AWS RDS DB Maintenance & Upgrades

RDS DB Instance Maintenance and Upgrades

Changes to a DB instance can occur when a DB instance is manually modified for e.g. DB engine version is upgraded, or when Amazon RDS performs maintenance on an instance

Amazon RDS Maintenance

  • Periodically, Amazon RDS performs maintenance on Amazon RDS resources, such as DB instances and most often involves updates to the DB instance’s operating system (OS).
  • Maintenance items can either
    • be applied manually on a DB instance at ones convenience
    • or wait for the automatic maintenance process initiated by Amazon RDS during the defined weekly maintenance window.
  • Maintenance window only determines when pending operations start, but does not limit the total execution time of these operations. Maintenance operations are not guaranteed to finish before the maintenance window ends, and can continue beyond the specified end time.
  • Maintenance update availability can be checked both on the RDS console and by using the RDS API. And if an update is available, one can
    • Defer the maintenance items.
    • Apply the maintenance items immediately.
    • Schedule them to start during the next defined maintenance window
  • Maintenance items marked as
    • Required cannot be deferred indefinitely, if deferred AWS will send a notify the time when the update will be performed next
    • Available and can be deferred indefinitely and the update will not be applied to the DB instance.
  • Required patching is automatically scheduled only for patches that are related to security and instance reliability. Such patching occurs infrequently (typically once every few months) and seldom requires more than a fraction of your maintenance window.
  • Maintenance items require that RDS take your DB instance offline for a short time. Maintenance that requires DB instance to be offline include scale compute operations, which generally take only a few minutes from start to finish, and required operating system or database patching.
  • Multi-AZ deployment for the DB instance reduces the impact of a maintenance event by following these steps:
    • Perform maintenance on the standby.
    • Promote the standby to primary.
    • Perform maintenance on the old primary, which becomes the new standby.
  • When database engine for the DB instance is modified in a Multi-AZ deployment, RDS upgrades both the primary and secondary DB instances at the same time. In this case, the database engine for the entire Multi-AZ deployment is shut down during the upgrade.

Operating System Updates

  • Upgrades to the operating system are most often for security issues and should be done as soon as possible.
  • OS updates on a DB instance can be applied at ones convenience or can wait for the maintenance process initiated by RDS to apply the update during the defined maintenance window
  • DB instance is not automatically backed up when an OS update is applied, and should be backup up before the update is applied

Database Engine Version Upgrade

  • DB instance engine version can be upgraded when a new DB engine version is supported by RDS.
  • Database version upgrades consist of major and minor version upgrades.
    • Major database version upgrades
      • can contain changes that are not backward-compatible
      • RDS doesn’t apply major version upgrades automatically
      • DB instance should be manually modified and thoroughly tested before applying it to the production instances.
    • Minor version upgrades
      • Each DB engine handles minor version upgrade slightly differently
        for e.g. RDS automatically apply minor version upgrades to a DB instance running PostgreSQL, but must be manually applied to a DB instance running Oracle.
  • Amazon posts an announcement to the forums announcement page and sends a customer e-mail notification before upgrading an DB instance
  • Amazon schedule the upgrades at specific times through the year, to help plan around them, because downtime is required to upgrade a DB engine version, even for Multi-AZ instances.
  • RDS takes two DB snapshots during the upgrade process.
    • First DB snapshot is of the DB instance before any upgrade changes have been made. If the upgrade fails, it can be restored from the snapshot to create a DB instance running the old version.
    • Second DB snapshot is taken when the upgrade completes. After the upgrade is complete, database engine can’t be reverted to the previous version. For returning to the previous version, restore the first DB snapshot taken to create a new DB instance.
  • If the DB instance is using read replication, all of the Read Replicas must be upgraded before upgrading the source instance.
  • If the DB instance is in a Multi-AZ deployment, both the primary and standby replicas are upgraded at the same time and would result in an outage. The time for the outage varies based on your database engine, version, and the size of your DB instance.

