building analytic apps for saas: “analytics as a service”

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Building Analytic Apps for SaaS: “Analytics as a Service”

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Page 1: Building Analytic Apps for SaaS: “Analytics as a Service”

Building Analytic Apps for SaaS: “Analytics as a Service”

Page 2: Building Analytic Apps for SaaS: “Analytics as a Service”

Today’s Presenters

David Potes, Partner Solutions Architect, Big Data, AWSMariano Luna, Sr. Manager, Technical Alliances & Cloud, TIBCO SoftwarePatrick Brown, VP of Digital Marketing, WaggleRaj Chary, VP Technology/Architecture, Waggle

Page 3: Building Analytic Apps for SaaS: “Analytics as a Service”

Relational data warehouse

Massively parallel; petabyte scale

Fully managed

HDD and SSD platforms

$1,000/TB/year; starts at $0.25/hour

Amazon Redshift

a lot fastera lot simplera lot cheaper

Page 4: Building Analytic Apps for SaaS: “Analytics as a Service”

The Amazon Redshift view of data warehousing

10x cheaper

Easy to provision

Higher DBA productivity

10x faster

No programming

Easily leverage BI tools, Hadoop, machine learning, streaming

Analysis inline with process flows

Pay as you go, grow as you need

Managed availability and disaster recovery

Enterprise Big data SaaS

Page 5: Building Analytic Apps for SaaS: “Analytics as a Service”

Amazon Redshift architecture Leader node

Simple SQL endpointStores metadataOptimizes query planCoordinates query execution

Compute nodesLocal columnar storageParallel/distributed execution of all queries, loads, backups, restores, resizes

Start at just $0.25/hour, grow to 2 PB (compressed)DC1: SSD; scale from 160 GB to 326 TBDS2: HDD; scale from 2 TB to 2 PB

SQL clients/BI tools

128GB RAM

16TB disk

16 cores

Ingestion/backupBackupRestoreAmazon S3/Amazon

DynamoDB/Secure Shell (SSH)

JDBC/ODBC

10 GigE(HPC)

128GB RAM

16TB disk

16 coresCompute node

128GB RAM

16TB disk

16 coresCompute node

128GB RAM

16TB disk

16 coresCompute node

Leadernode

Page 6: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #1: Amazon Redshift is fast Dramatically less I/O

Column storage

Data compression

Zone maps

Direct-attached storage

Large data block sizes

analyze compression listing;

Table | Column | Encoding ---------+----------------+---------- listing | listid | delta listing | sellerid | delta32k listing | eventid | delta32k listing | dateid | bytedict listing | numtickets | bytedict listing | priceperticket | delta32k listing | totalprice | mostly32 listing | listtime | raw

10 | 13 | 14 | 26 |…

… | 100 | 245 | 324

375 | 393 | 417…

… 512 | 549 | 623

637 | 712 | 809 …

… | 834 | 921 | 959

10

324

375

623

637

959

Page 7: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #1: Amazon Redshift is fastParallel and distributed

Query

Load

Export

Backup

Restore

Resize

S3/EMR/DynamoDB/SSH

128GB RAM

16TB disk

16 coresCompute node

128GB RAM

16TB disk

16 coresCompute node

128GB RAM

16TB disk

16 coresCompute node

SQL clients/BI tools

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 coresLeadernode

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 cores

CN

128GB RAM

48TB disk

16 coresLeadernode

Page 8: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #1: Amazon Redshift is fast

Hardware optimized for I/O intensive workloads, 4 GB/sec/node

Enhanced networking, over 1 million packets/sec/node

Choice of storage type, instance size

Regular cadence of autopatched improvements

Page 9: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #2: Amazon Redshift is inexpensive

Ds2 (HDD) Price per hour for DW1.XL single node

Effective annual price per TB compressed

On demand $ 0.850 $ 3,7251-year reservation $ 0.500 $ 2,1903-year reservation $ 0.228 $ 999

Dc1 (SSD) Price per hour for DW2.L single node

Effective annual price per TB compressed

On demand $ 0.250 $ 13,6901-year reservation $ 0.161 $ 8,7953-year reservation $ 0.100 $ 5,500

