http://predixtransform.com Data Services are building blocks used towards enabling outcomes in analytics. In this session, we will talk about data services with the help of a practical use case. Users will be able to understand how to integrate elements of data services to help enable deep insights from machine behavior data to drive operational efficiencies.

1. E2: Predix Data Services
Sanjeev Sayeeraman
Krishna Yelisetti

2. 2PREDIX TRANSFORM
Data Services - what do they do?
Enable
Deep Insights
from
Machine Behavior Data
To Drive
Operational
Efficiencies

3. 3PREDIX TRANSFORM
What Predix Data Services does?
Meet SaaS & SaaS Data Ingestion Data & Model Catalogs
Software as a Service,
Services as a Solution
Time Series, Control
Inputs, Work Orders,
Incidents
Standardized Data Sets
for Geo, Weather,
Demographic, etc. etc.

4. 4PREDIX TRANSFORM
Data Services – Main types
Time Series Blobs Relational
Data00110
10010
11001
01010

5. 5PREDIX TRANSFORM
TIME SERIES

6. 6PREDIX TRANSFORM
Time series | Architecture(what)
1 Time-Series
Query Service
Data ingestion pipeline
and data store
Cloud gateway and
distributed messaging
2 3
SITEASITEBSITEC
Sensor Controller
S2C Collector
OSM
Historian
2
Device Predix Machine
1
4
1
Device
5
2
Device
6
3
Device
Web Portals Dashboards &
Reports
Trends &
Charts
Mobile
Field/Operations
Engineers
Time Series Query API
Interactive sub-
second queries
Time Series
Query Service
Low latency
Columnar Store
Data Ingestion
Pipeline
Distributed
Messaging Layer
Time Series
Cloud
Gateway
S2C
(Websocket)
S2C
(Websocket)
S2C
(Websocket)

7. 7PREDIX TRANSFORM
Use Cases
Statistical analysis,
Machine Learning
Correlate anomalous
Time Series data with
test runs
Monitoring &
Diagnostics: Engineering
Analysis:
Root Cause Analysis
for anomalies
Anomaly detection
using Time Series
modeling
1000s of turbines
Optimal operation of Power
Generation Systems

8. 8PREDIX TRANSFORM
Operation
Efficiencies
Use Cases
X-Axis is
always Time
Forecasting Capacity
Planning
Anomaly
Detection
Machine
Learning
Model Creation
Intelligent (and
dumb) Alerting
Automated
RCA
Advanced
Correlations

9. 9PREDIX TRANSFORM
Using Time-Series -5 Simple Steps
Create Time
Series
instance in
Cloud Foundry
& include Time
Series client in
your project
Download
Time-Series
Client Library
From Predix.io
Configure
Library
Build your
Ingestion
Request
Build your
Query Request

10. 11PREDIX TRANSFORM
Using Time-Series – Step 4
IngestionRequestBuilder ingestionBuilder =
IngestionRequestBuilder.createIngestionRequest()
. withMessageID(MESSAGEID),
. addIngestionTag(INGESTION_TAG
.addDatapointlist (
(Time1, SensorValue1,QUALITY1).
(Time2, SensorValue2,QUALITY2),
(Time3, SensorValue3,QUALITY3)));
String json = ingestionBuilder.build().get(0);
IngestionResponse response =
ClientFactory.ingestionClientForTenant(ingestionTenant).ingest(json);
Build your
Ingestion
Request

11. 12PREDIX TRANSFORM
Using Time-Series – Step 5
QueryBuilder builder = QueryBuilder.createQuery()
. START_TIME
.ENDTIME
.addTags(QueryTag.Builder.createQueryTag()
.withTagNames(Arrays.asList("ALT_SENSOR",
"TEMP_SENSOR"))
QueryResponse response = ClientFactory.queryClientForTenant(tenant)
.query All(builder.build());
Build your
Query
Request

12. 13PREDIX TRANSFORM
LET’S TALK ABOUT BLOB
STORE

13. 14PREDIX TRANSFORM
Scalability
Challenges to manage BLOB data
Durability
Security Cost
High-Availability

14. 15PREDIX TRANSFORM
Predix Blobstore – what do we provide?
Provides a Web
Service interface
(REST)
Allows unlimited
storage of
objects(files)
Objects consists
of the raw object
data and
metadata
S3 API
compatibility
Scalable storage Reliable storage Multi tenancy
support
Secured access

15. 16PREDIX TRANSFORM
Use case – GE HealthCloud
Web app
and ZFP
viewer
• Reads 3000 images of
each 512kb size
• Generates 2D/3D views
• Clinicians receive notifications
• View or CD upload
• Specialists receive
notifications
CLINICIAN REMOTE
ACCESS, ANY DEVICE
SPECIALTY HOSPITAL B
COMMUNITY HOSPITAL A
Predix
Machine
X-Ray MR Ultrasound PathologyCell Analysis CT
User identity
Org Management
2D/3D Visualization
DICOM case
Security
Blobstore
Predix Cloud
• Create a case contains
up to 3000 files of each
size 512kb and uploads
to cloud
Predix Machine