RDS Maintenance Window

  • Every DB instance has a weekly maintenance window defined during which any system changes are applied.
  • Maintenance window is an opportunity to control when DB instance modifications and software patching occur, in the event either are requested or required.
  • If a maintenance event is scheduled for a given week, it will be initiated during the 30 minute maintenance window as defined
  • Maintenance events mostly complete during the 30 minute maintenance window, although larger maintenance events may take more time
  • 30-minute maintenance window is selected at random from an 8-hour block of time per region. If you don’t specify a preferred maintenance window when you create the DB instance, Amazon RDS assigns a 30-minute maintenance window on a randomly selected day of the week.
  • RDS will consume some of the resources on the DB instance while maintenance is being applied, minimally effecting performance.
  • For some maintenance events, a Multi-AZ failover may be required for a maintenance update to complete.
  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. A user has launched an RDS MySQL DB with the Multi AZ feature. The user has scheduled the scaling of instance storage during maintenance window. What is the correct order of events during maintenance window? 1. Perform maintenance on standby 2. Promote standby to primary 3. Perform maintenance on original primary 4. Promote original master back as primary
    1. 1, 2, 3, 4
    2. 1, 2, 3
    3. 2, 3, 4, 1
  2. Can I control if and when MySQL based RDS Instance is upgraded to new supported versions?
    1. No
    2. Only in VPC
    3. Yes
  3. A user has scheduled the maintenance window of an RDS DB on Monday at 3 AM. Which of the below mentioned events may force to take the DB instance offline during the maintenance window?
    1. Enabling Read Replica
    2. Making the DB Multi AZ
    3. DB password change
    4. Security patching
  4. A user has launched an RDS postgreSQL DB with AWS. The user did not specify the maintenance window during creation. The user has configured RDS to update the DB instance type from micro to large. If the user wants to have it during the maintenance window, what will AWS do?
    1. AWS will not allow to update the DB until the maintenance window is configured
    2. AWS will select the default maintenance window if the user has not provided it
    3. AWS will ask the user to specify the maintenance window during the update
    4. It is not possible to change the DB size from micro to large with RDS
  5. Can I test my DB Instance against a new version before upgrading?
    1. No
    2. Yes
    3. Only in VPC


AWS RDS Storage – Certification

AWS RDS Storage

  • RDS storage uses Elastic Block Store (EBS) volumes for database and log storage.
  • RDS automatically stripes across multiple EBS volumes to enhance IOPS performance, depending on the amount of storage requested

RDS Storage Types

  • RDS storage provides three storage types: Magnetic, General Purpose (SSD), and Provisioned IOPS (input/output operations per second).
  • These storage types differ in performance characteristics and price, which allows tailoring of storage performance and cost to the database needs
  • MySQL, MariaDB, PostgreSQL, and Oracle RDS DB instances can be created with up to 6TB of storage and SQL Server RDS DB instances with up to 4TB of storage when using the Provisioned IOPS and General Purpose (SSD)
    storage types.
  • Existing MySQL, PostgreSQL, and Oracle RDS database instances can be scaled to these new database storage limits without any downtime.

Magnetic (Standard)

  • Magnetic storage, also called standard storage, offers cost-effective storage that is ideal for applications with light or burst I/O requirements.
  • They deliver approximately 100 IOPS on average, with burst capability of up to hundreds of IOPS, and they can range in size from 5 GB to 3 TB, depending on the DB instance engine.
  • Magnetic storage is not reserved for a single DB instance, so performance can vary greatly depending on the demands placed on shared resources by other customers.

General Purpose (SSD)

  • General purpose, SSD-backed storage, also called gp2, can provide faster access than disk-based storage.
  • They can deliver single-digit millisecond latencies, with a base performance of 3 IOPS per Gigabyte (GB) and the ability to burst to 3,000 IOPS for extended periods of time up to a maximum of 10,000 PIOPS.
  • Gp2 volumes can range in size from 5 GB to 6 TB for MySQL, MariaDB, PostgreSQL, and Oracle DB instances, and from 20 GB to 4 TB for SQL Server DB instances.
  • Gp2 is excellent for small to medium-sized databases.

