Hi,
I am in need of an infrastructure set up for data analytics / live video stream analytics application using big data and analytics technology..
The data is basically right now stored as structured data(no video streaming) in PostgresDatabase. ( Its an emergency call handling solution, In database which stores, caller info (address, mobile number, locations co-ordinates, emergency category metadata and dispatch information regarding rescue vehicles., Rescue vehicle location update (lat, long)every 30 seconds all are stored in the Postgres Database ..
Input1 : I have to do an analytics on these data( say 600 GB for the last 2 years its the size grown from initial setup).To perform an analytical application development( using python and data analytics libraries, and displaying the results and analytical predication through a dashboard application.)
Query 1. How much resource in terms of compute(GPU?(CPU) cores required for this analytical application? and memory ? And any specific type of storage(in memory like redis required ? ) etc, which I have to provision for these kind of application processing. ?? any hints most welcome.. Any more input required let me know I can provide if available.
Input 2
In addition to the above I have to do video analytics from bodyworn cameras by police personnel, drone surveillance
Videos from any emergency sites, patrol vehicle (from a mobile tablet device over 5G )live streaming of indent locations for few minutes ( say 3 to 5 minutes live streaming for each incident. ) There are 50 drones, 500 Emergency rescue service vehicles, 300 body worn camera personnels.. and roughly 5000 incidents / emergency incidents per day happening, which needs video streaming for at least 1000 incidents for a time duration of 4 to 5 minutes live streaming.
Query2. What/(how many) kind of computing resources GPUs(CPUs)? RAM, Storage solutions I have to deploy in numbers( or cores of GPUs/how many/(CPUs)? RAM ? In Memory (Redis or similar ) or any other specific data storage mechanisms ? Any hints much appreciated..
Best,
Krishane