Log files usually come in variety of formats. These log formats are neither documented nor standardize. Moreover, there are no guidelines available on how to log. Some of them are interpretable while others are way more complicated to interpret.
Moreover, due to the ease of generating log files either from applications or machines like sensors log files grow very quickly. Thus, it becomes near impossible to expect humans to interpret those logs and find valuable insights from them.
For example, some of the log files report IP address while some log files report fully qualified domain name. How do you correlate them? Let’s say you want to map it to the hostname. So, you look up at DNS look up at that point and it will take a lot of time to get the result back. Moreover, if you have real-time streams coming in then you may have to face ever a big problem. Usually, you need to process logged data that is either semi structured or unstructured and correlate with another data that might be coming from absolutely different source.
In order to monitor log files you should be able to set different cues or dimensions that makes sense to analyze them. Looking for patterns in your log files is like finding needles in the hay stack.
At Brevitaz, we develop custom log analyzer that can consolidate and index your logs from either semi structured or unstructured form that may be from variety of sources.
We can develop custom log analytic tools having following features
- scale out as you need
- Monitor logs proactively with alerting.
- Real-time search and reporting through dash boarding based on multidimensional statistics and correlated event data.
- Deployable across hybrid IT environment
- Drill-down capabilities