Provisioned IOPS

  • Provisioned IOPS storage is designed to meet the needs of I/O-intensive workloads, particularly database workloads, that are sensitive to storage performance and consistency in random access I/O throughput.
  • Provisioned IOPS storage is a storage type that delivers fast, predictable, and consistent throughput performance.
  • For any production application that requires fast and consistent I/O performance, Amazon recommends Provisioned IOPS (input/output operations per second) storage.
  • Provisioned IOPS storage is optimized for I/O intensive, online transaction processing (OLTP) workloads that have consistent performance requirements.
  • Provisioned IOPS helps performance tuning.
  • Provisioned IOPS volumes can range in size from 100 GB to 6 TB for MySQL, MariaDB, PostgreSQL, and Oracle DB engines. SQL Server Express and Web editions can range in size from 100 GB to 4 TB, while SQL Server Standard and Enterprise editions can range in size from 200 GB to 4 TB.
  • Dedicated IOPS rate and storage space allocation is specified, when a DB instance is created. RDS provisions that IOPS rate and storage for the lifetime of the DB instance or until its changed.
  • RDS delivers within 10 percent of the provisioned IOPS performance 99.9 percent of the time over a given year.

For detailed explanation on refer post @ EBS volume Types

Adding Storage and Changing Storage Type

  • DB instance can be modified to use additional storage and converted to a different storage type.
  • However, storage allocated for a DB instance cannot be decreased
  • MySQL, MariaDB, PostgreSQL, and Oracle DB instances can be scaled up for storage, which helps improve I/O capacity.
  • Storage capacity nor the type of storage for a SQL Server DB instance can be changed due to extensibility limitations of striped storage attached to a Windows Server environment.
  • During the scaling process, the DB instance will be available for reads and writes, but may experience performance degradation
  • Adding storage may take several hours; the duration of the process depends on several factors such as load, storage size, storage type, amount of IOPS provisioned (if any), and number of prior scale storage operations.
  • While storage is being added, nightly backups are suspended and no other RDS operations can take place, including modify, reboot, delete, create Read Replica, and create DB Snapshot

Performance Metrics

  • Amazon RDS provides several metrics that can be used to determine how the DB instance is performing.
    • IOPS
      • the number of I/O operations completed per second.
      • it is reported as the average IOPS for a given time interval.
      • RDS reports read and write IOPS separately on one minute intervals.
      • Total IOPS is the sum of the read and write IOPS.
      • Typical values for IOPS range from zero to tens of thousands per second.
    • Latency
      • the elapsed time between the submission of an I/O request and its completion
      • it is reported as the average latency for a given time interval.
      • RDS reports read and write latency separately on one minute intervals in units of seconds.
      • Typical values for latency are in the millisecond (ms)
    • Throughput
      • the number of bytes per second transferred to or from disk
      • it is reported as the average throughput for a given time interval.
      • RDS reports read and write throughput separately on one minute intervals using units of megabytes per second (MB/s).
      • Typical values for throughput range from zero to the I/O channel’s maximum bandwidth.
    • Queue Depth
      • the number of I/O requests in the queue waiting to be serviced.
      • these are I/O requests that have been submitted by the application but have not been sent to the device because the device is busy servicing other I/O requests.
      • it is reported as the average queue depth for a given time interval.
      • RDS reports queue depth in one minute intervals. Typical values for queue depth range from zero to several hundred.
      • Time spent waiting in the queue is a component of Latency and
        Service Time (not available as a metric).

Amazon RDS Storage Facts

  • First time a DB instance is started and accesses an area of disk for the first time, the process can take longer than all subsequent accesses to the same disk area. This is known as the “first touch penalty”. Once an area of disk has incurred the first touch penalty, that area of disk does not incur the penalty again for the life of the instance, even if the DB instance is rebooted, restarted, or the DB instance class changes. Note that a DB instance created from a snapshot, a point-in-time restore, or a read replica is a new instance and does incur this first touch penalty.
  • RDS manages the DB instance and it reserves overhead space on the instance. While the amount of reserved storage varies by DB instance class and other factors, this reserved space can be as much as one or two percent of the total storage
  • Provisioned IOPS provides a way to reserve I/O capacity by specifying IOPS. Like any other system capacity attribute, maximum throughput under load will be constrained by the resource that is consumed first, which could be IOPS, channel bandwidth, CPU, memory, or database internal resources.
  • Current maximum channel bandwidth available is 4000 megabits per second (Mbps) full duplex. In terms of the read and write throughput metrics, this equates to about 210 megabytes per second (MB/s) in each direction. A perfectly balanced workload of 50% reads and 50% writes may attain a maximum combined throughput of 420 MB/s, which includes protocol overhead, so the actual data throughput may be less.
  • Provisioned IOPS works with an I/O request size of 32 KB. Provisioned IOPS consumption is a linear function of I/O request size above 32 KB. An I/O request smaller than 32 KB is handled as one I/O; for e.g. 1000 16 KB I/O requests are treated the same as 1000 32 KB requests. I/O requests larger than 32 KB consume more than one I/O request; while, a 48 KB I/O request consumes 1.5 I/O requests of storage capacity; a 64 KB I/O request consumes 2 I/O requests

