The PPT is aimed at the role of DBAs in CLOUD era where they have to learn multiple skills beyond the administration.

1. © Copyright 2017. Apps Associates LLC. 1
Role of DBAs in the Cloud ERA
Satyendra Pasalapudi
Director – Cloud Services
Apps Associates
Feb 11th 2017

2. © Copyright 2017. Apps Associates LLC. 2
About Me
Satyendra Kumar Pasalapudi
Director –Cloud Service at Apps Associates
Co-Founder & President of AIOUG
@pasalapudi

3. © Copyright 2017. Apps Associates LLC. 3
Performance. Growth. Excellence.
Global Reach – US, Europe, India
• Founded in 2002 with HQ in Boston,
MA
• $65M+ Annual Revenue
• 850+ Associates
• 150+ Active Customers
Mature Delivery Model
• GoTo Partner for Oracle Cloud ERP
• CMMI Level 3 & SOC 1 Appraised
• Premier AWS Partner for Oracle and
Migration Competencies
Long Term Focus on Customers and
Associates
• 30 customers with 5 & 10 year relationships
• 40 associates with 5 & 10 year
anniversaries
• Learning & Development and Mentor
programs
• 5% of Revenue Invested in L&D
• 10+ years of Average Oracle experience
• 15+ years of Average Business experience
Integrated Delivery Processes
• Projects & Managed Services
• Flexible Global Delivery ModelOur Strategic Partners

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GeneraTonal Change for Enterprise (IT)
Ÿ Cloud supports mission cri/cal workloads
─ 87% of Enterprises use Cloud for Mission
CriTcal ApplicaTons
Ÿ Cloud use in the enterprise con/nues to
grow
─ Half of the Enterprises say they will use
cloud for at least 75% of their workloads
by 2018
Ÿ No one cloud fits all
─ More than half (53 %) of enterprises use
two(2) to four(4) cloud providers
Source: Verizon 2016 State of the Market: Enterprise Cloud report

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Cloud – Probable to Inevitable
Ÿ GE undergoing most important
transformaTon in 140 year history
─ 9000 ApplicaTons to AWS & to 4000 ApplicaTons
─ 300 ERPs (two years back) to more manageable
─ 34 Data Centers to 4 Data Centers
Ÿ By 2020 - US$15b of Soeware Revenue
Ÿ Changes
─ People - Reduce Outsourcing
─ Technology - Build Approach for things that mafer
─ 20% of ApplicaTons in Cloud as of today
─ 70% of ApplicaTons by 2020 in Cloud
Source: AWS 2015 Keynote – Oct 6 2015
OOW Keynote with Mark Hurd Oct 26 2015
─ Service Management
─ Network Perimeter
─ Risk Based Security Controls
─ Self Service and AutomaTon
─ Financial Transparency

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Hybrid Cloud Framework
HR FIN
SCOM SALES
PROCUREMENT
PLANNING
DW / BI

7. History of Data Management Systems
Magne/c tape
“flat” (sequen/al) files
Pre-computer
technologies:
PrinTng press
Dewey decimal
system
Punched cards
MagneTc Disk
IMS
RelaTonal
Model
defined
Indexed-SequenTal
Access Mechanism
(ISAM)
Network Model
IDMS
ADABAS
System R
Oracle V2
Ingres
dBase
DB2
Informix
Sybase
SQL Server
Access
Postgres
MySQL
Cassandra
Hadoop
VerTca
Riak
HBase
Dynamo
MongoDB
Redis
VoltDB
Hana
Neo4J
Aerospike
Hierarchical model
1960-70 1940-50 1950-60 1970-80 1980-90 1990-2000
2000-2010

8. 3rd Plamorm drives new
demands on the database:
• Global high
availability
• Data volumes
• Unstructured data
• TransacTon rates
• Latency
A single architecture cannot
meet all those demands.
Why?

9. 2005

10. 2009

11. The Role of Data
is Changing

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UnTl now, QuesTons you ask drove
Data model
New model is collect as much data as possible
– “Data-First Philosophy”

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Data is the new raw material for
any business on par with
capital, people, labor
Data is the new raw material for any business on par
with capital, people, labor

14. We Need Tools Built Specifically
for Big Data

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Hadoop and it’s Eco System
• Scale out Easily
• Parallel Computing
• Commodity Hardware
• Solves some Problems
• Complex to Run
• Special Skills to Maintain

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We know we want
collect, store, organize,
analyze and share it.
But we have limited
resources

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The Cloud Optimizes
Precious IT Resources
i.e. Skilled People with
automation(DevOps/SysOps)

