ShenCe Introduction
Dec. 2016
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ShenCe Introduction
Web R&D’s New Plays
Big Data R&D’s New Plays
General Introduction
l Job Scheduling: GUI, cluster based, dynamic, distributed, relible job mgmt & scheduling service
l Intrusion Detection: User account & data protection; Account platform protection, 3 levels
l Real-time Monitor:Access count, success rate, performance of any Nginx based service , 3 levels
Data Collect
Login
Data
Distributed
Scripts
Web Server
Log
Data Analysis
Job Dispatch
Real-time Act
Intrusion
Detection
Job
Scheduling
Real-time
Monitor
GUI
ShenCe Web
Automatic and Intelligent Platform
p Main Advantages
ü Good commonality (Nginx, Apache, …)
ü No any influence to online service
ü Good real-time (Not more than 5 seconds)
ü 3 levels monitor (Cluster -> URL -> IP)
p Current Status
ü Has been deployed in production environment
ü Scheduling jobs in 3 machine rooms
ü Real-time detect, notify to intercept IP & protect
data
Resources & Progress
Total Human Resources:
R&D: 17 in all, 8 interns, 2 formal employees, 7 part time employees
Operations: 3 employees, part time
Jul.
Aug. ~ Sep.
Oct. ~ Nov.
Dec.
l Evaluation,
planning from
middle July
l 6 interns on July 20
l 2 interns and I
started developing
job scheduling part
on July 23
l Finish job related
R&D
l Deployed in cloud,
schedule job in
two MRs
l Begin focus on
spark related parts
in Sep.
l 7 people joined in
Sep., 1 internal
l Set up R&D ENV with
CLI + Maven
l Finish spark related
R&D and optimization
l Deployed in cloud &
physical machine ENV
l Connect to other
services in cloud ENV
l 1 of 3 people 100%
joined on Oct. 27
l Break through
limitations of CN2
in proxy
l Connect with other
Dec. 21
services in
PHYSICAL ENV
l Requirements
adjusting & adding
l 1 intern joined on
3 Spark Apps
Total Memory: 80Gb~120Gb
NginxLogAnalyzer
PopLoginAnalyzer
WebLoginAnalyzer
2 Web Apps
Intelligent tip & no SQL like* query
Job Mgmt, Scheduling, Execution Monitor
Real-time Intrusion Detection 1
Make Intrusion Intuitionistic