Post on 11-May-2015
description
Thank you for joining us, the webinar will start at:10:00 Pacific / 12:00 Central / 13:00 East / 18:00 UK Time
Manage Databases like Codebases
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• There will be a Q+A session at the end but please feel free to type your questions in the Questions box in the Control Panel in advance
• A recording of the full webinar will be put up online
Presenters
Tim O'Brien• Analyst, CTO• Gleanster Research
Yaniv Yehuda @yanivyehuda • Co-Founder & CTO at DBmaestro• Presenter at world-wide conferences: ODTUG, ilOUG
Kyle Hailey @kylehhailey• Technical Evangelist at Delphix• Oracle ACE, member of the OakTable Network
About Delphix
• Founded in 2008, launched in 2010• CEO Jedidiah Yueh (founder of Avamar: >$1B revenue))• Based in Silicon Valley, Global Operations• 10% of Fortune 500
About DBmaestro
• Founded in 2008, launched in 2010• Founded by Yariv Tabac and Yaniv Yehuda• Headquartered in Israel, Global Operations
Manage Databases like Codebases
Kyle Hailey & Yaniv Yehuda
The Business Need
Copyright@2010, Gartner RAS Core Research
80% of unplanned downtime is due to Change
50% More than
of this, half is due to human errors
40% of changes FAIL Copyright@2008, Juniper Networks, Inc.
Code, Databases, and Agility in 2014May 20, 2014
Tim O’BrienAnalyst, CTOGleanster Research
Industry Trends
Code in 2014
Distributed & Asynchronous New Normal
Self-service Critical to Productivity
Increasing Variety (from Javascript, Java, .NET, Ruby, Python + everything)
Everything is Automated
Industry Trends
Databases in 2014
More than just Relational Increasing Variety (Oracle, Mongo)
Management? Not as Mature as Code
Oddity
Big Data marginally more manageable than traditional RDBMS
“We’re still waiting for the database…”
Code is King
Modern Enterprise
Fully distributed development
Continuous Deployment Pipelines
Everything Automated! - DevOps, PaaS, IaaS
“Every Company is a Software Company”
How did we get here?
Scale Development
Open Source @ Scale Google Chrome, Mozilla Firefox Android, Apache httpd Linux*, FreeBSD
Characteristics Rapid Iterations, Frequent Releases
Numerous Experiments (or Branches)
Thousands of developers
OSS @ Scale established best practices now in use.
Scale Development
Organizations @ Scale Facebook, Wal-Mart, eBay, Salesforce, Intuit
Goldman Sachs, Apple, Amazon, Yahoo!
Google, SSA, Ford, Toyota
Characteristics Rapid Iterations, Frequent Releases
Numerous Experiments (or Branches)
Thousands of developers, Many Teams
@ ScaleEverything isContinuous
Continuous integration and deployment
Modern set of Tools Integrated with:
Source Control – Perforce, Clearcase, Git
Infrastructure-as-a-Service – Openstack
Platform-as-a-Service – AWS, Heroku
Databases? - Still an Integration Nightmare
Case in Point
Example Fortune 500 Relaunch Re-architecture: More distributed,
Move to a PaaS Scope: Everything, 2 Year Migration
Project Size: 1500 Developers, Several
Continents, $100M+
Results? Code: Distributed Projects,
Continuous Deployment Infrastructure: Self-service, On-
demand, Agile Database: Delays, Manual Builds,
Cost Overruns
Root Cause Analysis
Code is Agile Developers move FAST. Branches are fungible, disposable, personal. Deployments managed with DevOps tools
(immediately)
Traditional Databases are Not Costly to Setup Often require Dedicated Hardware Little automation. No Change
Management
“The rest of the department is Virtual but our Databases
are stuck in 1998.”
Worst Practices(we’re all used to)
Lack of Database Change Management:
Shared Developer Databases Results in Contention
Costly, Slow Environment Provisioning
Testing and Staging Not Synchronized with Production
Drag on Productivity and Efficiency
Opportunity lost
“We’ve accepted that the databases causes delays”
What We’ve Seen
1. QA: Expensive, Slow 2. Development: Bottlenecks & bugs3. Provisioning: Delays
1. QA: Expensive, Slow : Long Build times
Build Time
96% of QA time was building environment$.04/$1.00 actual testing vs. setup
Build
Build Time
QA Test
QA Test
Build
1. QA: Expensive, Slow: bugs found late
Build QA Env QA Build QA Env QA
Sprint 1 Sprint 2 Sprint 3
Bug CodeX
1 2 3 4 5 6 70
10203040506070
Delay in Fixing the bug
Cost ToCorrect
Software Engineering Economics – Barry Boehm (1981)
Build QA Env QA
2. Development: Bottlenecks & bugs: Bottlenecks
Frustration Waiting
2. Development: Bottlenecks & bugs: subsets cause bugs
2. Development: Bottlenecks & bugs: subsets cause bugs
3. Provisioning Delays : weeks to months
Management
DBA
System Admin
Storage Admin
Developers Submit Request
Disk Capacity?
