Create a Private Database Cloud in the Public Cloud using the Oracle Autonomous Database; Kris Bhanushali - Trivadis TechEvent 2019

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Private Database Cloud in Public Cloud using Oracle
Autonomous Database
August 2019
Kris Bhanushali
Sr. Principal Product Manager
Autonomous Database
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The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, timing and price of any
features or functionality described for Oracle's products may change and remains at the
sole discretion of Oracle Corporation.
Safe Harbor Statement
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Provision
Rapidly and easily creates
mission critical databases
Creates Exadata+
Cloud Infrastructure,
RAC+ scale-out database,
Active Data Guard+ standby
Autonomous Database – What and How
+ Unique to Oracle
Manage
Automates all infrastructure
and database maintenance
Patches all software online+,
tunes settings, performs
all OS and SYSDBA
operations, diagnoses errors+
Secure
Protects data from
external and internal threats
Applies security updates
online+, prevents admin
snooping with DB Vault+,
encrypts all data

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Protect
Recovers from any failure
without downtime
Automates backup, restore,
application transparent+
failover within cluster
or to remote standby
4
Autonomous Database – What and How
Scale
Scales online for highest
performance and lowest cost
Scales Up or Out as needed+;
instant, automatic, online+;
Elasticity enables
pay-per-use+
1 2 3 4 5
Optimize
Optimally runs workloads
without human direction
Automatically optimizes
data formats, indexes+,
parallelism+ and plans+ for
each workload
+ Unique to Oracle

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ORACLE
AUTONOMOUS
DATABASE
DedicatedServerless
Ultra-Simple and Elastic
Customizable Private Cloud in
Public Cloud
One Autonomous Database – Two Deployment Choices

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Workload Optimization

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• Runs on Exadata – world’s fastest database platform
– Fastest storage using latest NVMe flash
– Fastest communication - RDMA over InfiniBand
– Smart offload of queries to columnar cache in Exadata Storage
– Transparent elastic scaling for both OLTP and analytics
• Machine Learning optimizes each workload
– Automatically creates indexes for transaction processing
– Automatically creates data summaries for analytics
– Automatically creates columnar vector-processing formats
– Automatically parallelizes workload
Autonomous Database Provides Effortless Extreme Performance

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• Machine Learning algorithms process changes
to find new optimal plans and indexes
• Optimizer continuously captures new SQL
statements and changes in data volume
– Like capturing changes in traffic patterns and volume
• SQL Plans adapt as data volume changes
– Like driving directions that adapt as traffic changes
• New Indexes created if they speed up new SQL
– Like automatically creating new roads and bridges
* Coming soon 8
Continuous Optimization – Enabled by Machine Learning

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Automatic Indexing
Indexes implemented using Machine
Learning
Reinforcement Learning allows it to learn
from its own actions as all candidate indexes
are validated before being implementing
The entire process is fully automatic
Indexing activities are viewable, controllable,
and auditable
Real-time optimizer statistics gathering
ensures plans stay current

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ATP In Action On Netsuite Workload
• Ran a complex Netsuite workload, and compared ATP to existing expert tuning
• 17,542 SQL statements, 1,852 tables, 8,151 indexes - years of tuning to create these indexes
– Before running on ATP, all indexes and statistics were dropped
10
ATP achieved identical performance to expert manual tuning
ATP stays tuned as workload changes
Elapsed
Time
(sec)
Expert Autonomous
11551172
Indexes
Used
Expert
Autonomous
1733
4663

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Client Connections

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• Connect to Services for Workload Prioritization and Maintenance
• Applications connect to a pre-defined database service to control:
– SQL parallelism, relative priority, max concurrently executing users
SERVICE
DEFAULT SQL
PARALLELISM
SHARE OF
RESOURCES
CONCURRENCY
BEFORE QUEUING
TPURGENT MANUAL 12 100 X CPUs
TP 1 8 100 X CPUs
HIGH CPUs 4 3
MEDIUM 4 2 1.25 X CPUs
LOW 1 1 100 X CPUs
OLTP
DW, Batch,
Reporting
Client Connections Best Practices
• Key Considerations,
– DW Query Parallelism, OLTP Concurrency, Overall Request Prioritization

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Client Connections
• Secure Connections
– Wallet based TLS Certificates, normal SQL *NET
• Connection Services
– Priority based, workload specific
• Transaction Processing, Reporting
• Transparent Application Continuity
– Tracks and records session and transaction state
• Recovers and replays in the event of unplanned outage
– Proactively drains services before maintenance
– Hides planned switchover and/or failure events
Secure and Highly Available Client Connectivity
Autonomous Oracle Database
4. Transparent Application Continuity
Currently, unique to Dedicated

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Deployment Use Cases

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Autonomous – Private Database Cloud in Public Cloud
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• Administrator specifies size, region, and availability
domain of desired dedicated Exadata Infrastructure
• Administrator then partitions the system by specifying
desired clusters and container databases
• Database users provision databases within container
databases
– Users just specify DB compute (OCPUs) and max storage
– CPU and storage can elastically grow or shrink online
• Billing is based on size of Exadata Infrastructure and
number of CPUs used by the databases
– Can bring existing database licenses to lower costs
RAC CLUSTER
WEB STORE
SHOP SHIP….