16. 17PREDIX TRANSFORM
Plant/Factory
Predix
Machine
Machines
Blobstore
Timeseries
Asset
Postgres
Business
Apps
Analytics
Dashboards
Secured Network
Write
Read Write
Read
Read
Business
Apps
Legacy Systems
Use case – Oil & Gas
Predix Cloud
Bringing data from legacy systems at plant to cloud
Data Types
Images Acoustic
Data
Asset Timeseries Waveform Alarms
$

17. 18PREDIX TRANSFORM
Using Blobstore
Create Blobstore Instance
cf create-service predix-blobstore
Tiered <service-instance-name>
Bind to an APP
cf bind-service <business-app>
<service-instance-name>

18. 19PREDIX TRANSFORM
UsingBlobstore
VCAP_SERVICES
VCAP_SERVICES": {
"predix-blobstore": [
{
"credentials": {
"access_key_id": "421b19-98c7-440c-98f5-d042fe4",
"bucket_name": "bucket-421b2e-98c7-440c-98f5-d042fe4f",
"host": "storeenc.gecis.io",
"secret_access_key": "d90ea6f4-4a7c-b71a-28a0e8d25d3",
"url": "https://bucket-421b2e-98c7-440c-98f5-d042fe4f.store.gecis.io"
},
"label": "predix-blobstore",
"name": "blob-test-ins",
"plan": "Tiered",
}

19. 20PREDIX TRANSFORM
UsingBlobstore
Read Credentials
Import (“github.com/cloudfoundry-community/go-cfenv”)
appEnv, err := cfenv.Current()
for _, v := range appEnv.Services {
for _, service := range v {
if service.Name == blobstoreServiceInstanceName {
blobstoreAccessKeyID = service.Credentials[accessKeyID].(string)
blobstoreSecretAccessKey = service.Credentials[secretAccessKey].(string)
blobstoreHost = service.Credentials[host].(string)
blobstoreBucketName = service.Credentials[bucketName].(string)
}
}
}

20. 21PREDIX TRANSFORM
UsingBlobstore
Create Session & Handler
Import (“github.com/aws/aws-sdk-go/service/s3”)
awsConfig := aws.Config{
Credentials: credentials.NewStaticCredentials(accessKeyID, secretAccessKey, ""),
Endpoint: &endpoint,
LogLevel: &logLevel,
}
s := session.New(&awsConfig)
svc := s3.New(s)
svc.Handlers.Sign.PushBack(SignV2)
s3Hndler := &S3Handler{
s: s,
svc: svc,
bucketName: bucketName,
}

21. 22PREDIX TRANSFORM
UsingBlobstore
Upload File
uploader := s3manager.NewUploader(s.s)
svc := uploader.S3.(*s3.S3
svc.Handlers.Sign.Clear()
svc.Handlers.Sign.PushBack(SignV2)
result, err := uploader.Upload(&s3manager.UploadInput{
Body: file,
Bucket: &s.bucketName,
Key: &fileName,
})

22. 23PREDIX TRANSFORM
UsingBlobstore
Get & Delete File
input := &s3.GetObjectInput{
Bucket: &s.bucketName,
Key: &fileName,
}
resp, err := s.svc.GetObject(input)
params := &s3.DeleteObjectInput{
Bucket: &s.bucketName,
Key: &fileName,
}
_, err := s.svc.DeleteObject(params)

23. 24PREDIX TRANSFORM
UsingBlobstore
Samples
• Go sample using aws-sdk-go
• Java sample using AWS S3 Client SDK
• Java sample using Apache Jclouds SDK
https://github.com/PredixDev/blobstore-samples

24. 25PREDIX TRANSFORM
DEMO

25. 26PREDIX TRANSFORM
Demo Architecture
Predix Cloud
Raspberry Pi
Blobstore
Timeseries
Browser
Data Types
Images Acoustic
Data
Timeseries Waveform
Authentication Dashboard
App
BlobstoreApp

26. 27PREDIX TRANSFORM
Q & A

27. 28PREDIX TRANSFORM
How does this help you?
We Deliver
Foundational capabilities
All the data in one place
Create Magic
You
With

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representation, warranty or documentation regarding the product or service featured. Illustrations are provided for informational purposes, and your configuration may differ. This information does not
constitute legal, financial, coding, or regulatory advice in connection with your use of the product or service. Please consult your professional advisors for any such advice. GE, Predix and the GE Monogram are
trademarks of General Electric Company. ©2016 General Electric Company – All rights reserved.