xylos cloud services · 2016-03-01 · debunking myths on data & analytics in the cloud •myth...

Cloud Discovery

“Cloud use cases today!”

Geert Baeke

Agenda

• Evolution of public cloud

•Common infrastructure scenarios

• Securing SaaS Applications

•Data and Analytics

Evolution of Public Cloud

•Amazon and Microsoft as the two leading “hyperscale” public cloud providers

•Vendors giving up or scaling down:• VMware vCloud Air • HP Helion• Verizon

Public Cloud Adoption

Source: RightScale 2016 State of the Cloud Report

57%

17%13%

7% 6% 7%

17%

25%

20%

13% 15% 10%

8%

11%

12%

9% 10%

8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

A WS A Z URE IA A S A Z URE PA A S GOOGLE A PP ENGINE

GOOGLE IA A S IBM SOFTLA YER

Running Experiment Plan

Use of PaaS is growing!

Cloud Benefits


Agility as main driver

Cloud Maturity and Benefits


Agenda





Common Infrastructure Scenarios

Primary Storage

• Potentially terabytes of data on file servers

• Small portion actively used

• Use of unlimited cloud capacity

Backup to Cloud

• Store backups of any kind in cloud storage

• Long time retention

• Avoid tape handling and storage

DR to Cloud

• Replicate workloads to cloud

• Orchestrated failover and failback

• Avoid overhead of secondary datacenter/room

Clean up your storage space

•A lot of inactive data is stored on file servers (80/20 rule)

•Back-end storage for file servers on expensive SAN systems

• You need to manage growth, retention, daily backup, disaster recovery

Cloud Storage Opportunity

CloudStorageOpportunity

Use a Cloud Storage Gateway

Azure StorSimple Benefits

What about the network?

• StorSimple does not require a dedicated network connection to Azure• Uses you existing Internet uplink with

SSL encryption

• ExpressRoute is recommended in most Azure scenarios for production• Dedicated bandwidth• Private uplink even for public services• Low latency

ExpressRoute Scenarios


Primary Storage




Backup to Cloud




DR to Cloud




Eliminate backup headaches

•Most common customer questions:• Simplify backup architecture• On-premises backup to disk to cloud• Avoid backup to tape and tape handling procedures

Features to look for

• Native integration with cloud storage• Azure Blobs, Amazon S3 and many others• Deduplication, compression and

encryption as must-haves• You do not want simple copy jobs!

• Backup to local appliance with cloud integration• Backup to disks of appliance• Appliance dedupes, compresses and

encrypts

Microsoft On-Premises Backup Options

Small business or branch:• Agent on Windows Server

• Integration with Windows Server backup tool

Protected Server

System CenterDPM

or

System Center Data Protection Manager*:

• Agent on Data Protection Manager

* Similar option: Azure Backup Server as version of DPM for every Azure Backup customer

Veeam Cloud Connect


Primary Storage




Backup to Cloud




DR to Cloud




Disaster Recovery as a Service

•Disaster Recovery needs to go beyond just the “technical stuff”

•Disaster Recovery often results in great complexity

• Focus on what matters to the business and use “DR as a Service” (DRaaS) if possible

• Focus on workload level

Disaster Recovery with Azure Site Recovery

Communication and Replication

Microsoft Azure Site Recovery

Primary Site

Windows Server

Microsoft Azure Site Recovery

Communication Channel

Replication channel: Hyper-V Replica or

SAN Replication

Primary Site

Windows Server

Recovery Site

Windows Server

Core Features of Azure Site Recovery

• Replicate physical and virtual machines to Azure blob storage

• Smart Replication• Used blocks only• Delta replication for changes

• Failover and failback withRecovery plans• Azure Automation runbooks• Manual actions

• Test failover

Deployment Scenarios to Azure

Replication Source Replicate From Replicate To

VMware virtual machines On-premises VMware server Azure Storage

Physical Windows/Linux server On-premises physical server Azure Storage

Hyper-V virtual machines On-premises Hyper-V host server in VMM cloud (System Center)

Azure Storage

Hyper-V virtual machines On-premises Hyper-V site (one or more Hyper-V host servers – no VMM)

Azure Storage

Replication to offline storage

VMware, Hyper-V and physical

Notes about VMware and physical

No need to deploy replication or orchestration components in Azure

Custom DR Solutions

• In conjunction with partners, Xylos enables custom DRaaS solutions

•When needed?• Dedicated fiber connections• Synchronous replication options• Stretched network• Specific hardware requirements such as firewalls, audio

gateways, …

Call To Action

• Start identifying most common scenarios that work for you

• You are not pioneering! Proven solutions today!

