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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
July 13, 2016
Deep Dive on Amazon Relational
Database Service
Scott Ward, Solutions Architect
What to expect
• Amazon RDS overview (super quick)
• Security
• Metrics and monitoring
• High availability
• Scaling on RDS
• Backups and snapshots
• Migrating to RDS
No infrastructure
management
Scale up/down
Cost-effective
Instant provisioning
Application
compatibility
Amazon Relational Database Service (Amazon RDS)
Amazon RDS engines
Commercial Open source Amazon Aurora
Trade-offs with a managed service
Fully managed host and OS
• No access to the database host operating system
• Limited ability to modify configuration that is managed on the
host operating system
• No functions that rely on configuration from the host OS
Fully managed storage
• Max storage limits
• Microsoft SQL Server—4 TB
• MySQL, MariaDB, PostgreSQL, Oracle—6 TB
• Aurora—64 TB
• Growing your database is a process
Selected Amazon RDS customers
Selected Amazon Aurora customers
Security
Amazon Virtual Private Cloud (Amazon VPC)
Securely control network configuration
Availability Zone
AWS Region
10.1.0.0/16
10.1.1.0/24
Manage connectivity
AWS Direct
Connect
VPN
Connection
VPC
Peering
Internet
Gateway
Routing
Rules
Security groups
Database IP firewall protection
Protocol Port Range Source
TCP 3306 172.31.0.0/16
TCP 3306 “Application
security group”
Corporate address admins
Application tier
Compliance
Singapore MTCS
27001/9001
27017/27018
MySQL and Oracle
• SOC 1, 2, and 3
• ISO 27001/9001
• ISO 27017/27018
• PCI DSS
• FedRamp
• HIPAA BAA
• UK government programs
• Singapore MTCS
Compliance
SQL Server and PostgreSQL
• SOC 1, 2, and 3
• ISO 27001/9001
• ISO 27017/27018
• PCI DSS
• UK government programs
• Singapore MTCS
SSL
Available for all six engines
Database traffic encryption
At-rest encryption
• DB instance storage
• Automated backups
• Read Replicas
• Snapshots
• Available for all six engines
• No additional cost
• Support compliance requirements
AWS KMS —RDS standard encryption
Two-tiered key hierarchy using envelope encryption
• Unique data key encrypts customer data
• AWS KMS master keys encrypt data keys
Benefits:
• Limits risk of compromised data key
• Better performance for encrypting large data
• Easier to manage small number of master keys
than millions of data keys
• Centralized access and audit of key activity
Data Key 1
Amazon
S3 Object
Amazon
EBS
Volume
Data Key 2 Data Key 3 Data Key 4
Custom
Application
Customer Master
Key(s)
