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The Future of The DBADevOps, the Cloud Paradigm, & the Microsoft
Data Platform
Stuart R Ainsworth
http://codegumbo.com
Agenda
Explore (high-level) the Microsoft Data Platform
Describe the typical state of database administration
Define & describe DevOps and the cloud computing
paradigm
Discuss the implications for data professionals
3
1
2
4
1
Assumptions About You
Learning-centered
SQL Server experience
Exposure to database admin & architecture
Desire to build modern skills
3
1
2
4
2
About Me 3
Manage IT for financial services company
Former Data Architect, DBA, developer
AtlantaMDF Chapter Leader
Infrequent blogger: http://codegumbo.com
My
career
trajectory
4
You have brains in your head
And SQL Skills to boot
You'll soar to great heights
On the Data Platform too
You're on your own,
And you know what you know,
And YOU are the one
who'll decide where to go.
http://bit.ly/2j8Wi5z
Where Are We?
Typical SQL Server Person
5
6Typical SQL Server Person
• Specialized knowledge
• May have exposure to other infrastructure or
development tools
• Usually reports to Operations (not Development)
• Often one of the “last stops” in deployment chain
Typical SQL Server Person 7
SQL (DDL & DML)
Performance Tuning
(Code)
Index Analysis
Data Warehousing
Reporting
Development
Skills
Administration
Skills
Server Configuration
Performance Tuning
(Server)
Index Maintenance
Backups and Restores
Security
8MCSA SQL 2012\2014
• 70-461: Querying Microsoft SQL Server 2012/2014
• 70-462: Administering Microsoft SQL Server 2012/2014
Databases
• 70-463: Implementing a Data Warehouse with Microsoft
SQL Server 2012/2014
What’s coming… 9
• Data production is accelerating– Est .79ZB in 2009
– Est 7.9ZB in 2015
– Est 35ZB in 2020 (44 times greater than 2009)
• Data is diversifying– Relational Data
– Big (Size) Data
– Fast Data
– Dark Data
– Lost Data
– New Data
DevOps
Philosophy, not Methodology
10
A (Very) Brief Overview 11
• DevOps is focused on delivering quality, faster.
• Philosophical approach, not methodological– Automation, infrastructure as code, continuous deployment
– Emphasis on communication; silo reduction
• Born out of Agile, several innovators contributing– Patrick Debois & Andrew Clay Shafer – Agile Infrastructure (Agile 08)
– John Allspaw & Paul Hammond – 10+ Deploys Per Day (Velocity 09)
– Gene Kim, Kevin Behr, & George Spafford – The Phoenix Project
The Phoenix Project 12
The Phoenix Project 13
The Phoenix Project 14
Key Takeaways 15
• DevOps is rooted in a sense of continuous improvement
• People over tools
• Reduce silos by focusing on shared goals, not
technology
The Cloud Paradigm
Infrastructure, Platform, Software
16
What do we mean by “The Cloud”?
17
• Trendy marketing term?
• Network hosting?
• Internet connected services?
• Distributed, scalable, shared computing resources?
Product-Focused Paradigm 18
Cloud Paradigm 19
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
Cloud Paradigm 20
Cloud Paradigm 21
Cloud Paradigm 22
Ideal System Architecture 24
• Scalable
• Resilient to Failure (Redundant)
• Service-Oriented Architecture
• Automated Monitoring, Configuration and Build
• “Infrastructure As Code”
• Completely Automatic
– Code checked in -> new build
– Unit & regression testing
– User acceptance testing
– Continuous Integration
– Dependent on “infrastructure as code”
• Micro-releases (100 deployments per day)
• No rollbacks
Ideal Release Process 25
Ideal Operations 26
• Automatic instrumentation (Logging)
– Long Term Storage
– Predictive Analytics
• Automatic Error Logging & Alerting
– Respond to Every Error
– On-call Rotation includes Developers
• Automatic Scaling
– Scale Up
– Scale Down
• “Zero Maintenance”
Ideal Data Architecture 28
Consistent
Available Partition
Tolerant
SQL Server
Relational
Engine
Hadoop
Cassandra
CAP Principle (Gilbert & Lynch)
Microsoft Data Platform
Diversity in Data
29
Microsoft Data Platform 31
Microsoft Data Platform 32
Impact on Careers
Future Prognostications
33
Current Trends 35
• Companies are recognizing the value of different kinds of
data, and an increased need for analytics.
– Adoption of Big Data technologies is on the rise
– Data Science jobs are increasing
– The Internet (or Fog) of Things is coming.
• Operational methodologies like Agile and DevOps are
pushing companies toward the Cloud Paradigm.
Current Trends 36
• The Cloud Paradigm with its separation of duties is
causing companies to realign resources.
– Infrastructure Teams
– Platform Teams
– Software Teams
• Operational technologies (virtualization, scripting) are
allowing organizations to scale out computing resources
with fewer human resources.
Cloud Paradigm 34
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
SQL
SERVER
SOFTWARE
PLATFORM
INFRA-
STRUCTURE
My Predictions 37
• Increased segregation between Development and
Administration roles.
• Number of development jobs will increase
– Diversity of data platform.
– Need for integration.
– Data mining and analysis skills.
• Number of administrative jobs will decrease
– Infrastructure as code, scripting, virtualization
– Product specific specialists for initial configuration
What does this mean for YOU? 38
• Choose your path: Development or Administration
• Developers have opportunities for breadth:
– Big Data (Hadoop, HDInsight)
– Data Science (Statistics, R)
– Visualizations (Reporting, Power BI)
• Administrators have opportunities for depth:
– Always On
– Infrastructure & Platform impacts
– Scripting & configurations
MCSA SQL 2016 39
Querying Data with
Transact-SQL
Developing SQL
Databases
Administering a SQL Database Infrastructure
Provisioning SQL Databases
Implementing a SQL Data Warehouse
Developing SQL Models
40
Contact Me
Stuart R. Ainsworth
Twitter: @codegumbo
Email: [email protected]
Blog: http://codegumbo.com
Slides available: http://bit.ly/2j7lFVb
41
Be Good at Getting Better
Continuous Improvement for your career