AWS Certification – Database Services – Cheat Sheet

Relational Database Service – RDS

  • provides Relational Database service
  • supports MySQL, MariaDB, PostgreSQL, Oracle, Microsoft SQL Server, and the new, MySQL-compatible Amazon Aurora DB engine
  • as it is a managed service, shell (root ssh) access is not provided
  • manages backups, software patching, automatic failure detection, and recovery
  • supports use initiated manual backups and snapshots
  • daily automated backups with database transaction logs enables Point in Time recovery up to the last five minutes of database usage
  • snapshots are user-initiated storage volume snapshot of DB instance, backing up the entire DB instance and not just individual databases that can be restored as a independent RDS instance
  • RDS Security
    • support encryption at rest using KMS as well as encryption in transit using SSL endpoints
    • supports IAM database authentication, which prevents the need to store static user credentials in the database, because authentication is managed externally using IAM.
    • supports Encryption only during creation of an RDS DB instance
    • existing unencrypted DB cannot be encrypted and you need to create a  snapshot, created a encrypted copy of the snapshot and restore as encrypted DB
    • supports Secret Manager for storing and rotating secrets
    • for encrypted database
      • logs, snapshots, backups, read replicas are all encrypted as well
      • cross region replicas and snapshots does not work across region (Note – this is possible now with latest AWS enhancement)
  • Multi-AZ deployment
    • provides high availability and automatic failover support and is NOT a scaling solution
    • maintains a synchronous standby replica in a different AZ
    • transaction success is returned only if the commit is successful both on the primary and the standby DB
    • Oracle, PostgreSQL, MySQL, and MariaDB DB instances use Amazon technology, while SQL Server DB instances use SQL Server Mirroring
    • snapshots and backups are taken from standby & eliminate I/O freezes
    • during automatic failover, its seamless and RDS switches to the standby instance and updates the DNS record to point to standby
    • failover can be forced with the Reboot with failover option
  • Read Replicas
    • uses the PostgreSQL, MySQL, and MariaDB DB engines’ built-in replication functionality to create a separate Read Only instance
    • updates are asynchronously copied to the Read Replica, and data might be stale
    • can help scale applications and reduce read only load
    • requires automatic backups enabled
    • replicates all databases in the source DB instance
    • for disaster recovery, can be promoted to a full fledged database
    • can be created in a different region for disaster recovery, migration and low latency across regions
    • can’t create encrypted read replicas from unencrypted DB or read replica
  • RDS does not support all the features of underlying databases, and if required the database instance can be launched on an EC2 instance
  • RDS Components
    • DB parameter groups contains engine configuration values that can be applied to one or more DB instances of the same instance type for e.g. SSL, max connections etc.
    • Default DB parameter group cannot be modified, create a custom one and attach to the DB
    • Supports static and dynamic parameters
      • changes to dynamic parameters are applied immediately (irrespective of apply immediately setting)
      • changes to static parameters are NOT applied immediately and require a manual reboot.
  • RDS Monitoring & Notification
    • integrates with CloudWatch and CloudTrail
    • CloudWatch provides metrics about CPU utilization from the hypervisor for a DB instance, and Enhanced Monitoring gathers its metrics from an agent on the instance
    • Performance Insights is a database performance tuning and monitoring feature that helps illustrate the database’s performance and help analyze any issues that affect it
    • supports RDS Event Notification which uses the SNS to provide notification when an RDS event like creation, deletion or snapshot creation etc occurs


  • is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases
  • is a managed services and handles time-consuming tasks such as provisioning, patching, backup, recovery, failure detection and repair
  • is a proprietary technology from AWS (not open sourced)
  • provides PostgreSQL and MySQL compatibility
  • is “AWS cloud optimized” and claims 5x performance improvement
    over MySQL on RDS, over 3x the performance of PostgreSQL on RDS
  • scales storage automatically in increments of 10GB, up to 64 TB with no impact to database performance. Storage is striped across 100s of volumes.
  • no need to provision storage in advance.
  • provides self-healing storage. Data blocks and disks are continuously scanned for errors and repaired automatically.
  • provides instantaneous failover
  • replicates each chunk of my the database volume six ways across three Availability Zones i.e. 6 copies of the data across 3 AZ
    • requires 4 copies out of 6 needed for writes
    • requires 3 copies out of 6 need for reads
  • costs more than RDS (20% more) – but is more efficient
  • Read Replicas
    • can have 15 replicas while MySQL has 5, and the replication process is faster (sub 10 ms replica lag)
    • share the same data volume as the primary instance in the same AWS Region, there is virtually no replication lag
    • supports Automated failover for master in less than 30 seconds
    • supports Cross Region Replication using either physical or logical replication.
  • Security
    • supports Encryption at rest using KMS
    • supports Encryption in flight using SSL (same process as MySQL or Postgres)
    • Automated backups, snapshots and replicas are also encrypted
    • Possibility to authenticate using IAM token (same method as RDS)
    • supports protecting the instance with security groups
    • does not support SSH access to the underlying servers
  • Aurora Serverless
    • provides automated database Client  instantiation and on-demand  autoscaling based on actual usage
    • provides a relatively simple, cost-effective option for infrequent, intermittent, or unpredictable workloads
    • automatically starts up, shuts down, and scales capacity up or down based on the application’s needs. No capacity planning needed
    • Pay per second, can be more cost-effective
  • Aurora Global Database
    • allows a single Aurora database to span multiple AWS regions.
    • provides Physical replication, which uses dedicated infrastructure that leaves the databases entirely available to serve the application
    • supports 1 Primary Region (read / write)
    • replicates across up to 5 secondary (read-only) regions, replication lag is less than 1 second
    • supports up to 16 Read Replicas per secondary region
    • recommended for low-latency global reads and disaster recovery with an RTO of < 1 minute
    • failover is not automated and if the primary region becomes unavailable, a secondary region can be manually removed from an Aurora Global Database and promote it to take full reads and writes. Application needs to be updated to point to the newly promoted region.
  • Aurora Backtrack
    • Backtracking “rewinds” the DB cluster to the specified time
    • Backtracking performs in place restore and does not create a new instance. There is a minimal downtime associated with it.
  • Aurora Clone feature allows quick and cost-effective creation of Aurora Cluster duplicates
  • supports parallel or distributed query using Aurora Parallel Query, which refers to the ability to push down and distribute the computational load of a single query across thousands of CPUs in Aurora’s storage layer.