Factors That Impact Storage Performance

  • Several factors can affect the performance of a DB instance, such as instance configuration, I/O characteristics, and workload demand.
  • System related activities also consume I/O capacity and may reduce database instance performance while in progress:
    • DB snapshot creation
    • Nightly backups
    • Multi-AZ peer creation
    • Read replica creation
    • Scaling storage
  • System resources can constrain the throughput of a DB instance, but there can be other reasons for a bottleneck. Database could be the issue if :-
    • Channel throughput limit is not reached
    • Queue depths are consistently low
    • CPU utilization is under 80%
    • Free memory available
    • No swap activity
    • Plenty of free disk space
    • Application has dozens of threads all submitting transactions as fast as the database will take them, but there is clearly unused I/O capacity

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AWS Certification Exam Practice Questions

  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. When should I choose Provisioned IOPS over Standard RDS storage?
    1. If you have batch-oriented workloads
    2. If you use production online transaction processing (OLTP) workloads
    3. If you have workloads that are not sensitive to consistent performance
  2. Is decreasing the storage size of a DB Instance permitted?
    1. Depends on the RDMS used
    2. Yes
    3. No
  3. Because of the extensibility limitations of striped storage attached to Windows Server, Amazon RDS does not currently support increasing storage on a _____ DB Instance.
    1. SQL Server
    2. MySQL
    3. Oracle
  4. If I want to run a database in an Amazon instance, which is the most recommended Amazon storage option?
    1. Amazon Instance Storage
    2. Amazon EBS
    3. You can’t run a database inside an Amazon instance.
    4. Amazon S3
  5. For each DB Instance class, what is the maximum size of associated storage capacity?
    1. 1TiB
    2. 2TiB
    3. 8TiB
    4. 16TiB (The limit keeps on changing so please check the latest always)


AWS Storage Options – RDS, DynamoDB & Database on EC2

AWS Storage Options Whitepaper with RDS, DynamoDB & Database on EC2 Cont.

Provides a brief summary for the Ideal Use cases, Anti-Patterns and other factors for Amazon RDS, DynamoDB & Databases on EC2 storage options

Amazon RDS

  • RDS is a web service that provides the capabilities of MySQL, Oracle, MariaDB, Postgres or Microsoft SQL Server relational database as a managed, cloud-based service
  • RDS eliminates much of the administrative overhead associated with launching, managing, and scaling your own relational database on Amazon EC2 or in another computing environment.

Ideal Usage Patterns

  • RDS is a great solution for cloud-based fully-managed relational database
  • RDS is also optimal for new applications with structured data that requires more sophisticated querying and joining capabilities than that provided by Amazon’s NoSQL database offering, DynamoDB.
  • RDS provides full compatibility with the databases supported and direct access to native database engines, code and libraries and is ideal for existing applications that rely on these databases


  • Index and query-focused data
    • If the applications don’t require advanced features such as joins and complex transactions and is more oriented toward indexing and querying data, DynamoDB would be more appropriate for this needs
  • Numerous BLOBs
    • If the application makes heavy use of files (audio files, videos, images, etc), it is a better choice to use S3 to store the objects instead of database engines Blob feature and use RDS or DynamoDB only to save the metadata
  • Automated scalability
    • RDS provides pushbutton scaling and it only scales up and has limited scale out ability. If fully-automated scaling is needed, DynamoDB may be a better choice.
  • Complete control
    • RDS does not provide admin access and does not enable the full feature set of the database engines.
    • So if the application requires complete, OS-level control of the database server with full root or admin login privileges, a self-managed database on EC2 may be a better match.
  • Other database platforms
    • RDS, at this time, provides a MySQL, Oracle, MariaDB, PostgreSQL and SQL Server databases.
    • If any other database platform (such as IBM DB2, Informix, or Sybase) is needed, it should be deployed on a self-managed database on an EC2 instance by using a relational database AMI, or by installing database software on an EC2 instance.


