Vasanth Muppalla

Identifying problems based on anomalies or deviations from normal behavior. Forecasting value of a certain metric to prevent outages or to improve operational readiness. Grouping or clustering alerts, events or logs based on symptoms or text descriptions.

In Application DB, When there is Sudden inflow of jobs from upstream, data base space is filled up and there is slowness observed in the application. Build time series models (Naive, Seasonal Naive, Holt Winters, ARIMA)to predict the growth of the DB. Scripts sends an email everyday to the team with a graphical representation which holds the current growth and the predict future growth for next 10 to 15 days. Based on the prediction sent by the script the team can take predictive measures in clearing/purging the DB (Planned Change Management) before hand and not wait till there is a critical/high incident raised by the application team.

Vehicle detection: Detect those vehicles which are moving on a road. Vehicle classification: Detect the vehicle into a particular class such as four-wheelers and two-wheelers. Classify the classes into respective category such cars, bikes. AI Ops Time Series Analysis Detect and Identify the vehicles (Computer Vision)

Telecom company needs to pay attention to the roaming rates. They need to provide good offers to the customers who are using services from a roaming zone. The company needs to focus on the STD and ISD rates. Perhaps, the rates are too high. Provide them with some kind of STD and ISD packages. To look into both of the issues stated above, it is desired that the telecom company collects customer query and complaint data and work on their services according to the needs of customers.

Contribute in the preparation of the defect management, communication and Test scope sections of the test plan. Performing requirement feasibility analysis and identified test scenarios/test objectives. Identifying end-to-end test cases, regression suites, and system test cases. Use of Jira/ ALM for test management and defect management.