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Autonomous Dedicated Isolation
16
RAC CLUSTER
• Dedicated allows multiple levels of isolation
• Database (DB)
• Container database (CDB)
• Cluster of VMs
• Separate Hardware (Exadata Infrastructure)
• Hardware Enforced Private Network (VCN)
• The level of security and performance isolation can be
tailored to the needs of each database
• Implementing isolation is normally complex but in
autonomous you just specify what you want
WEB STORE
SHOP SHIP….

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Autonomous Dedicated – Customizable Operational Policies
17
WEB STORE
SHOP SHIP…. • Customizable database separation policies:
• Separate critical, general purpose, and test databases
• Separate databases by organization (sales, HR, marketing)
• Customizable software patching and upgrade policies:
• Deploy new versions on test/dev database before production
• Avoid updates during peak periods (e.g. sale, quarter close)
• Control upgrade to conform to application certified version
• Customizable availability policies (SLA):
• Specify level of HA and DR needed for each container DB
• Customizable overprovisioning and peak usage policies

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• Simplest deployment has single cluster and single
Container Database (Web Store)
– One service level and maintenance update schedule for all
• All Databases (Shop, Ship, etc.) are created in the
single Container Database
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Simple Private Cloud in Public Cloud
WEB STORE
SHOP SHIP….

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WEB STORE
SHOP ... SHIP
MFG
PARTS LABOR
Sophisticated Private Cloud in Public Cloud
TEST
DB1 DB2 DB3
RAC CLUSTER
…
• Separate container DBs (CDBs) for WEB STORE, MFG, and TEST
– TEST workloads isolated from production workloads
– TEST DBs get patches and new versions first
– WEB STORE CDB configured with remote replica for Disaster Recovery
– WEB STORE and MFG CDBs separated for independent patching
– High overprovisioning in TEST, no overprovisioning in STORE
• Visibility and access to CDBs restricted by cloud user group

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Security

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• No highly privileged access - no Root or SYSDBA
• No login allowed to OS or CDB
– No callouts to OS allowed
– Prevents installing or modifying any software on system
• Secure Configuration deployed at all levels – Network, OS, DB, storage, etc.
• Databases run in customer’s private Virtual Cloud Network
– Prevents unwanted network connections
– Public IP not required
• Network encryption available
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Security

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Patching And Upgrades

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Patching Policy
• Oracle is Responsible for all patching operations
• Quarterly Patching of all components (on-demand for critical security issue)
– Firmware, OS, Storage, Network, Hypervisor, Clusterware, Database
– Installs new Gold Image of patched database executables rather than applying patch
• Patching is automatically scheduled based on customer preferences
– Customer can adjust timing to accommodate critical business periods
• Patches applied rolling across RAC nodes and Exadata storage servers
– Database is continuously available to application
– Applications using Application Continuity best practices run without interruption

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Quarterly Database Updates - Example
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Quarterly UpdatesAnnual
Release
Production April July October January April
19.2.0 19.3.0 19.4.0 19.5.0 19.6.0 19.7.0

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Revisions - Example
25
Production April July October January April
19.2.0 19.3.0
19.3.1
19.3.2
Update
Revision #1
Revision #2

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Updates and Revisions
26
Production April July October January April
19.2.0 19.3.0 19.4.0
19.3.1 19.4.1
19.3.2 19.4.2
Update
Revision #1
Revision #2

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• Customers selects either current or previous Update or Revision
• Allows applying latest Update on test system, Revision on production
• Allows for one-off and application specific gold images
Patching Options

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High Availability

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Autonomous Database is Highly Available
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• Automatically protects from all types of downtime:
Failures
Site Outages
Maintenance
Changes
User Errors
No ridiculous exclusions to availability in fine print
– Amazon excludes planned downtime, database bugs, regional outages, etc.
– Exadata+, RAC+
– Active Data Guard +
– RAC Rolling Updates+, App Continuity+
– Online Indexing, Edition Based Redefinition+
– Flashback Database +, Table +, Query+
+ Unique to Oracle