  • RDS Provisioned IOPS, where the IOPS can be specified when the instance is launched and is guaranteed over the life of the instance, provides a high-performance storage option designed to deliver fast, predictable, and consistent performance for I/O intensive transactional database workload

Durability and Availability

  • RDS leverages Amazon EBS volumes as its data store
  • RDS provides database backups, for enhanced durability, which are replicated across multiple AZ’s
    • Automated backups
      • If enabled, RDS will automatically perform a full daily backup of your data during the specified backup window, and will also capture DB transaction logs
    • User initiated backups
      • User can initiate backups at time and they are not deleted unless deleted explicitly by the user
  • RDS Multi AZ’s feature enhances both the durability and the availability of the database by synchronously replicating the data between a primary RDS DB instance and a standby instance in another Availability Zone, which prevents data loss,
  • RDS provides a DNS endpoint and in case of an failure on the primary, it automatically fails over to the standby instance
  • RDS also allows Read replicas for the supported databases, which are replicated asynchronously

Cost Model

  • RDS offers a tiered pricing structure, based on the size of the database instance, the deployment type (Single-AZ/Multi-AZ), and the AWS region.
  • Pricing for RDS is based on several factors: the DB instance hours (per hour), the amount of provisioned database storage (per GB-month and per million I/O requests), additional backup storage (per GB-month), and data transfer in/out (per GB per month)

Scalability and Elasticity

  • RDS resources can be scaled elastically in several dimensions: database storage size, database storage IOPS rate, database instance compute capacity, and the number of read replicas
  • RDS supports “pushbutton scaling” of both database storage and compute resources. Additional storage can either be added immediately or during the next maintenance cycle
  • RDS for MySQL also enables you to scale out beyond the capacity of a single database deployment for read-heavy database workloads by creating one or more read replicas.
  • Multiple RDS instances can also be configured to leverage database partitioning or sharding to spread the workload over multiple DB instances, achieving even greater database scalability and elasticity.


  • RDS APIs and the AWS Management Console provide a management interface that allows you to create, delete, modify, and terminate RDS DB instances; to create DB snapshots; and to perform point-in-time restores
  • There is no AWS data API for Amazon RDS.
  • Once a database is created, RDS provides a DNS endpoint for the database which can be used to connect to the database.
  • Endpoint does not change over the lifetime of the instance even during the failover in case of Multi-AZ configuration

Amazon DynamoDB

  • Amazon DynamoDB is a fast, fully-managed NoSQL database service that makes it simple and cost-effective to store and retrieve any amount of data, and serve any level of request traffic.
  • DynamoDB being a managed service helps offload the administrative burden of operating and scaling a highly-available distributed database cluster.
  • DynamoDB helps meet the latency and throughput requirements of highly demanding applications by providing extremely fast and predictable performance with seamless throughput and storage scalability.
  • DynamoDB provides both eventually-consistent reads (by default), and strongly-consistent reads (optional), as well as implicit item-level transactions for item put, update, delete, conditional operations, and increment/decrement.
  • Amazon DynamoDB handles the data as below :-
    • DynamoDB stores structured data in tables, indexed by primary key, and allows low-latency read and write access to items.
    • DynamoDB supports three data types: number, string, and binary, in both scalar and multi-valued sets.
    • Tables do not have a fixed schema, so each data item can have a different number of attributes.
    • Primary key can either be a single-attribute hash key or a composite hash-range key.
    • Local secondary indexes provide additional flexibility for querying against attributes other than the primary key.

Ideal Usage Patterns

  • DynamoDB is ideal for existing or new applications that need a flexible NoSQL database with low read and write latencies, and the ability to scale storage and throughput up or down as needed without code changes or downtime.
  • Use cases require a highly available and scalable database because downtime or performance degradation has an immediate negative impact on an organization’s business. for e.g. mobile apps, gaming, digital ad serving, live voting and audience interaction for live events, sensor networks, log ingestion, access control for web-based content, metadata storage for S3 objects, e-commerce shopping carts, and web session management