Approve Request $$ (2 Weeks)
Approve Request $$
(1 Week)
RequestAdditional Storage?
ProvisionCapacity
File SystemConfigured?
Configure LUNS & Build File System
Coordinate Replication w/ Infrastructure
Re-Parameterize & Configure DB
Mount Recovery DB to
Specific PIT
Begin Work
Approve Request $$ (2 Weeks)
(3 Days)
(3 Days)
(2 Days)
(3 Days)
(3 Days)
…….1-2 Weeks of Approvals, Delays, and Provisioning……
24
Developer Asks for DB Get Access
Manager approves
DBA Request system
Setup DB
System Admin
Requeststorage
Setup machine
Storage Admin
Allocate storage (take snapshot)
3. Provisioning Delays : culture of no
What We’ve Seen
1. QA: Higher costs more code re-work2. Development: Bottlenecks & bugs3. Provisioning: Delays
Three Physical Copies Three Virtual Copies
Install Delphix on Commodity Intel Hardware
Intel hardware
Allocate Any Storage to Delphix
Allocate StorageAny type
One time backup of source database
Database
Production
Instance
File system
File system
DxFS (Delphix) Compress Data
Database
Production
Instance
Data is compressed typically 1/3 size
File system
Incremental forever change collection
Database
Production
Instance
File system
Changes
• Collected incrementally forever• Old data purged
Time Window
File system
Typical Architecture
Production
Instance
Development
Instance
QA
Instance
UAT
Instance
Database
File systemFile system
Database
File systemFile system
Database
File systemFile system
Database
File systemFile system
With Delphix
Database
File system
Production
Instance
Database
Development
Instance
Database
QA
Instance
Database
UAT
Instance
Parallel environments
Instance
Instance
Instance
Instance
Source
What We’ve Seen With Delphix
1. QA: Low cost, fast bug detection 2. Development: Parallelized, less bugs3. Provisioning: Fast, Culture of Yes
1. QA Efficient : Lower cost
Build Time
QA Test
1% of QA time was building environment$.99/$1.00 actual testing vs. setup
Build Time
QA Test
Build
1. QA Fast : bugs found fast and fixed
Sprint 1 Sprint 2 Sprint 3
Bug CodeX
QA QA
Build QA Env
QA
Build QA Env
QA
Sprint 1 Sprint 2 Sprint 3
Bug Code
X
2. Development : Parallelize
gif by Steve Karam
2. Development: Eliminate bugs
3. Provisioning: Fast, Efficient, Self Service, Culture of Yes!
What We’ve Seen With Delphix
1. QA: Low cost, fast bug detection 2. Development: Parallelized, less bugs3. Provisioning: Fast, Culture of Yes
But …
How do we manage database changes as code changes and automate deployment of changes?
Dealing with Risk Smaller and more focused changes are easier to manage (Agile…) Automation of repeating tasks lowers risk of (human) error Development and Operations should work in synergy (DevOps)
45
• More rapid changes• Reacting quickly to market needs• Getting ahead of competition
• Fewer changes backed out• Better collaboration• Fewer defects
• Ultimately better service • Happy customers • Profitability
Why Continuous Delivery?
46
• Team and process• Version everything• Automate your tests• Fix it, properly (no out of process changes!)
• Automate your deployments
Database Continuous Delivery?
47
A quick poll
48
• The database holds your essential information
• Changes can impact the entire system• Need to be synchronized with other
changes• Often overlooked
Database is a Key Component
49
• There is more to a database than SQL scripts– Schema structure– Code– Content and meta-content– Internal dependencies– …
• Ensure that changes are not made without authorization
• Ensure no out-of-process changes
Reaching Inside the Database
50
• Old adage but true• The database is often neglected and therefore
can become the weakest link• Essential from a compliance point of view• Should be the strongest link
The Weakest Link In a Chain
51
Challenges…
Un-coordinated Process
Silos in development
Deployment delays…
Out-of-Process Changes
Errors in production
Lack of confidence in automation
Code overrides
Different methodologies
Lack of history Missing changes
wrong versions
52
Two isolated Processes
Version Control Process Development Process
Check-Out Script
Modify Script
Get updated Script from DB
Check-In Script
Compile Scriptin DB
Debug Scriptin DB
?
