unlocking the potential of database automation

Unlocking the potential of

dev/test/prod automation

October 2016

Before We Begin

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Presenters

Gary Hallam

CTO, Director of Presales, EMEA at Delphix

Gary has a development & consulting background with a lot of global project delivery

experience. He ran a remote tech pre-sales team at Oracle before joining Delphix.

Yaniv spent the last years raising awareness about the challenges around database

development and deployment, and how to support database Continuous Delivery.

© 2016 Delphix Corporation 4 4 © 2016 Delphix Corporation

Over 30 of the Global100 run on Delphix

Financial Healthcare Telecom Manufacturing Retail Technology

5 © 2016 Delphix Corporation

Delphix value

Accelerate application release cycles

Meet data privacy requirements

Make large scale data accessible

Reduce infrastructure requirements

All at the same time

Simplify and automate database deployment processes in an

agile environment and reduce critical application downtime.

10X Faster time to market

15% Increase in team efficiency & productivity

80% Reduction in application downtime due to human errors

100% Control, 100% Compliance - control and audit who, does what, when and why!


Continuous Delivery “Stack”

VIRTUALIZATION

AUTOMATION • Self service environment creation

• Continuous integration, release delivery

• Virtualized runtime environment

• Instantiate base system image

• Install and configure software

• Configuration as code

• Connect services across systems

• Dynamic scaling

• Find and correct problems

• Analyze and tune performance

CONFIGURATION

MANAGEMENT

ORCHESTRATION

MONITORING


Data Is The Missing Link

VIRTUALIZATION

AUTOMATION • Self service environment creation

• Continuous integration, release delivery

• Virtualized runtime environment

• Instantiate base system image

• Install and configure software

• Configuration as code

• Connect services across systems

• Dynamic scaling

• Find and correct problems

• Analyze and tune performance

CONFIGURATION

MANAGEMENT

ORCHESTRATION

MONITORING

DATA MANAGEMENT

▸ How do you supply

production data?

▸ How do you share

the data?

▸ How do you stand

up data in new

environments?

Your data has never done this before


Data Virtualization: How it works

STORAGE STORAGE

NON PRODUCTION PRODUCTION

STORAGE

APP

DBMS

STORAGE

APP

DBMS

APP

DBMS

APP

DBMS

NON PRODUCTION PRODUCTION

STORAGE STORAGE STORAGE

APP

DBMS

APP

DBMS

APP

DBMS

APP

DBMS

Collect & compress

production data

Capture All Data

Create, rewind, refresh,

point-in-time virtual copies

Self Service

Share data blocks instead

of duplicating data

Virtual Data

Continuous change-data

recording

Time Machine


Delphix Architecture Schematic

Other Databases

Flat files (Applications)

EBS Data Sources

and VDBs

DELPHIX ENGINE

Production

Sources

Target Host

VDB

Target Host

VDB

TCP

Synchronization

(Incremental

Backups)

Any

Storage

Data

Self Service


DEV TEAMS: Power Data Features

to Accelerate SDLC

Governance Model Across Dev Teams, IT Ops

AUTOMATE

Provision apps,

DBs with right data

in minutes

MASK

Replace private,

sensitive data with

masked values

RETAIN

Store 30 days in space

of one for restore,

archive

REPLICATE

Replicate within, across

sites, or to the cloud

TRANSFORM

Convert Unix data into to

Linux for modernization

OPS TEAMS: Full Security, Control,

& Resource Allocation

ROLLBACK

Reset to run A/B tests, recover

from errors and data loss

SYNCHRONIZE

Dial multiple applications to

exact same time

BOOKMARK

Mark release changes,

business events

BRANCH

Pass environments to/from

Dev and QA

REFRESH

Refresh to the latest data

for high fidelity testing,

analytics


User Interfaces and Automation API

Dev Ops


Accelerate Releases – “Shift Left” Quality

200 TB

Storage saved

20 min

Environment turnaround

60%

Lower Defect Rates

Case Study: Fortune 500 Financial Institution

• Massive growth in online platform usage, demand for features

• Struggling with quality issues impacting customer experience

• Explosion in data growth, rising IT costs

0

100

200

300

400

500

Dev Testing UAT Production

Bugs Discovered Before After

400

300

200

100

0


Accelerate with Synchronised Application Time Travel

Switch

Branch/Version

ORCL

SQL

/application

TEMPLATE

Synchronize data

delivery across

sources

Enable short

Feedback Loops

CONTAINER Self-Service


Developers Can Test and Undo Changes Quickly

Developer resets in minutes. A new project requires a

destructive schema change.

The developer creates a

bookmark

Developer tests schema change.

Change is not correct and

development is unusable.

Test Developers

can’t work

Developer Developer Developer Developer

Developer makes changes to

their script and successfully re-

executes.

Test Developers

continue to work

1:30:56 P.M.


Increase Quality and Speed Delivery with Self-Service

Tester resets in minutes,

continues testing

Tester logs defect and creates a

bookmark of the same name and

shares with development

Tester encounters error

1:30:56 P.M.

Developer

Errors are found earlier using

real business data

Developer opens defect ticket

and creates a branch off of the

bookmark in minutes

Developer

After fixing the defect, the

developer activates the

branch he was previously

working on and continues

development


What About Data Security of Virtual Data?