•Besides virtual machines, focus on:• Primary storage with gateways• Backup solutions that are cloud-integrated• DR as a Service

Agenda





Robin Vermeirsch

Securing SaaS applications

Who is using SaaS applications today?

Who knows what users are doing in the cloud?

Lack of visibility

Compliance

Threat prevention

Data security

Security in the SaaS world

• Security Policies/requirements are developed for on premises solutions.

• In many cases SaaS applications are a initiated by the business

• SaaS providers implement ‘some’ security, but does it fit my needs?

• Limited control/visibility what users are doing in the cloud.

• No visibility over anomalies over different applications.

Security in the SaaS world

Does not meet requirements

SHOWSTOPPER

Requirements met by adding

control

COMPENSATED

Requirements met by SaaS

provider

ACCEPTABLE

Change architecture

Adjustment expectations

Src: http://www.gartner.com/webinar/3100619

Evolution in security

Transport

• IP Firewalling

• Segmentation

Protocol inspection

• Proxies

• Deep inspection

Application Protection

• MDM

• Web Application Firewalls

Data CentricAudit & Protection(DCAP)

• CASB

• SPSM

• CDPG

+ Unmanaged devicesShadow ITCompany data is spread over multiple providers How to protect DATA?

Note trend of ABAC in DEV

What do we need?

But how?

CASB (Gartner)

• on-premises, or cloud-based security policy enforcement points

• placed between cloud service consumers and cloud service providers

• to combine and interject enterprise security policies as the cloud-based resources are accessed.

• consolidate multiple types of security policy enforcement.

http://www.gartner.com/it-glossary/cloud-access-security-brokers-casbs

Options to add security

SaaSIaaS /PaaS

SPSMSaas Platform Security

Management

CASBCloud Access Security

Brokers

CDPGCloud Data Protection Gateway

EncryptionTokenization

Masking

User activity monitoring

Data discoveryDLP

Remediation

Usage discoveryUser activity monitoringDLP (passive and active)

User activity blocking (real time)Data discovery

SSO

Vendors: http://www.gartner.com/webinar/3100619

REALTIME RETROACTIVE

Architecture Options

• Using forward proxies

• Integration existing proxies

• Placing Reverse proxies

• Using Endpoint agents

+ IDaaS/MDM/Log integrations

Hackers/unkown

endpointsApproved Endpoint

Unknown SaaSApproved SaaS

Reverse Proxy

Forward Proxy

ControlAccess

&Actions

Existing Proxy

BlockActions

Architecture Solutions

• CASB (Cloud Access Security Brokers)• Forward Proxy• Reverse Proxy• API Integration

• CDPG (Cloud Data Prot. GW)• Forward Proxy• Reverse Proxy

• SPSM (SaaS Platform Mgmt)• API integration

Hackers/unkown

endpointsApproved Endpoint

Unknown SaaSApproved SaaS

Reverse Proxy

Forward Proxy

ControlAccess

&Actions

Existing Proxy

BlockActions

CASB

SPSM

CDPG

What should you look at?

Impact on functionality & operational risk


Implementation strategy

Implementation strategy


Start small and add functionality

Call to action

•Detect shadow IT today (=High Risk)

• Start controlling access to SaaS applications

•Get visibility over user activity in SaaS applications

•Protect your company data in SaaS applications

Agenda





PaaS: Debunking myths on data & analytics in the cloud

Tim Jacobs

Agenda

•PaaS?

•Myth #1

•Myth #2

•Myth #3

•Conclusions

PaaS?

• Provides a platform for:• Development (cloud native apps)

• Content distribution (media / CDN)

• Internet of Things

• Automation

• Data processing & analytics

Data and data analytics?