Pricing is simpleNumber of nodes x price/hourNo charge for leader node No upfront costsPay as you go

Page 10: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #3: Amazon Redshift is fully managed

Continuous/incremental backups

Multiple copies within cluster

Continuous and incremental backups to Amazon S3

Continuous and incremental backups across regions

Streaming restore

Amazon S3

Amazon S3

Region 1

Region 2

Compute node

Compute node

Compute node

Page 11: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #4: Security is built in• Load encrypted from Amazon S3

• SSL to secure data in transit

• ECDHE perfect forward security

• Amazon VPC for network isolation

• Encryption to secure data at rest

– All blocks on disks and in Amazon S3 encrypted– Block key, cluster key, master key (AES-256)– On-premises HSM and AWS CloudHSM support

• Audit logging and AWS CloudTrail integration

• SOC 1/2/3, PCI-DSS, FedRAMP, BAA

10 GigE(HPC)

IngestionBackupRestore

SQL clients/BI tools

128GB RAM

16TB disk

16 cores

128GB RAM

16TB disk

16 cores

128GB RAM

16TB disk

16 cores

128GB RAM

16TB disk

16 cores

S3/EMR/DynamoDB/SSH

Customer VPC

InternalVPC

JDBC/ODBC

Leadernode

Compute node

Compute node

Compute node

Page 12: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #5: We innovate quickly Well over 125 new features added since launch Release every two weeks Automatic patching

-50

-80

100

40

-30

15

30

90

80

Page 13: Building Analytic Apps for SaaS: “Analytics as a Service”

Benefit #6: Amazon Redshift is powerful• Approximate functions

• User-defined functions

• Machine learning

• Data science

Page 14: Building Analytic Apps for SaaS: “Analytics as a Service”

Mariano Luna

January 12th, 2017

Building Analytic Apps for SaaS: “Analytics as a Service”

Page 15: Building Analytic Apps for SaaS: “Analytics as a Service”

Hello, it’s me

Mariano Luna

Sr. Manager, Technical Alliances & Cloud

TIBCO Software (Houston, TX)

Page 16: Building Analytic Apps for SaaS: “Analytics as a Service”

Do you feel like your users are always looking for more?

Page 17: Building Analytic Apps for SaaS: “Analytics as a Service”

The Rise of Modern ApplicationsThe Old Way Modern Applications

Page 18: Building Analytic Apps for SaaS: “Analytics as a Service”

The Rise of Modern Applications

Your app

Analytics

Knowledge

worker

The Old Way Modern Applications

Page 19: Building Analytic Apps for SaaS: “Analytics as a Service”

The Rise of Modern Applications

Your app

Analytics

Put answers in context

Increase adoption of BI

Give consumersactionable data

Embedded Analytics

Knowledge

worker

The Old Way Modern Applications

Page 20: Building Analytic Apps for SaaS: “Analytics as a Service”

Jaspersoft OverviewAn embeddable analytics platform designed for software companies

Page 21: Building Analytic Apps for SaaS: “Analytics as a Service”

Jaspersoft OverviewAn embeddable analytics platform designed for software companies

Jaspersoft Studio

Desktop report designer for JasperReports

JasperReports Server

Powerful BI platform and server

Reports Dashboards Self-service

Jaspersoft ETL

Data integration for improved reporting & analysis

JasperReports

World’s most popular Java reporting library

Page 22: Building Analytic Apps for SaaS: “Analytics as a Service”

From Data to Delivery

Connect to & manage your platform

Server

Connect toyour data

Data Tier

Inside any appor process

DeliveryYour app

Output

Create beautiful reports & dashboards

Page 23: Building Analytic Apps for SaaS: “Analytics as a Service”

Why Jaspersoft for AWS

OOTB multi-tenant

support

Built to 100% modern web

standards

RESTful web service APIs

Visualize.js for advanced

embeddingJavaScript/ HTML5 UI

10 minutes

to deploy

Autodetect for:• RDS• Redshift• EMR

Starts at less

than $1/hour

Pay-as-you-go withno user or data limits

Save with discountedannual subscriptions

Autoscaling

clusters

Infinite elastic scalability

Multi-AZ enterprise

deployments

Page 24: Building Analytic Apps for SaaS: “Analytics as a Service”

Patrick Brown - Vice President of MarketingRaj Chary - Vice President of Technology/Architecture

Page 25: Building Analytic Apps for SaaS: “Analytics as a Service”

Smart, responsive practice

Math and ELA (Grades 2-8)

Provides students the right challenge at the right time

What is Waggle?

