In telecommunications, fault management is critical to improve network availability and user experience. To enhance reliability of their networks, operators require tools to quickly understand the cause of an outage. In particular, logs of alarms keep track of failures arising in their infrastructures. Due to the increasing size of networks and to the high diversity of technologies, these files may be verbose and noisy. That is why analyzing a log is often complex, hence delaying recovery and then degrading network availability. This demo presents a tool suite dedicated to log analysis. Our methodology is illustrated through the processing of a real alarm log issued from a 4G network. First, one can simplify the log by discarding irrelevant alarms and by clustering co-occurrent ones. Then, the underlying graph structure, called DIG-DAG, can store causal patterns by processing the input log online. Hence, experts can query the DIG-DAG to retrieve small and interpretable patterns.