System anomalies such as network interruptions, operating system halt, disk crash could result in significant financial losses to organizations. In this demonstration we describe a novel log event analysis framework called Solution Recommender which provides a ranked list of solutions to overcome such system errors. The solution recommender gathers log events via a publisher/subscriber mechanism and indexes them inside the WSO2 Data Analytics Server (DAS). Collected information is analyzed using a knowledge graph which conducts log event pattern matching to identify solutions for system failures. We have implemented the proposed approach on WSO2 Log Analyzer for WSO2 API Manager and tested its functionality. In this paper we describe our experience of implementing the log event recommender interface, the first such recommender developed in a log event analyzer system. The insights presented here will assist practitioners with implementing such Log Event analysis solutions for real world scenarios.