Platforms such as Cloudfoundry and/or Kubernetes enabled the proliferation of micro-services both in terms of development and deployment of apps/services at epic proportions. This brings several key challenges - one of them being; how to monitor all these services at scale at different layers ( to complicate it further; across multiple clouds) and collate the metrics, logs from disparate source systems then correlate them back to analyze further. Monitoring critical apps/services and alerting on issues is the key to success of any business enterprise. In this talk Dill Anupoju would like to present how to leverage some of the available open source tool stack coupled with some of the Machine Learning/NLP techniques to monitor these services at scale in the context of distributed computing environments.