling on Oracle, SQL Server nvarchar indexing improvements, and DB2 bulk insert exceptions.
Creating and upgrading Flowable tables when developers cannot run DDL in production: the create, drop and upgrade scripts per database, engine and history table sets, and turning off automatic schema updates.
Getting BPMN, CMMN and DMN models from Git into production Flowable engines: business archives, auto-deployment in Spring Boot, versioning on each deploy, Java classes on the classpath, and rollback options.
Checking Flowable Docker images before they run: cosign signatures from version 6.7.3, the published public key, pinning image versions, and fitting verification into an admission or CI policy.
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