Let’s face it - we are not all working for a company like Facebook, Netflix or LinkedIn where we need to process terabytes of data each day. Often we just need to solve some complex business processes with a moderate amount of data. Or we need to generate some documents based on input given by another microservice without blocking the http request.
Using JobRunr, you can transform any Java 8 lambda and turn it into a distributed background job: the lambda is analysed together with the arguments and saved as a job to a SQL or noSQL database. Next, different BackgroundJobServer beans (in different JVM instances) inside your application fetch these jobs and process them. By scaling up the instances of your application (e.g. in Kubernetes), your jobs will get processed faster.
As of JobRunr 5.0, it also supports Spring Native - scaling up can now happen in milliseconds and processing will go faster than ever!