Amazon
RDS
Instance
Your RDS Instance
+
Data key Encrypted data key
Encrypted
data
Master key(s) in
customer’s account
AWS KMS
1. RDS instance requests encryption key to use to encrypt data, passes reference to master key in account.
2. Client request authenticated based on permissions set on both the user and the key.
3. A Unique data encryption key is created and encrypted under the KMS master key.
4. Plaintext and encrypted data key returned to the client.
5. Plaintext data key used to encrypt data and then deleted when practical.
6. Encrypted data key is stored; It’s sent back to KMS when needed for data decryption.
How keys are used to protect your data
Enabling encryption
AWS Command Line Interface (AWS CLI)
aws rds create-db-instance --region us-west-2 --db-instance-identifier sg-cli-test 
--allocated-storage 20 --storage-encrypted 
--db-instance-class db.m4.large --engine mysql 
--master-username myawsuser --master-user-password myawsuser
aws rds create-db-instance --region us-west-2 --db-instance-identifier sg-cli-test1 
--allocated-storage 20 --storage-encrypted --kms-key-id xxxxxxxxxxxxxxxxxx 
--db-instance-class db.m4.large --engine mysql  --master-username myawsuser
--master-user-password myawsuser
Amazon RDS + AWS KMS useful hints
• You can only encrypt on new database creation
• Encryption cannot be removed
• Master and Read Replica must be encrypted
• Unencrypted snapshots cannot be restored to encrypted DB
• Aurora will allow this
• You can create encrypted copies of your unencrypted snapshots
• Cannot restore MySQL to Aurora or Aurora to MySQL
• Cannot copy snapshots or replicate DB across regions
IAM governed access
You can use AWS Identity and Access Management (IAM)
to control who can perform actions on RDS
Users and DBAApplications DBA and Ops
Your database RDS
Controlled with IAMControlled with database grants
Metrics and monitoring
Standard monitoring
Amazon CloudWatch
metrics for Amazon RDS
 CPU utilization
 Storage
 Memory
 Swap usage
 DB connections
 I/O (read and write)
 Latency (read and write)
 Throughput (read and write)
 Replica lag
 Many more
Amazon CloudWatch Alarms
 Similar to on-premises custom
monitoring tools
Enhanced Monitoring
Access to over 50 new CPU, memory, file system, and disk I/O metrics as
low as 1 second intervals
Event notifications
• Uses Amazon Simple Notification
Service (Amazon SNS) to notify
users when an event occurs
• 17 different event categories
(availability, backup, configuration
change, and so on)
High availability
Minimal deployment—single AZ
Availability Zone
AWS Region
10.1.0.0/16
10.1.1.0/24
Amazon Elastic Block Store
Volume
High availability—Multi-AZ
Availability Zone A
AWS Region
10.1.0.0/16
10.1.1.0/24
Availability Zone B
10.1.2.0/24
Replicated storage
Same instance
type as master
High availability—Multi-AZ to DNS
dbinstancename.1234567890.us-west-2.rds.amazonaws.com:3006
High availability—Amazon Aurora storage
• Storage volume automatically grows up to
64 TB
• Quorum system for read/write; latency
tolerant
• Peer-to-peer gossip replication to fill in
holes
• Continuous backup to Amazon S3 (built for
11 9s durability)
• Continuous monitoring of nodes and disks
for repair
• 10 GB segments as unit of repair or hotspot
rebalance
• Quorum membership changes do not stall
writes
AZ 1 AZ 2 AZ 3
Amazon S3
High availability—Aurora nodes
• Aurora cluster contains primary
node and up to 15 secondary
nodes
• Failing database nodes are
automatically detected and
replaced
• Failing database processes are
automatically detected and recycled
• Secondary nodes automatically
promoted on persistent outage, no
single point of failure
• Customer application can scale out
read traffic across secondary nodes
AZ 1 AZ 3AZ 2
Primary
Node
Primary
Node
Primary
Node
Primary
Node
Primary
Node
Secondary
Node
Primary
Node
Primary
Node
Secondary
Node
Aurora-DNS Failover
App
RunningFailure Detection DNS Propagation
Recovery Recovery
DB
Failure
MYSQL
App
Running
Failure Detection DNS Propagation
Recovery
DB
Failure
AURORA WITH MARIADB DRIVER
1 5 - 3 0 s e c
5 - 2 0 s e c
1 5 - 3 0 s e c
Driver benefits
Scaling on RDS
Read Replicas
Bring data close to your customer’s
applications in different regions
Relieve pressure on your master
node for supporting reads and
writes.
Promote a Read Replica to a
master for faster recovery in the
event of disaster
Read Replicas
Within a region
• MySQL
• MariaDB
• PostgreSQL
• Aurora
Cross-region
• MySQL
• MariaDB
• PostgreSQL
• Aurora
Read Replicas for Amazon Aurora
AZ 1
AZ 3AZ 2
Primary
Node
Primary
Node
Primary
Node
AZ 1
AZ 1
Primary
Node
Primary
Node
Read Replica
Node
AZ 1
Primary
Node
Primary
Node
Read Replica
Node
Read Replicas—Oracle and Microsoft SQL Server
Options
• Oracle GoldenGate
• Third-party replication products
• Snapshots
Scaling up—or down
• Handle higher load or lower usage
• Control costs
Scaling up—or down
Console
Scaling—single AZ
With single AZ deployment, the master takes an outage
dbinstancename.1234567890.us-west-2.rds.amazonaws.com:3006
Scaling—Multi-AZ
With Multi-AZ, the standby gets upgraded first
dbinstancename.1234567890.us-west-2.rds.amazonaws.com:3006
Scaling—automation
AWS CLI
Scheduled CLI—cron
aws rds modify-db-instance --db-instance-identifier sg-cli-test --db-instance-class
db.m4.large --apply-immediately
#Scale down at 8:00 PM on Friday
0 20 * * 5 /home/ec2-user/scripts/scale_down_rds.sh
#Scale up at 4:00 AM on Monday
0 4 * * 1 /home/ec2-user/scripts/scale_up_rds.sh
Scaling—automation
Scheduled—AWS Lambda
No server but still runs on a schedule!