  • Structured data with Join and/or Complex Transactions
    • If the application uses structured data and required joins, complex transactions or other relationship infrastructure provided by traditional database platforms, it is better to use RDS or Database installed on an EC2 instance
  • Large Blob data
    • If the application uses large blob data for e.g. media, files, videos etc., it is better to use S3 to store the objects and use DynamoDB to store metadata for e.g. name, size, content-type etc
  • Large Objects with Low I/O rate
    • DynamoDB uses SSD drives and is optimized for workloads with a high I/O rate per GB stored. If the applications stores very large amounts of data that are infrequently accessed, S3 might be a better choice
  • Prewritten application with databases
    • For Porting an existing application using databases, RDS or database installed on the EC2 instance would be a better and seamless solution


  • SSDs and limited indexing on attributes provides high throughput and low latency and drastically reduces the cost of read and write operations.
  • Predictable performance can be achieved by defining the provisioned throughput capacity required for a given table.
  • DynamoDB handles the provisioning of resources to achieve the requested throughput rate, taking away the burden to think about instances, hardware, memory, and other factors that can affect an application’s throughput rate.
  • Provisioned throughput capacity reservations are elastic and can be increased or decreased on demand.

Durability and Availability

  • DynamoDB has built-in fault tolerance that automatically and synchronously replicates data across three AZ’s in a region for high availability and to help protect data against individual machine, or even facility failures.

Cost Model

  • DynamoDB has three pricing components: provisioned throughput capacity (per hour), indexed data storage (per GB per month), data transfer in or out (per GB per month)

Scalability and Elasticity

  • DynamoDB is both highly-scalable and elastic.
  • DynamoDB provides unlimited storage capacity, and the service automatically allocates more storage as the demand increases
  • Data is automatically partitioned and re-partitioned as needed, while the use of SSDs provides predictable low-latency response times at any scale.
  • DynamoDB is also elastic, in that you can simply “dial-up” or “dial-down” the read and write capacity of a table as your needs change.


  • DynamoDB provides a low-level REST API, as well as higher-level SDKs in different languages
  • APIs provide both a management and data interface for Amazon DynamoDB, that enable table management (creating, listing, deleting, and obtaining metadata) and working with attributes (getting, writing, and deleting attributes; query using an index, and full scan).

Databases on EC2

  • EC2 with EBS volumes allows hosting a self managed relational database
  • Ready to use, prebuilt AMIs are also available from leading database solutions

Ideal Usage Patterns

  • Self managed database on EC2 is an ideal scenario for users whose application requires a specific traditional relational database not supported by Amazon RDS for e.g. IBM DB2, Informix, or Sybase
  • Users or applications that require a maximum level of administrative control and configurability which is not provided by RDS


  • Index and query-focused data
    • If the applications don’t require advanced features such as joins and complex transactions and is more oriented toward indexing and querying data, DynamoDB would be more appropriate for this needs
  • Numerous BLOBs
    • If the application makes heavy use of files (audio files, videos, images, and so on), it is a better choice to use S3 to store the objects instead of database engines Blob feature and use RDS or DynamoDB only to save the metadata
  • Automated scalability
    • Relational databases on EC2 leverages the scalability and elasticity of the underlying AWS platform, but this requires system administrators or DBAs to perform a manual or scripted task. If you need pushbutton scaling or fully-automated scaling, DynamoDB or RDS may be a better choice.
  • RDS supported database platforms
    • If the application using RDS supported database engine and all the features are available, RDS would be a better choice instead of self managed relational database on EC2


  • Performance depends on the size of the underlying EC2 instance, the number and configuration of the EBS volumes and the database itself
  • Performance can be increased by scaling up memory and compute resources by choosing a larger Amazon EC2 instance size.
  • For database storage, it is usually best to use EBS Provisioned IOPS volumes. To scale up I/O performance, the Provisioned IOPS can be increased, the number of EBS volumes changed, or use software RAID 0 (disk striping) across multiple EBS volumes, which will aggregate total IOPS and bandwidth.