??
?
A
A’
53
X1.11.1.11.11.21.31.41.51.61.7
Build Once Deploy Many
Int QA Stage Prod
Database Deploy Script
Environment
Re-Base (due to defects)
DevDev
DevModel
1.1 1.2
1.2 1.3
1.3 1.4
1.4 1.5
1.5 1.6
1.6 1.7
1.11.11.41.7
1.1 1.2
1.2 1.3
1.3 1.4
1.4 1.5
1.5 1.6
1.6 1.7
1.1 1.2
1.2 1.3
1.3 1.4
1.4 1.5
1.5 1.6
1.6 1.7
Out of Process Change
X
X
X
X
X
? 1.1.1
X
54
Dealing with challenges…
Coordinated Process Traceability
Start in the Beginning
No Out-of-Process Changes
Impact Analysis
Automation
Task Based Development
Well Defined Processes
What is DBmaestro TeamWork
• Database Enforced Change Management+ Database version control+ Plugs into the ALM (change request, tickets & work
items)
+ Database merge & change impact analysis
• DevOps Solution for databases + Baseline aware deployment automation, rollback
& recovery+ Plugs into release management & Continuous
Delivery
How?
• Database version control – Enforced Check Out/In – Labels– Rollback/Undo – Audit trail reports
• Database impact analysis – Utilizes version control repository information – 3-way analysis
• Database deployment automation– API – Baselines – Conflict resolution – Customized business logic
57
Version Control - One Enforced Process
58
1.11.21.31.41.51.61.7
Build & Deploy On Demand
*
Int QA Stage Prod
Database Deploy Script
Environment* Execute the same script being executed at the Stage environment
Re-Base (due to defects)
DevDev
DevModel
1.1 1.2
1.2 1.3
1.3 1.4
1.4 1.5
1.5 1.6
1.6 1.7
1.1 1.4
1.4 1.7
1.1.1 1.7
1.1 1.1 1.11.41.7
File Based Version Control
Out of Process Change
1.1.11.7 1.1.11.7
Safety Net For Deployment Automation
Source vs. Target
Action
= No Action
≠ ?
Source vs. Baseline
Target vs. Baseline
Action
= = No Action
≠ = Deploy Changes
= ≠ Protect Target
≠ ≠ Merge Changes
You do not have all of the information
With Baselines and 3 way analysis the unknown is now known
Simple Compare & Sync Baseline aware Deployment
An index exists in Target (Production) but not in source (QA). What should we do? Drop the index or not?
Benefits - Development
• Database change repository• Follow SCM best practices
(Check-Out/Check-In) • All changes are documented• Manage who can do what, where, when &
why
Benefits - Operations
• Integrated deployment engine• Business level audit• Roles & responsibilities enforcement
Benefits - Management
• Complete visibility into changes in progress• Management reports, Audit reports• No silos
+
Time Window
Instance
Instance
Instance
Virtual DatabaseDev1
Dev2
Trunk
Virtual Database
Virtual Database
Developer 1 modify
Developer 2 modify
DBVC
Merge Dev1 to ForkMerge to dev2
Dev2
Dev1Merge to dev1
Merge Dev2 to Fork
Trunk
Merge Dev1 to Fork
Merge Dev2 to Fork
DBVC
Fork
Fork
Fork
Fork
Safe and Efficient Work Process
• Clone relevant number of virtual copies of the Trunk– Dev Team 1-n, Developer a-z, Hot fix environment, Etc…– Work in parallel, save time
• Rely on enforced change process– Know exactly who did what, when and why
• Deployment automation– Save time, mitigate risk– Continuous integration, Continuous Delivery
• Deal with conflicts & merge them into the Trunk• Test before deploy to production
– Pre-prod clone
Q&A
Kyle Hailey @kylehhaileyDelphix: delphix.com
Yaniv Yehuda @yanivyehudaDBmaestro: dbmaestro.com
Tim O'Brien Gleanster: gleanster.com
Thanks!
Kyle Hailey @kylehhaileyDelphix: delphix.com
Yaniv Yehuda @yanivyehudaDBmaestro: dbmaestro.com
Tim O'Brien Gleanster: gleanster.com