Page 26: Building Analytic Apps for SaaS: “Analytics as a Service”

Right Challenge, Right Time Waggle looks for more than correct answers. Waggle continually analyzes each student’s decisions and progress. That way, students get tougher material right when they’re ready.

What is Waggle?

Page 27: Building Analytic Apps for SaaS: “Analytics as a Service”

Productive Struggle Waggle motivates students to push themselves forward. How? Through helpful hints, supportive feedback, and achievement badges that build grit and confidence.

What is Waggle?

Page 28: Building Analytic Apps for SaaS: “Analytics as a Service”

Constructive Grouping Waggle’s insights means you can easily group students together based on learning needs. All without sacrificing the quality of individual instruction.

What is Waggle?

Page 29: Building Analytic Apps for SaaS: “Analytics as a Service”

Waggle: Product Demo• Data Creators

Differentiated learning experience Fun and engaging

• Data Visualizers Seamless integration with application Analytics with a Story Actionable Data

With integration deep dives into TIBCO Jaspersoft (Visualize.js) and AWS services (Redshift)

Page 30: Building Analytic Apps for SaaS: “Analytics as a Service”

How did we build Waggle?

Page 31: Building Analytic Apps for SaaS: “Analytics as a Service”

How did we build Waggle?• Data Modelling

Lens-based model (distribution keys and sort keys)

Ask and validate Performance Efficiency

(compression, load/unload, vacuum/analyze, in-memory processing, WLM)

Page 32: Building Analytic Apps for SaaS: “Analytics as a Service”

How did we build Waggle?• Data Modelling

Lens-based model (distribution keys and sort keys)

Ask and validate Performance Efficiency

(compression, load/unload, vacuum/analyze, in-memory processing, WLM)

• Contextual Design Prototype and

storyboard Capture the “Intent”

Page 33: Building Analytic Apps for SaaS: “Analytics as a Service”

Amazon Redshift: Data Warehouse Layout

Write ClusterCompute – dw2.large

Redshift

Read ClusterCompute – dw2.large

Redshift

History ClusterDensity – dw1.xlarge

Redshift

Initial and Incremental {processed} data loads

Periodic Data Snapshots for historical analysis

Data sources

For serving Jaspersoft reports

APIs

OLTP

S3 COPY

S3 UnLoad and Load

S3 UnLoad and Load

Data mart(aggregations)

NodesNodes

Staging

Datamart(aggregations)

NodesS3 UnLoad and Load

S3 UnLoad and Load + UPSERTS

Page 34: Building Analytic Apps for SaaS: “Analytics as a Service”

Results and Lessons Learned• Performance Metrics

– Millions of records are processed in <1 minute• LOAD/UNLOAD commands | UPSERTS | S3 COPY

Command – Report queries average < 1 to ~1.5 seconds– {compression} – gained 20+% efficiencies in data retrieval

• Best Practices– {sort keys} – lens-based data model: visualize data in variety of ways – {commit stats} – Redshift is not a transactional system– {nested loops} – no Cartesian products, ensure joins well managed– {queries that queue} – tune the WLM configuration– {query runtimes} – faster query means less queuing– {stats missing} – analyze and vacuum when possible– {alerts with tables} – monitor to ensure queries running optimally

Page 35: Building Analytic Apps for SaaS: “Analytics as a Service”
Page 36: Building Analytic Apps for SaaS: “Analytics as a Service”

Find TIBCO Jaspersoft on AWS Marketplace

Page 37: Building Analytic Apps for SaaS: “Analytics as a Service”

Q & A