accelerating grc by power of cloud...accelerating grc by power of cloud vidya phalke eric z beard...

Accelerating GRC by Power of CloudVidya Phalke Eric Z BeardMetricStream AWS

Vidya Phalke

© 2018 GRC Summit All Rights Reserved.

GRC Cloud – A modern Software as a Service Approach

GRC Cloud

Full data & stack segregation to ensure zero data-co-mingling

Provisioning of bespoke value added services, e.g., Tableau

Rapid deployment & dynamic scaling of GRC environment

Granular app & instance level security as per regulatory and customer specific standards

Enable customer specific audit, data migration and data segregation capabilities

Manage sector specific cloud data regulatory standards such

as HIPAA, PCI, FedRAMP


The GRC Journey - What GRC Cloud Delivers

GRCCLOUD

MANAGEABILITY FLEXIBILITY

SCALABILITY AGILITY

RISK MANAGEMENT

AUDIT

MAN

AGEMEN

TCOM

PLIA

NCE

MAN

AGEM

ENT

POLICYMANAGEMENT

PROVISIONING

APP DEPLOYMENT

CHANGE MANAGEMENT

ADVANCED CLOUD SERVICES

END TO END MANAGEMENT

INCREASE BUSINESS OPITM

IZATION

1

2

3

4


Provisioning and App Deployment

Faster Configuration

Increased Productivity

Application Isolation

Security Management

Auto-scalability

Load Balancing

DNS Management

Resource Monitoring


Change Management – Full Spectrum of Options

Landing Pages

Reports

Charts

Forms

Workflows

Emails

Roles

Branding

PERSONALIZE CONFIGURE EXTEND CUSTOMIZE

UserProfile End User Business Admin. IT IT

UpgradeSafe Yes Yes Yes No

Code/No-Code No Code No Code Code Both


Advanced Cloud Services – Cloud Business Intelligence


Advanced AWS Cloud Services – Available today

Virtual Private Cloud (VPC)

Hardware Security Module (HSM)

S3 Containers

GRC CLOUD

AWS Services


Enhance GRC Cloud with Added AWS Services

GRC CLOUD

Additional AWS Services

ANALYTICS DEV OPS CORE SERVICES

SECURITY & COMPLIANCE INFRASTRUCTURE

Elastic Research

ETL One-click App Deployment

Application Lifecycle

management

Compute Storage CDNNetworking

StorageKey Management &

StorageRegions Availability

ZonePoints of Presence

Eric Beard

© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

Amazon Redshift

Fast

Delivers fast results for all types

of workloads

Simple

Create and start using a data

warehouse in minutes

Cost-effective

No upfront costs, start small, and

pay as you go

Scalable

Gigabytes to petabytes

to exabytes

Integrated

Integrated with S3 data lakes,

AWS services and third-party tools

Secure

Audit everything; encrypt data

end-to-end; extensive certification and compliance

10x Faster at 1/10th the Cost


Data Lakes

Data Warehouse

Business Intelligence

OLTP ERP CRM LOB

• Relational and non-relational data

• TBs–EBs scale

• Diverse analytical engines

• Low-cost storage & analytics

Devices Web Sensors Social

Data Lake

Big Data processing, real-time, Machine Learning


Data Lakes on AWS

Analytics

• Unmatched durability, and availability at EB scale

• Best security, compliance, and audit capabilities• Object-level controls for fine-grain access

• Fastest performance by retrieving subsets of data

• The most ways to bring data in

• 2x as many integrations with partners

• Analyze with broadest set of analytics & ML services

MachineLearning

Real-time DataOn-premises

Data Lake on AWS

MovementData Movement


Enterprise Grade Hadoop and Spark

• Scale compute (EMR) & storage (S3) independently

• Store, and process any amount of data—PB to EBs

• Provision one, hundreds, or thousands of nodes

• Auto-scalingData Lake on AWS

Amazon EMR


Machine Learning on AWS

Fram ew o rks &Infrastructure

AWS Deep Learning AMI

G PU(P3 Instances)

M o b ileCPU Io T (G reen grass)

V isio n :

R eko gn itio n Im ageR eko gn itio n V id eo

Sp eech :

Po llyTran scrib e

Lan gu age:

Lex Tran slate

Co m p reh en d

Apache

MXNetPyTo rchCognitive

ToolkitKeras

Caffe2 & Caffe

TensorFlow Gluon

A pplicatio n A I Services

M anagedPlatfo rmServices

Amazon Machine Learning

M ech an ica l Tu rk

Sp ark &

EM R

A m azo n SageM aker

A W S D eep Len s


Machine learning is hard…

1. Data wrangling• Setup and manage

Notebook environments

• Get data to

notebooks securely

2. Experimentation• Setup and manage clusters

• Scale/distribute ML algorithms

3. Deployment• Setup and manage

inference clusters

• Manage and auto scale

inference APIs

• Testing, versioning, and monitoring

Fetch data

Clean & format data

Prepare & transform

data

Train modelEvaluate model

Integrate with prod

Monitor/debug/refresh

6-18Months


Amazon Sagemaker

One-click training for ML, DL, and custom

algorithms

Easier training with hyperparameter

optimization

Highly-optimized machine learning

algorithms

Deployment without engineering effort

Fully-managed hosting at scale

AuthorPre-built notebook

instances

DeployTrain


Inherit global security and compliance controls

Thank YouContinue the conversation on #GRCSummit

accelerating grc by power of cloud...accelerating grc by power of cloud vidya phalke eric z beard...

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