import boto3
client=boto3.client('rds')
def lambda_handler(event, context):
response=client.modify_db_instance(DBInstanceIdentifier='sg-cli-test',
DBInstanceClass='db.m4.xlarge',
ApplyImmediately=True)
print response
Scaling—automation
Metrics-based scaling
• Amazon CloudWatch and AWS Lambda!
Scaling—automation
import boto3
import json
client=boto3.client('rds')
def lambda_handler(event, context):
message = event['Records'][0]['Sns']['Message']
parsed_message=json.loads(message)
db_instance=parsed_message['Trigger']['Dimensions'][0]['value']
print 'DB Instance: ' + db_instance
response=client.modify_db_instance(DBInstanceIdentifier=db_instance,
DBInstanceClass='db.m4.large',
ApplyImmediately=True)
print response
Backups and snapshots
Backups
MySQL, PostgreSQL, MariaDB, Oracle, SQL Server
• Scheduled daily backup of entire instance
• Archive database change logs
• 35 day retention for backups
• Multiple copies in each AZ where you have instances for a deployment
Aurora
• Automatic, continuous, incremental backups
• Point-in-time restore
• No impact on database performance
• 35 day retention
Restoring
• Restoring creates an entire new database instance
• You define all the instance configuration just like a new
instance
Snapshots
• Full copies of your Amazon RDS database that are
different from your scheduled backups
• Backed by Amazon S3
• Used to create a new RDS instance
• Remain encrypted if using encryption
Snapshots
Use cases
• Resolve production issues
• Nonproduction environments
• Point-in-time restore
• Final copy before terminating a database
• Disaster recovery
• Cross-region copy
• Copy between accounts
Migrating onto RDS
 Move data to the same or different database engine
 Keep your apps running during the migration
 Start your first migration in 10 minutes or less
 Replicate within, to, or from Amazon EC2 or RDS
AWS Database
Migration Service
Migrate from Oracle and SQL Server
Move your tables, views, stored procedures,
and data manipulation language (DML) to
MySQL, MariaDB, and Amazon Aurora
Highlight where manual edits are needed
AWS Schema
Conversion Tool
Thank you!

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Deep Dive on Amazon Relational Database Service

  • 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. July 13, 2016 Deep Dive on Amazon Relational Database Service Scott Ward, Solutions Architect
  • 2. What to expect • Amazon RDS overview (super quick) • Security • Metrics and monitoring • High availability • Scaling on RDS • Backups and snapshots • Migrating to RDS
  • 3. No infrastructure management Scale up/down Cost-effective Instant provisioning Application compatibility Amazon Relational Database Service (Amazon RDS)
  • 4. Amazon RDS engines Commercial Open source Amazon Aurora
  • 5. Trade-offs with a managed service Fully managed host and OS • No access to the database host operating system • Limited ability to modify configuration that is managed on the host operating system • No functions that rely on configuration from the host OS Fully managed storage • Max storage limits • Microsoft SQL Server—4 TB • MySQL, MariaDB, PostgreSQL, Oracle—6 TB • Aurora—64 TB • Growing your database is a process
  • 9. Amazon Virtual Private Cloud (Amazon VPC) Securely control network configuration Availability Zone AWS Region 10.1.0.0/16 10.1.1.0/24 Manage connectivity AWS Direct Connect VPN Connection VPC Peering Internet Gateway Routing Rules
  • 10. Security groups Database IP firewall protection Protocol Port Range Source TCP 3306 172.31.0.0/16 TCP 3306 “Application security group” Corporate address admins Application tier
  • 12. MySQL and Oracle • SOC 1, 2, and 3 • ISO 27001/9001 • ISO 27017/27018 • PCI DSS • FedRamp • HIPAA BAA • UK government programs • Singapore MTCS Compliance SQL Server and PostgreSQL • SOC 1, 2, and 3 • ISO 27001/9001 • ISO 27017/27018 • PCI DSS • UK government programs • Singapore MTCS
  • 13. SSL Available for all six engines Database traffic encryption
  • 14. At-rest encryption • DB instance storage • Automated backups • Read Replicas • Snapshots • Available for all six engines • No additional cost • Support compliance requirements