PRODUCTION DATA

20%

80%

NON-PRODUCTION DATA

NON-PRODUCTION DATA:

» REPRESRENTS LARGE SURFACE AREA

OF RISK

On average, 8-12 copies for every production

source

» ENTAILS DISPARATE DATA SOURCES

secured with a variety of tools and processes

» IS CONSTANTLY GROWING

and changing over time

Data Masking Can Dramatically Reduce The Surface of Risk


Evolution of Data Masking

CAPABILITY

HOME

GROWN

SCRIPTS

VIRTUAL

DATA

MASKING

EXTRACT

TRANSFORM

LOAD

STORED

PROCEDURE

▸Mask Once and Share

▸Simplicity: Easy to implement,

easy to use

▸Database Agnostic

▸Self-service & automation

▸Enterprise Architecture


Delphix Data Masking

• Verify all sensitive data is

masked

• Alert admins if vulnerabilities are

identified

• Deliver assessment to auditors

• Mask data without any programming

• Maintain usability with fictitious, but

realistic data

• Apply masking with consistency,

repeatability

• Identify sensitive data across

sources

• Assign masking algorithms to

match data

• Report risk profile across the

enterprise

Profile Secure Audit

Name

SSN#

Phone#

CC#

Name

SSN#

Phone#

CC#


Data-centric security and reduced risk

Secure, virtual data sets:

Reduce privileged user risk by automatically masking data prior to access

Reduce surface area of risk by eliminating admin touch points

Secure data record from vandalism with independent, granular time machine

18 hours

Mask Data

6 hours

Standalone

Masking

10 min

Mask Data

4 hours

Deliver, Provision Masked Data

Provision masked data in minutes

Realistic, irreversible, repeatable

Maintains referential integrity


Resolve the Data Bottleneck for Continuous Integration

Implement DevOps capability – rapid spin-up / tear down with full datasets

Self Service Automation Integration


A

5%

subset

A

20%

subset

Production Data Manipulation Test Data Factory Developer Self-Service

Mask

Subset

Add

Synthetic

Dev QA Test

A

A

A

A

A

A

A

10% subset,

masked

A

Full

copy

A

Prod +

synth

A

Prod +

synth

A

Masked

copy

Collect, bookmark,

& store

Bookmark, reset,

branch, etc.

Collect, compress,

& synchronize

Provision, mask,

& replicate

A

Full

copy

A

Prod +

synth

A

10%

subset

Data Delivery Mechanism

1/10th

1/10th

1/10th

Storage-Efficient Time Machine Integrated Masking Self-Service

A Test Data Management Factory

Int Stage Prod

Dev Dev

Dev Sandbox

‘Break Glass’

Out of

Process

Change Team

A Dev

Team

B Dev QA

Used to take days, now its so easy!!!

But now, people are starting to make changes… And we need to mange them and push them forward!

Int Stage Prod

Dev Dev

Dev Sandbox

‘Break Glass’

Out of

Process

Change

…

Team

A Dev

Team

B Dev QA

We have undocumented changes…

And conflicting changes

We need to merge everything… and deal with conflicts…

We MUST Identify that drift… as scripts that worked, can no longer be trusted

or else…

And be able to easily merge everything where it belongs…

▪ We need tools and processes to support that, but…

− Challenging manual source control process

− Static deployments code overrides and configuration drift

− Dynamic deployments tools unaware of version control

− No release automation red-flags – don’t know when to stop the line…

File Version Control Process

DB Development Process

Check-Out Script

Modify Script

Get updated Script from

DB

Check-In Script

Compile Script in DB

Debug Script in DB

?

?

?

?

A

A’

72% Admit database may not be in sync with the source repository

X Int QA Stage Prod

Dev

Dev

Dev

Model

‘Break Glass’

Out of Process

Change

X

X

X

X

X

X

…

Configuration drift…

60% Of those manually building scripts have to fix or tweak them regularly as part of a deployment process

Safe to automate?

70% of those using compare & sync tools have to review and fix the results as they can't always trust them to automatically deploy correctly

‘ ’

Revision history

Actions

Standard IDE

Change management

Int QA Stage Prod

Dev Dev

Dev Model

‘Break Glass’

Out of Process

Change

Validate

Configuration Drift prevention / conflict identification and

Validated execution

OR

Validate

Validate

Dynamic in nature Static in nature

Dev - Baseline aware analysis Ops – Validated execution

- Understand the nature of the changes

- Raise red flags on conflicts

- Support out-of-process changes

- Utilize baseline aware analysis

…

Track all changes Alert security monitors Create an audit log for compliance reports

Define a process Automate the process Prevent/Alert out of process changes

Int Stage Prod

Dev Dev Dev

Sandbo

x

‘Break Glass’

Out of

Process

Change

…

Team

A Dev

Team

B

Dev

QA

We have undocumented changes…

And conflicting changes

We need to merge everything… and deal with conflicts…

We MUST Identify that drift… as scripts that worked, can no longer be trusted

or else…

And be able to easily merge everything where it belongs…

Check out/in changes

Merge changes

Identify changes

vs baseline

Identify drift

Merge back changes /

Get latest version

Validate deployment

Unique: Database Enforced Source Control

Unique: Enhanced Security and Regulatory Compliance

Unique: Database Merge and Build Automation

Database Release Automation

Delphix & DBmaestro

LLGR2

SQL

/app_config

JUL 1,

13:31:51

JUL 1,

09:00:00

JUL 1,

13:28:29

JUL 1,

11:30:12

Synchronize data

delivery across

sources

Enable short

Feedback Loops

JUL 1,

15:11:27

Baseline Label 1.1 Label 1.2 VALIDATE

UNLOCK INNOVATION

Questions…

unlocking the potential of database automation

Software