Prescriptive analytics

Predictive Analytics

Diagnostic Analysis

Descriptive Analytics

Data Collection

Big Data

IoT

Hypes linked together

Analytics

IoTBig Data

Debunking myths on data & analytics in the cloud

• Myth #1 – Predictive analytics & big data are just BI on steroids

• Myth #2 – All my data needs to go to the cloud! Y0u f00lz cr4zy?

• Myth #3 – You need to hold 3 PhD’s to do predictive analytics

Myth confirmed?

Is it plausible?

Blow everything up

No No

Yes

Yes

Myth Debunking Flowchart

Agenda

•PaaS?

•Myth #1“Predictive analytics & big data are just BI on steroids”

•Myth #2

•Myth #3

•Conclusions

New in the data landscape…

1. “Big” data

2. “Artificial Intelligence” & learning from data

3. Cheap hardware + fast & ubiquitious network connectivity

Evolution of data

Big Data Traditional BI


• Big Data & Predictive Analytics will not replace your BI stack

• Different questions, different tooling, different methodologies

• BI and Predictive Analytics worlds are converging :• BI platform extensions to Big Data-esque & Advanced Analytics-y operations

• Big Data tooling gets SQL-like interfaces:Drill, Impala, Hive, SparkSQL, HAWQ, Presto, Vortex, …

• Big Data tooling can do descriptive and predictive analytics: MLLib, H2O, Oryx, Mahout, SAMOA, FlinkML, …

(R)Evolution & convolution

Agenda

•PaaS?

•Myth #1

•Myth #2“All my data needs to go to the cloud! Y0u f00lz cr4zy?”

•Myth #3

•Conclusions

On-premises or cloud?

• Advantages of cloud:• Start fast & fail fast

• Easy consumption of created data models

• Democratic in pricing & availability of algorithms

• Attention points for cloud (mostly exceptions!):

• Data privacy: legislation ↔ provider

• Data volume & velocity: bandwidth

Getting data to the cloud

• Transfer existing data:• “Just upload the CSV”

• Azure Data Factory (SQL, Oracle, DB2, MySQL, Sybas, PostgreSQL, ODBC, HDFS, … )

• Capture event/streaming data:• Eventhub / IoT hub

Scheduling / transformation

Event Hub

Stream A.

Azure Data Factory

Blob Storage

Data Lake

Data Warehouse

Data BaseDirect

Data Mgmt

Gateway

File

Data Base

Data Warehouse IoT IoT

IoT IoT

© The Cloud ®™

Conclusion

• Compliant solutions available through provider

• Subsetting & anonimization easily possible with data transfer tools

Agenda

•PaaS?

•Myth #1

•Myth #2

•Myth #3“You need to hold 3 PhD’s to do predictive analytics”

•Conclusions

Examples use cases

• Predictive Maintenance

• Automatic data & document classification

• Fraud detection

• Product recommendation


• Azure ML studio has a low learning curve• Modular, drag & drop

• Pre-built machine learning algoritms with meaningful default settings

• Use cases: very easy to publish “predictive engine” for your own applications

• Do you need expert knowledge? • Is the out of the box 70% accuracy sufficient?

• Or do you need 95% prediction accuracy?

Example: predicting Belgian house prices

Model Features Prediction accuracy

Linear 1 Just based on m2 living area 48,40%

Linear 2 m2 living area & postal code 69,43%

Linear 3 m2 living area, postal code, # bedrooms, house type

70,36%

Decision Tree 1 m2 living area, postal code, # bedrooms, house type

70,41%

Linear 4 Linear in: postal code, # bedrooms, house type3rd power in: m2 living area

71,17%

Agenda

•PaaS?

•Myth #1

•Myth #2

•Myth #3

•Conclusions

Conclusions

• Three valid use cases for data in the cloud:• Reporting & analytics on big data sets, with new types of intelligence

• Storing and synchronizing (subsets of) your data in the cloud

• Adding intelligence to existing applications you develop

• Advantages of cloud:• Easy to start, quick to get to results, fast decommissioning once completed

• Democratizing of tools & algorithmes lowers starting threshold

• Xylos can help with:• advanced expertise (data scientists)

• data collection & storage expertise

• data consumption / visualization expertise

Evaluations

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clouddiscovery.presenterswall.com

Xylos Cloud Services

xylos cloud services · 2016-03-01 · debunking myths on data & analytics in the cloud •myth...

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