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Evolution of Monitoring
Submitted by Aveek Misra (@aveekmisra) on Monday, 18 January 2016
This talk will focus on the various innovations in some of the monitoring solutions of today and how monitoring systems have evolved tremendously in the past few years. Also given the changes in application landscape today, we will talk about what are really the important things to monitor and why
Monitoring today is no longer about creating a few dashboards and alerts about the system and infrastructure metrics. Companies and organizations are more interested to look at how their business transactions are getting impacted. Also in a Mobile-First world, it has become extremely important to keep a close watch on your Mobile apps. Increasingly many of the monitoring solutions are focusing on how to do proactive monitoring and anomaly detection rather than alert after an incident has already happened. Companies are also thinking about how to use this treasure trove of monitoring data to do insightful analytics and trend analysis
In this session we will talk about some of the advancements in the monitoring landscape today. So for example how are some of the solutions doing advanced correlation of alerts using unsupervised machine learning, how can lambda architecture be used to do querying of data, what are the new time series databases that are making news, how can concepts like dynamic baselines be used for anomaly detection and so on. This talk will not be about the different monitoring tools in the market but will focus more on the innovations that are happening in the Monitoring domain and how they are relevant in today’s world.
Participants should have a very basic idea of what monitoring involves.
I have been in the Monitoring domain for the past 6 years and have worked with both open source and enterprise solutions. In my earlier organization, I was part of a development team that built a monitoring framework from scratch and that could do 1 million metric writes per second. Currently I am working as a DevOps architect in Intuit.