Durability & Availability

  • As the database on EC2 uses EBS as storage, it has the same durability and availability provided by EBS and can be further enhanced by using EBS snapshots or by using third-party database backup utilities (such as Oracle’s RMAN) to store database backups in Amazon S3

Cost Model

  • Cost for running a database on EC2 instance is mainly determined by the size and the number of EC2 instance running, the size of the EBS volume used for database storage and any third party licensing cost for the database

Scalability & Elasticity

  • Users of traditional relational database solutions on Amazon EC2 can take advantage of the scalability and elasticity of the underlying AWS platform by creating AMI and spawning multiple instances

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AWS Certification Exam Practice Questions

  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. Which of the following are use cases for Amazon DynamoDB? Choose 3 answers
    1. Storing BLOB data.
    2. Managing web sessions
    3. Storing JSON documents
    4. Storing metadata for Amazon S3 objects
    5. Running relational joins and complex updates.
    6. Storing large amounts of infrequently accessed data.
  2. A client application requires operating system privileges on a relational database server. What is an appropriate configuration for highly available database architecture?
    1. A standalone Amazon EC2 instance
    2. Amazon RDS in a Multi-AZ configuration
    3. Amazon EC2 instances in a replication configuration utilizing a single Availability Zone
    4. Amazon EC2 instances in a replication configuration utilizing two different Availability Zones
  3. You are developing a new mobile application and are considering storing user preferences in AWS, which would provide a more uniform cross-device experience to users using multiple mobile devices to access the application. The preference data for each user is estimated to be 50KB in size. Additionally 5 million customers are expected to use the application on a regular basis. The solution needs to be cost-effective, highly available, scalable and secure, how would you design a solution to meet the above requirements?
    1. Setup an RDS MySQL instance in 2 availability zones to store the user preference data. Deploy a public facing application on a server in front of the database to manage security and access credentials
    2. Setup a DynamoDB table with an item for each user having the necessary attributes to hold the user preferences. The mobile application will query the user preferences directly from the DynamoDB table. Utilize STS. Web Identity Federation, and DynamoDB Fine Grained Access Control to authenticate and authorize access (DynamoDB provides high availability as it synchronously replicates data across three facilities within an AWS Region and scalability as it is designed to scale its provisioned throughput up or down while still remaining available. Also suitable for storing user preference data)
    3. Setup an RDS MySQL instance with multiple read replicas in 2 availability zones to store the user preference data .The mobile application will query the user preferences from the read replicas. Leverage the MySQL user management and access privilege system to manage security and access credentials.
    4. Store the user preference data in S3 Setup a DynamoDB table with an item for each user and an item attribute pointing to the user’ S3 object. The mobile application will retrieve the S3 URL from DynamoDB and then access the S3 object directly utilize STS, Web identity Federation, and S3 ACLs to authenticate and authorize access.
  4. A customer is running an application in US-West (Northern California) region and wants to setup disaster recovery failover to the Asian Pacific (Singapore) region. The customer is interested in achieving a low Recovery Point Objective (RPO) for an Amazon RDS multi-AZ MySQL database instance. Which approach is best suited to this need?
    1. Synchronous replication
    2. Asynchronous replication
    3. Route53 health checks
    4. Copying of RDS incremental snapshots
  5. You are designing a file -sharing service. This service will have millions of files in it. Revenue for the service will come from fees based on how much storage a user is using. You also want to store metadata on each file, such as title, description and whether the object is public or private. How do you achieve all of these goals in a way that is economical and can scale to millions of users?
    1. Store all files in Amazon Simple Storage Service (53). Create a bucket for each user. Store metadata in the filename of each object, and access it with LIST commands against the S3 API.
    2. Store all files in Amazon 53. Create Amazon DynamoDB tables for the corresponding key -value pairs on the associated metadata, when objects are uploaded.
    3. Create a striped set of 4000 IOPS Elastic Load Balancing volumes to store the data. Use a database running in Amazon Relational Database Service (RDS) to store the metadata.
    4. Create a striped set of 4000 IOPS Elastic Load Balancing volumes to store the data. Create Amazon DynamoDB tables for the corresponding key-value pairs on the associated metadata, when objects are uploaded.
  6. Company ABCD has recently launched an online commerce site for bicycles on AWS. They have a “Product” DynamoDB table that stores details for each bicycle, such as, manufacturer, color, price, quantity and size to display in the online store. Due to customer demand, they want to include an image for each bicycle along with the existing details. Which approach below provides the least impact to provisioned throughput on the “Product” table?
    1. Serialize the image and store it in multiple DynamoDB tables
    2. Create an “Images” DynamoDB table to store the Image with a foreign key constraint to the “Product” table
    3. Add an image data type to the “Product” table to store the images in binary format
    4. Store the images in Amazon S3 and add an S3 URL pointer to the “Product” table item for each image