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Data Processing with Microservices Using Spring Frameworks
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Data Processing with Microservices Using Spring Frameworks
1.
DATA PROCESSING WITH MICROSERVICES
2.
3.
@michaelmine lla @OffHe ap
4.
github.com/mminella/data- microservices
5.
LAY OF THE LAND
6.
SPRING FRAMEWORK
7.
SPRING INTEGRATION
8.
SPRING BATCH
9.
SPRING CLOUD STREAM
10.
SPRING CLOUD TASK
11.
SPRING CLOUD DATA FLOW
12.
WHAT ARE WE GOING TO
TALK ABOUT?
13.
DATA INTEGRATION
14.
EVOLUTI ON
15.
MONOLIT HS
16.
MULTIPLE INTEGRATION FLOWS & BATCH JOBS
17.
LARGE COMPLEX ARTIFAC TS
18.
DIFFIC ULT TO TEST
19.
HARD TO GET TO PRODUCTIO N
20.
BIG DATA PLATFOR MS
21.
GOOD WITH LARGE VOLUMES OF DATA
22.
BAD WITH SMALL VOLUMES OF DATA
23.
LARGE LEARNING CURVE
24.
LITTLE/NO REUSE BETWEEN SOLUTIONS
25.
HEAVY FOOTPRINT IN YOUR CODE
26.
HARD TO TEST
27.
HARD TO GET TO PRODUCTIO N
28.
CATEGORY CAN BE USEFUL JUST
NOT FOR EVERYTHING
29.
DATA MICROSERVI CES
30.
CLOUD NATI VE
31.
DEVELOPED AND TESTED IN ISOLATIO N
32.
INDEPENDANT LY SCALAB LE
33.
FAMILIAR DEVELOPMENT MODEL
34.
SMALL AND SIMPLE TO TEST
35.
OPERATIONALLY EASY TO GOVER N
36.
TWO MAIN PROCESSING MODELS
37.
STREA MS
38.
TAS KS
39.
DATA INTEGRATION AS A
SERVICE
40.
COMPOSTIO N OF MICROSERVI CES
41.
STREAMS AND FLOWS BECOME YOUR “APP”
42.
OPERATIONAL AND ORCHESTRATION COVERAGE
43.
SPRI NG
44.
Spring Spring Integration Spring Batch Spring Cloud Stream Spring Cloud Task
45.
SPRING CLOUD STREA M
46.
MESSAG E DRIV EN
47.
transformertime log
48.
transformertime log
49.
@EnableBinding(Source.class)
50.
@EnableBinding(Processor.class)
51.
@EnableBinding(Sink.class)
52.
53.
USE CASES
54.
DATA INGESTION 1
55.
DATA TRANSFORMATION 2
56.
REAL-TIME DATA PROCESSING 3
57.
IO T 4
58.
Demo DEM O
59.
SPRING CLOUD TAS K
60.
MICROSERVIC ES THAT END
61.
TASK REPOSITORY 1
62.
BATCH INTEGRATION 2
63.
STREAM INTEGRATION 3
64.
@EnableTask
65.
66.
USE CASES
67.
BATCH JOBS 1
68.
ONE OFF PROCESSES 2
69.
ETL PROCESSES 3
70.
DATA SCIENCE 4
71.
FINITE PROCESSING 5
72.
Demo DEM O
73.
SPRING CLOUD DATA FLOW
74.
WHAT IS SPRING CLOUD
DATA FLOW?
75.
DATA FLOW ORCHESTR ATES
76.
77.
78.
TAKES ADVANTAGE OF MODERN PLATFORMS
79.
CLOUDFOUN DRY 1
80.
KUBERNE TES 2
81.
LOC AL 3
82.
http | filter
| hdfs // DSL
83.
http | filter
| hdfs // DSL
84.
NO INSTALLED CONTAIN
85.
EVERYTHIN G IS SPRING
86.
A BOOT APP FOR THE
87.
A BOOT APP FOR THE
88.
ALL BOOT APPS FOR OTB
89.
Data Flow Server
shell app app app browser
90.
Data Flow Server
shell twitter log field-value-counter browser
91.
twitter log field-value-counter
92.
Stream Demo DEM O
93.
BUT WAIT, THERE’S MORE!
94.
TASK/STREAM/B ATCH INTEGRAT ION 1
95.
PARTITIONED STREAMS 2
96.
SCALING STREAMS & TASKS 3
97.
Learn More. Stay
Connected. Spring Cloud Data Flow Project: cloud.spring.io/spring-cloud-dataflow/ Github: github.com/spring-cloud/spring-cloud-dataflow Spring Cloud Stream Project: cloud.spring.io/spring-cloud-stream/ Github: github.com/spring-cloud/spring-cloud-stream Spring Cloud Task Project: cloud.spring.io/spring-cloud-task/ Github: github.com/spring-cloud/spring-cloud-task Pivotal: pivotal.io Twitter: twitter.com/springcentral YouTube: spring.io/video LinkedIn: spring.io/linkedin Google Plus: spring.io/gplus
98.
QUESTIO NS?
99.
Th End
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