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• High Availability - Protection from hardware failures,
software crashes, patches, updates
– Uses RAC Database, App continuity, Flashback DB, redundant
network, triple mirrored storage, and daily backup
• Extreme Availability – Adds protection from site
outages and data corruptions (coming soon)
– Uses Active Data Guard Standby
– Service Uptime SLA per Month: 99.995 NRX%
• NRX = No Ridiculous Exclusions
– 99.995% Uptime = at most 2m 12s of downtime per month
– Goal is less than 20 seconds application impact from any
availability event
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Primary Database
Site #1
Site #2
Standby Database
Active
Data Guard
Backup
Service
Availability Policies

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Backup Policy
• Fully automated daily backups to Cloud Object Storage
– Backup of archive logs performed every hour (will be 15 minutes soon)
• Retention time for CDB backups is configurable (7-60 days)
• Immediate backups can be created on demand by DB Admin
• Restore at PDB level by the DB Admin
• Zero Data Loss Recovery Cloud Service will be used for backups in future
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Empowering Developers

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Autonomous Database empowers Developers
• Fastest and simplest creation of database
– Just specify capacity and name
• No database management, no support from I.T. required
– Fully automated tuning, scaling, patching and upgrading, etc.
• Most Flexible and Productive development
– Single database for Relational, JSON, Spatial, Graph, Text, etc.
– Full set of SDKs - Java, Python, Node, Go, .NET, Ruby, C
– Industry standard compliant; ISO SQL, JDBC, PEP249 etc.
– Access via REST, OCI CLI, SDK to integrate with common dev pipelines
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Rich Developer Tools
• Built-in SQL Developer Web
– Sophisticated development environment for SQL and PL/SQL
– Worksheet for running queries and scripts, reports interface
– Perfhub for monitoring applications and database
– Complete data modeling solution
• Built-in Application Express (APEX)
– Simple low-code web-based application development and execution
• Built-in REST Data Services (ORDS)
– Makes database access from applications super simple by automatically
building REST interfaces to database tables and procedures
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• Terraform Orchestration
– OCI Provider: https://www.terraform.io/downloads.html
• Language SDKs and IDE toolkits
– Java, Python, Ruby, & Go: https://docs.cloud.oracle.com/iaas/Content/API/Concepts/sdks.htm
– Eclipse Toolkit:: https://docs.cloud.oracle.com/iaas/Content/API/SDKDocs/eclipsetoolkit.htm
• Containers
– Using Docker with ATP example:
– https://github.com/oracle/learning-library/blob/master/workshops/autonomous-transaction-
processing/LabGuide800BuildingMicroservicesOnATP.md
• Client Compute for Database in Oracle Cloud Marketplace
– Oracle demo client image, configured during OCI Compute Provisioning
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Orchestration & Developer SDKs

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Cost Savings

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Autonomous Database Slashes Total Database Costs
More Importantly:
• Eliminates full-stack administration costs
• Eliminates cost of downtime
• Accelerates development and time to market
37
Bring Your Own
License (BYOL)
Eliminates
software costs
Exadata Speed with
Self-Optimizing DB
Reduces runtime
costs up to 80%
+
Online Elasticity
with Pay-Per-Use
Cuts runtime costs
up to another 90%
+

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• Subscribe to Exadata Infrastructure – e.g. Quarter Rack
– Minimum 1 month term (soon week), no minimum OCPUs
• Exadata Storage cost included as part of infrastructure
• Choose License Included, or BYOL model for software
– License Included model has all Database Options (RAC, ADG, etc)
– For BYOL need Multitenant, RAC for >16 OCPU, ADG for uptime
guarantee
• Choose number of ATP or ADW OCPUs for each database
– Can change OCPUs - Billed on aggregate OCPUs for all DBs per hour
• Up to 60 days of Backup retention included in v1
38
Autonomous Dedicated – Pricing Model
ONLINE STORE
SHOP SHIP….

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Summary
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Spend Less
–Reduce Admin Cost: Eliminates expensive, tedious, unsafe manual database management
– Reduce Runtime Cost: Cloud pay-per-use, Exadata speed, and self-tuning cuts costs up to 90%
Reduce Risk
– Prevent cyber-attacks: Secure configurations, fully automatic and online security updates
– Always Available: 99.995% uptime guaranteed including maintenance and DR
– Proven: Runs all your enterprise workloads, easy migration of existing databases
Innovate More
– Refocus talent: Focus on new projects, user experience, analytics, ML, instead of admin
– Develop faster: Instant provisioning, self-tuning, integrated database app development
All Benefits of Autonomous Database
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Specific Benefits of Autonomous Database – Dedicated
41
• Provides a Private Database Cloud running on dedicated
Exadata Infrastructure in the Public Cloud
– Runs all your databases - any size, scale, or criticality
• Highest Isolation from other tenants
– Multiple levels of isolation protect from noisy or hostile neighbors
• Customizable Operational Policies
– Customer can control provisioning, updates, availability, density
• Available as a Cloud at Customer solution in 2019