  • 15. AWS KMS —RDS standard encryption Two-tiered key hierarchy using envelope encryption • Unique data key encrypts customer data • AWS KMS master keys encrypt data keys Benefits: • Limits risk of compromised data key • Better performance for encrypting large data • Easier to manage small number of master keys than millions of data keys • Centralized access and audit of key activity Data Key 1 Amazon S3 Object Amazon EBS Volume Data Key 2 Data Key 3 Data Key 4 Custom Application Customer Master Key(s) Amazon RDS Instance
  • 16. Your RDS Instance + Data key Encrypted data key Encrypted data Master key(s) in customer’s account AWS KMS 1. RDS instance requests encryption key to use to encrypt data, passes reference to master key in account. 2. Client request authenticated based on permissions set on both the user and the key. 3. A Unique data encryption key is created and encrypted under the KMS master key. 4. Plaintext and encrypted data key returned to the client. 5. Plaintext data key used to encrypt data and then deleted when practical. 6. Encrypted data key is stored; It’s sent back to KMS when needed for data decryption. How keys are used to protect your data
  • 17. Enabling encryption AWS Command Line Interface (AWS CLI) aws rds create-db-instance --region us-west-2 --db-instance-identifier sg-cli-test --allocated-storage 20 --storage-encrypted --db-instance-class db.m4.large --engine mysql --master-username myawsuser --master-user-password myawsuser aws rds create-db-instance --region us-west-2 --db-instance-identifier sg-cli-test1 --allocated-storage 20 --storage-encrypted --kms-key-id xxxxxxxxxxxxxxxxxx --db-instance-class db.m4.large --engine mysql --master-username myawsuser --master-user-password myawsuser
  • 18. Amazon RDS + AWS KMS useful hints • You can only encrypt on new database creation • Encryption cannot be removed • Master and Read Replica must be encrypted • Unencrypted snapshots cannot be restored to encrypted DB • Aurora will allow this • You can create encrypted copies of your unencrypted snapshots • Cannot restore MySQL to Aurora or Aurora to MySQL • Cannot copy snapshots or replicate DB across regions
  • 19. IAM governed access You can use AWS Identity and Access Management (IAM) to control who can perform actions on RDS Users and DBAApplications DBA and Ops Your database RDS Controlled with IAMControlled with database grants
  • 21. Standard monitoring Amazon CloudWatch metrics for Amazon RDS  CPU utilization  Storage  Memory  Swap usage  DB connections  I/O (read and write)  Latency (read and write)  Throughput (read and write)  Replica lag  Many more Amazon CloudWatch Alarms  Similar to on-premises custom monitoring tools
  • 22. Enhanced Monitoring Access to over 50 new CPU, memory, file system, and disk I/O metrics as low as 1 second intervals
  • 23. Event notifications • Uses Amazon Simple Notification Service (Amazon SNS) to notify users when an event occurs • 17 different event categories (availability, backup, configuration change, and so on)
  • 25. Minimal deployment—single AZ Availability Zone AWS Region 10.1.0.0/16 10.1.1.0/24 Amazon Elastic Block Store Volume
  • 26. High availability—Multi-AZ Availability Zone A AWS Region 10.1.0.0/16 10.1.1.0/24 Availability Zone B 10.1.2.0/24 Replicated storage Same instance type as master
  • 27. High availability—Multi-AZ to DNS dbinstancename.1234567890.us-west-2.rds.amazonaws.com:3006
  • 28. High availability—Amazon Aurora storage • Storage volume automatically grows up to 64 TB • Quorum system for read/write; latency tolerant • Peer-to-peer gossip replication to fill in holes • Continuous backup to Amazon S3 (built for 11 9s durability) • Continuous monitoring of nodes and disks for repair • 10 GB segments as unit of repair or hotspot rebalance • Quorum membership changes do not stall writes AZ 1 AZ 2 AZ 3 Amazon S3