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Operational
RDBMS
(Oracle, SQL
Server, …)
In-memory
Analytics
(HANA,
Exalytics …)
In-memory
processing
(Spark)
Hadoop
Web DBMS
(MySQL,
Mongo,
Cassandra)
ERP & in-
house CRM
Analytic/BI
software
(SAS, Tableau
Web
Server
Data
Warehouse
RDBMS
(Oracle,
Terradata …)
Changing Architectures

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What is VirtualizaTon?
• It is a abstracTon of computer hardware resources
Virtualization technology
emulates real — or physical —
computing resources, such as
desktop computers and servers,
processors and memory, storage
systems, networking, and
individual applications.
A hypervisor — also known as a
virtual machine manager
(VMM) — allows multiple “guest”
operating systems
to run concurrently on a single
physical host
computer.
Types
Ø Hardware Virtualization
Ø Full Software
Virtualization
Ø Para virtualization
Ø Hardware-assisted
software virtualization
Ø Component or resource
virtualization
Virtualization players in market

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EvoluTon of VirtualizaTon Types
• 1st Generation: Full
virtualization (Binary
rewriting)
– Software Based
– VMware and Microsoft
Time
• 3rd Generation: Silicon-
based (Hardware-assisted)
virtualization
– Unmodified guest
– VMware and Xen on
virtualization-aware
hardware platforms
• 2nd Generation: Para
virtualization
– Cooperative
virtualization
– Modified guest
– VMware, Xen
Dynamic Translation
Virtual
Machine
Hardware
Operating System
Virtual
Machine
…
Hypervisor
Hardware
VMVM
Hardware
Virtual
Machine
Virtual
Machine
…
Virtualization Logic
Hypervisor
…

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Reasons for VirtualizaTon?
Server Consolidation
Server Provisioning
Backup/Restore
Hosting/ Cloud Computing

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Types of Hypervisors
Oracle VM
VMware vSphere
KVM
Xen
Hyper-V
VirtualBox
VMware Fusion
VMware Player
VMware Workstation
Gues
t OS
Gues
t OS
Gues
t OS
Server
Hypervisor
Type 1 – Native (Bare metal)
Gues
t OS
Gues
t OS
Gues
t OS
Operating System
Hypervisor
Server
Type 2 – Hosted

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VirtualizaTon in a nutshell
Virtualization : Running multiple machines on a single hardware
“Real” hardware invisible to OS
OS only sees an abstracted out picture
Only Virtual Machine Monitor (VMM) / Hypervisor talks to hardware
Traditional
Environment
Virtualized
Environment

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Pros and Cons – Full VirtualizaTon
• Pros
– Disaster recovery, failover
– Virtual appliance deployment
– Legacy code on non-legacy hardware
• Cons
– LATENCY of core four resources
– RAM performance reduced 25% to 75%
– Disk I/O degraded from 5% to 20%
– Network performance decreased up to 10%
– CPU privileged instrucTon dings nearing 1% to 7%

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Cloud EvaluaTon ConsideraTons
Running Oracle On Cloud

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Key ConsideraTons for running Oracle on Cloud
Oracle Database
Compute
Storage /
Shared FS
Load
Balancing &
Network
Backup /
Cloning
Security
Performance

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AWS vs Oracle IaaS - Terminology
AWS ORACLE IaaS
Compute Instance Type (EC2) Shape
CPU VCPU OCPU
Block Storage ElasTc Block Storage Storage Volume
Object Storage AWS S3 Object Storage
Archival Storage AWS Glacier Archive Storage
Snapshots EBS snapshot Storage Volume Snapshot
Network Virtual Private Cloud (VPC) Virtual Cloud Network
Load Balancer ElasTc Load Balancer Oracle Traffic Director
Images Amazon Machine Images (AMI) Machine Images
Data Centers in a Region
Availability Zones (AZ’s)
Availability Domains (AD’s)

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RelaTon between Oracle compute cloud objects
instance
Image list Public IP
(IP reservaTon)
SSH Public
Key
Storage
volume
Shape
Used to create
Used to create
attached to
attached to
associates with
Protocol
(secapplicaTon)
Network group
(seclist) IP list
(seclist)
Access rule
(secrule)
associated with
source inused in
Source/destination in
10 1

29. NoSQL

30. Name Site Counter
Dick Ebay 507,018
Dick Google 690,414
Jane Google 716,426
Dick Facebook 723,649
Jane Facebook 643,261
Jane ILoveLarry.com 856,767
Dick MadBillFans.com 675,230
NameId Name
1 Dick
2 Jane
SiteId SiteName
1 Ebay
2 Google
3 Facebook
4 ILoveLarry.com
5 MadBillFans.com
NameId SiteId Counter
1 1 507,018
1 3 690,414
2 3 716,426
1 3 723,649
2 3 643,261
2 4 856,767
1 5 675,230
Id Name Ebay Google Facebook (other columns) MadBillFans.com
1 Dick 507,018 690,414 723,649 . . . . . . . . . . . . . . 675,230
Id Name Google Facebook (other columns) ILoveLarry.com
2 Jane 716,426 643,261 . . . . . . . . . . . . . . 856,767
BigTable (Wide Column) data model

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Scalability Requirement

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Is RDBMS Scalable?

