Machine Learning & Monitoring
Submitted by Bhuvaneswari on Thursday, 15 March 2018
Technical level: Intermediate Status: Under evaluation
The world is moving towards machine learning. Every technical conference and blogs talk about ML & Artificial Intelligence. With my experience in monitoring team, I could see a huge gap between monitoring existing systems and machine learning. I am sure there will be audience who are facing similar challenges and would like to share our experience on bridging that gap.
To be successful, every software organization needs some type of monitoring. And in the time when everyone are moving to Cloud, any organization will have challenges like.
• Do I need to take a step ahead for moving to Cloud? • How do I migrate all my applications to Cloud? • How do I monitor them/ measure them? • When investing in Cloud and latest technologies, what will be the investment in improving monitoring in existing systems so that Customers are happy?
For sure, improving the existing monitoring systems is a MUST so that we do not lose our customers. Now comes other questions like
• How to apply latest technologies like machine learning or artificial intelligence for monitoring existing systems? • How to have a scalable and reliable solution that will be quick so that investment is less, but it should work for a long term. • What are the trade-offs that you might face in this situation.
These are the challenges as a team we took. It is my pleasure to share how we approached these problems.
I would also like to explain a sample solution where we applied latest technologies for monitoring applications.
I am Bhuvaneswari Radhakrishnan working for PayPal India Pvt Ltd, Chennai. I have close to 9yrs of experience in IT industry and 3 yrs of experience in monitoring systems. This will be my first speaker session to external audience.