  • 29. High availability—Aurora nodes • Aurora cluster contains primary node and up to 15 secondary nodes • Failing database nodes are automatically detected and replaced • Failing database processes are automatically detected and recycled • Secondary nodes automatically promoted on persistent outage, no single point of failure • Customer application can scale out read traffic across secondary nodes AZ 1 AZ 3AZ 2 Primary Node Primary Node Primary Node Primary Node Primary Node Secondary Node Primary Node Primary Node Secondary Node
  • 30. Aurora-DNS Failover App RunningFailure Detection DNS Propagation Recovery Recovery DB Failure MYSQL App Running Failure Detection DNS Propagation Recovery DB Failure AURORA WITH MARIADB DRIVER 1 5 - 3 0 s e c 5 - 2 0 s e c 1 5 - 3 0 s e c Driver benefits
  • 32. Read Replicas Bring data close to your customer’s applications in different regions Relieve pressure on your master node for supporting reads and writes. Promote a Read Replica to a master for faster recovery in the event of disaster
  • 33. Read Replicas Within a region • MySQL • MariaDB • PostgreSQL • Aurora Cross-region • MySQL • MariaDB • PostgreSQL • Aurora
  • 34. Read Replicas for Amazon Aurora AZ 1 AZ 3AZ 2 Primary Node Primary Node Primary Node AZ 1 AZ 1 Primary Node Primary Node Read Replica Node AZ 1 Primary Node Primary Node Read Replica Node
  • 35. Read Replicas—Oracle and Microsoft SQL Server Options • Oracle GoldenGate • Third-party replication products • Snapshots
  • 36. Scaling up—or down • Handle higher load or lower usage • Control costs
  • 38. Scaling—single AZ With single AZ deployment, the master takes an outage dbinstancename.1234567890.us-west-2.rds.amazonaws.com:3006
  • 39. Scaling—Multi-AZ With Multi-AZ, the standby gets upgraded first dbinstancename.1234567890.us-west-2.rds.amazonaws.com:3006
  • 40. Scaling—automation AWS CLI Scheduled CLI—cron aws rds modify-db-instance --db-instance-identifier sg-cli-test --db-instance-class db.m4.large --apply-immediately #Scale down at 8:00 PM on Friday 0 20 * * 5 /home/ec2-user/scripts/scale_down_rds.sh #Scale up at 4:00 AM on Monday 0 4 * * 1 /home/ec2-user/scripts/scale_up_rds.sh
  • 41. Scaling—automation Scheduled—AWS Lambda No server but still runs on a schedule! import boto3 client=boto3.client('rds') def lambda_handler(event, context): response=client.modify_db_instance(DBInstanceIdentifier='sg-cli-test', DBInstanceClass='db.m4.xlarge', ApplyImmediately=True) print response
  • 43. Scaling—automation import boto3 import json client=boto3.client('rds') def lambda_handler(event, context): message = event['Records'][0]['Sns']['Message'] parsed_message=json.loads(message) db_instance=parsed_message['Trigger']['Dimensions'][0]['value'] print 'DB Instance: ' + db_instance response=client.modify_db_instance(DBInstanceIdentifier=db_instance, DBInstanceClass='db.m4.large', ApplyImmediately=True) print response
  • 45. Backups MySQL, PostgreSQL, MariaDB, Oracle, SQL Server • Scheduled daily backup of entire instance • Archive database change logs • 35 day retention for backups • Multiple copies in each AZ where you have instances for a deployment Aurora • Automatic, continuous, incremental backups • Point-in-time restore • No impact on database performance • 35 day retention
  • 46. Restoring • Restoring creates an entire new database instance • You define all the instance configuration just like a new instance
  • 47. Snapshots • Full copies of your Amazon RDS database that are different from your scheduled backups • Backed by Amazon S3 • Used to create a new RDS instance • Remain encrypted if using encryption
  • 48. Snapshots Use cases • Resolve production issues • Nonproduction environments • Point-in-time restore • Final copy before terminating a database • Disaster recovery • Cross-region copy • Copy between accounts
  • 50.  Move data to the same or different database engine  Keep your apps running during the migration  Start your first migration in 10 minutes or less  Replicate within, to, or from Amazon EC2 or RDS AWS Database Migration Service
  • 51. Migrate from Oracle and SQL Server Move your tables, views, stored procedures, and data manipulation language (DML) to MySQL, MariaDB, and Amazon Aurora Highlight where manual edits are needed AWS Schema Conversion Tool