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Scaling Out RDBMS

34. Web
servers
Database
Servers
MemcachedsS
ervers
Shard (G-O) Shard (P-Z)Shard (A-F)
Read Only Slaves

35. CAP Theorem says something has to give.
• CAP (Brewer’s)
Theorem says you can
only have two out of
three of Consistency,
ParTTon Tolerance,
Availability
Consistency
Everyone always sees the
same data
Availability
System stays up when
nodes fail
Par//on
tolerance
System stays up when
network between
nodes fail
RDBMS
lives here
Eventual
consistency
No go
zone

36. Major influences on non-relaTonal
• Eventually consistent transacTon model
• Consistent hashing
Amazon Dynamo
• Column Family model for sparse distributed columnar
data
Google BigTable
• Paved the way for the document database
OODBMS and XML DBs

37. Dynamo Consistent Hashing
A
C
B
F D
H
E
G
Rowkey=”johnny”
Hash= -6.7e10
Node=H
Hash values -4e10
To -8e10

38. Dynamo Consistent Hashing
A
C
B
F D
H
E
G
Rowkey=”johnny”
Hash= -6.7e10
Node=H First write
2nd Write
3rd Write
2nd Write
3rd Write
Node on a
different rack
Node in a
different data
center

39. Document databases
• Structured documents – XML
and JSON (JavaScript Object
NotaTon) become more
prevalent within applicaTons
• Web programmers start
storing these in BLOBS in
MySQL
• Emergence of XML and JSON
databases

40. MongoDB

41. Sharding Architecture
Linear scaling and replica/on
• Elastic Auto Sharding
(split, add, contract)
Store
• Writes to elected
node with flexible
durability
• Reads from any
node in shard
Shard
M
R
R
Shard
M
Shard
R
R
R R
Application
NoSQL Driver
M
Shard
R
R
M
• Auto re-balance of
data on expansion
Expand

42. Oracle Sharding (beta)
Shard Directory
Coordinator
And Catalog DB
Replica 1
Shard 1
Replica 2
Shard 2
Replica n
Shard n
Shard Chunks
Shard 1
Shard Chunks
Shard 2
Shard Chunks
Shard n
Shard Directory
Coordinator
And Catalog DB
Shard
Director
Shard
Director
Shard
Directors
Application
SQL including shard keySQL without shard key
1
4
2
3
5
6
Database Client
Router
(Mongos)
Config server
Config server
Shard 2
(mongod)
Config server
Config server
Config Server
(mongod)
Config server
Config server
Shard 1
(mongod)
Config server
Config server
Shard 3
(mongod)
1 1 1
23

43. On Premises Oracle CloudSame Architecture
Same Software
Same Skills
Hybrid Cloud
Integrated and Hybrid Cloud database soluTon
Database Cloud Service

44. Databa
se
Ready
for Use
Allocate
Compute
Allocate
Storage
Set Keys &
Privileges
Request
for
Service
Provision
OS
Install &
Configure
Database
Configure
Tools
Configure
Access
Configure
Backups
Reduced time and
complexity to provision
database services
Increased
standardization of the
“fleet”
Also use to deploy Maximum
Availability Architectures
Benefits
Automated database and infrastructure provisioning and administraTon
Database Cloud Service

45. Automated
DBA and Patching
Backup/Recovery
plus HA & DR
Simple Provisioning
Any Language Maximum Security
Local and Remote
Management
Oracle Cloud – Security By Default
Database Cloud Service - AutomaTon

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Capture
Trail
Route
Deliver
Pump
GoldenGate Cloud Service
GoldenGat
e
Database as a Service
Hadoop as a Service*
Database
Cloud Service
Exadata
Cloud Service
Big Data
Cloud Service
GGCS
GGCS
GoldenGate Cloud Service
ü Real-time Data Replication
Service in Oracle Cloud via
Subscription or Hourly basis
Key Benefits
ü Changed Data delivery is
more effective than batch
processes
ü No Data Loss reliable and
proven core GG technology
ü Realtime Data always up to
the moment replication &
visibility
3rd Party Cloud
ü Migrate from Amazon any
database from AWS RDS
ü Deliver to 3rd Party Clouds
from on-premise databases
3rd Party Cloud
GoldenGate

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Oracle Database Cloud – Summary of Services

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Cloud DBA
DBA/
NoSQL 60%
Network
Admin 10%
Storage
Admin 10%
Automa/on
20%
= + + +
Prepare yourself for * as a service

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51. Thank You!