The document provides an overview of Amazon Web Services (AWS) and demonstrates several key AWS services. It discusses compute options like EC2 virtual machines and container services. It covers storage services like S3, Glacier and EBS volumes. It demonstrates database services like RDS, Redshift and DynamoDB. It also shows big data services like EMR for Hadoop and data pipelines for transferring data. The document concludes that EC2 is good for testing, training and production, while S3 and Glacier are better for archiving, and services like RDS, Redshift and DynamoDB provide specialized database functionality in the cloud.
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
AWS for the SQL Server Pro
1. AWS for the SQL Server Pro
@LynnLangit
Nov 2013
2. Data Expertise / Lynn Langit
Practicing Architect
• Cloud Deployments (Azure, AWS, Google)
Technical author / trainer
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Google Cloud Developer Series
SQL Server 2012 Developer Series
Cloudera Certified Developer
2 books on SQL Server BI
Industry awards
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Microsoft – MVP for SQL Server
Google – GDE for Cloud Platform
10Gen – Master for MongoDB
Former MSFT FTE
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4 years
3. What and Why AWS?
Market leader
AWS
Amazon’s cloud
Large Set of
services
• Compute
• Data
• More
• In market longest
• Usually cheapest
• Most often used
in production
17. RDS vs. EC2 for SQL Server
Why RDS
costs more
• Provisioned IO –
performance guarantees
• Scheduled backups
• Point in time restores
• Scheduled maintenance
windows
• Full use of all SQL tools,
SSMS, Profiler, DTA, etc…
• Supports Availability Groups
(requires 2012 Enterprise)
• Cross-regional snapshots
29. Demo – AWS SDK
Add-in for Visual Studio and .NET
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April 2013
30. Cloud Database Services by Vendor
AWS
Google
Microsoft
Virtual Machines
EC2 w/SQL Server
GCE – Linux only
Azure VM – W/SQL
Server
Cloud RDBMS
RDS - SQL Server
Redshift -Postgres
mySQL
MariaDB
SQL Azure
NoSQL buckets
Key-Value stores
S3, EBS, Glacier,
DynamoDB
Cloud Storage
HR Datastore on GAE
Azure Blobs
Azure Tables
Pipelines
Data Pipelines
Via APIs only
SSIS (on-premises)
Streaming
Machine Learning
Custom EC2
Prospective Search &
Prediction API
StreamInsight
Document
MongoDB on EC2
None
MongoDB on Windows
Azure
Hadoop MapReduce
or Dremel
MapReduce on EC2
using S3
Big Query
HDInsight (HDFS) on
Azure
Data sets & other
EBS volumes w/datasets
Freebase
Translation API
Full-text search
Azure Marketplace
34. Creative Financing
Regular Pricing
• Use what you need and no more, i.e. instance size, storage size…
• Watch for price drops – RDS price decrease this week
Smart EC2 Instance Usage
• Pause EC2 instances to reduce compute charges
• Delete EC2 instances to reduce storage charges
Vanity Pricing
• Set pricing alerts
• Use spot pricing
• Re-selling compute / storage
37. Tip: Use Pricing Calculators
Example – from RightScale ‘PlanForCloud’
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38. Conclusions
EC2 for testing, training and production (IaaS)
S3 for archiving R/W
Glacier for archiving W fast & cheap, R slow & expensive
RDS for HA SQL Server
Redshift for Data Warehousing on demand
DynamoDB for fast NoSQL – on SSDs
Elastic Map Reduce for easy Hadoop MapReduce
http://aws.amazon.com/rds/sqlserver/ and http://aws.amazon.com/rds/faqs/#4Can scale to larger instances, can backup, can restore up to 5 minutes, all tools work, all patching is managed
Hadoop on AWS - http://wiki.apache.org/hadoop/AmazonEC2
S3 = .12 / GB / month -> $ 150 100 GB / yrEBS = .10 / GB / month -> $ 100 100 GB / yrEC2 = .12 / hr (Small, on-demand, Windows) -> $ 1051 run all year (up to 3.85 / hr, down to .01 / hr for spot instances) can be PLUS other services, i.e. CloudWatch…RDS = .14 / hr (small, on demand, SQL 2008 STD) -> $ 1226 run all year ( up to 3.85 / hr, down to .05 / hr to heavy utilitization PLUS up/down data chargedDynamo = .01 / 10 writes & .01 / 50 reads PLUS up/down chargesElastic Beanstalk / Windows = starter package $ 42 / month -> $ 504 / yr
http://aws.amazon.com/usergroups/ & http://aws.amazon.com/aws-training/