  • fully managed NoSQL database service
  • synchronously replicates data across three facilities in an AWS Region, giving high availability and data durability
  • runs exclusively on SSDs to provide high I/O performance
  • provides provisioned table reads and writes
  • automatically partitions, reallocates and re-partitions the data and provisions additional server capacity as data or throughput changes
  • creates and maintains indexes for the primary key attributes for efficient access of data in the table
  • supports Secondary Indexes
    • allows querying attributes other then the primary key attributes without impacting performance.
    • are automatically maintained as sparse objects
  • Local vs Global secondary index
    • shares partition key + different sort key vs different partition + sort key
    • search limited to partition vs across all partition
    • unique attributes vs non unique attributes
    • linked to the base table vs independent separate index
    • only created during the base table creation vs can be created later
    • cannot be deleted after creation vs can be deleted
    • consumes provisioned throughput capacity of the base table vs independent throughput
    • returns all attributes for item vs only projected attributes
    • Eventually or Strongly vs Only Eventually consistent reads
    • size limited to 10Gb per partition vs unlimited
  • DynamoDB Consistency
    • provides Eventually consistent (by default) or Strongly Consistent option to be specified during an read operation
    • supports Strongly consistent reads for few operations like Query, GetItem, and BatchGetItem using the ConsistentRead parameter
  • DynamoDB Throughput Capacity
    • supports On-demand and Provisioned read/write capacity modes
    • Provisioned mode requires the number of reads and writes per second as required by the application to be specified
    • On-demand mode provides flexible billing option capable of serving thousands of requests per second without capacity planning
  • DynamoDB Global Tables
    • DynamoDB Global Tables provide multi-master, cross-region replication capability of DynamoDB to support data access locality and regional fault tolerance for database workloads.
  • DynamoDB Streams
    • provides a time-ordered sequence of item-level changes made to data in a table
  • DynamoDB Time to Live (TTL)
    • enables a per-item timestamp to determine when an item expiry
    • expired items are deleted from the table without consuming any write throughput.
    • supports cross region replication using DynamoDB streams which leverages Kinesis and provides time-ordered sequence of item-level changes and can help for lower RPO, lower RTO disaster recovery
  • DynamoDB Accelerator (DAX)
    • is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second.
  • supports triggers to allow execution of custom actions or notifications based on item-level updates
  • Data Pipeline jobs with EMR can be used for disaster recovery with higher RPO, lower RTO requirements


  • managed web service that provides in-memory caching to deploy and run Memcached or Redis protocol-compliant cache clusters
  • ElastiCache with Redis,
    • like RDS, supports Multi-AZ, Read Replicas and Snapshots
    • Read Replicas are created across AZ within same region using Redis’s asynchronous replication technology
    • Multi-AZ differs from RDS as there is no standby, but if the primary goes down a Read Replica is promoted as primary
    • Read Replicas cannot span across regions, as RDS supports
    • cannot be scaled out and if scaled up cannot be scaled down
    • allows snapshots for backup and restore
    • AOF can be enabled for recovery scenarios, to recover the data in case the node fails or service crashes. But it does not help in case the underlying hardware fails
    • Enabling Redis Multi-AZ as a Better Approach to Fault Tolerance
  • ElastiCache with Memcached
    • can be scaled up by increasing size and scaled out by adding nodes
    • nodes can span across multiple AZs within the same region
    • cached data is spread across the nodes, and a node failure will always result in some data loss from the cluster
    • supports auto discovery
    • every node should be homogenous and of same instance type
  • ElastiCache Redis vs Memcached
    • complex data objects vs simple key value storage
    • persistent vs non persistent, pure caching
    • automatic failover with Multi-AZ vs Multi-AZ not supported
    • scaling using Read Replicas vs using multiple nodes
    • backup & restore supported vs not supported
  • can be used state management to keep the web application stateless


  • fully managed, fast and powerful, petabyte scale data warehouse service
  • uses replication and continuous backups to enhance availability and improve data durability and can automatically recover from node and component failures
  • provides Massive Parallel Processing (MPP) by distributing & parallelizing queries across multiple physical resources
  • columnar data storage improving query performance and allowing advance compression techniques
  • only supports Single-AZ deployments and the nodes are available within the same AZ, if the AZ supports Redshift clusters
  • spot instances are NOT an option

AWS ElastiCache – Certification

AWS ElastiCache

  • AWS ElastiCache is a managed web service that helps deploy and run Memcached or Redis protocol-compliant cache clusters in the cloud easily
  • ElastiCache is available in two flavours: Memcached and Redis
  • ElastiCache helps
    • simplify and offload the management, monitoring, and operation of in-memory cache environments, enabling the engineering resources to focus on developing applications
    • automate common administrative tasks required to operate a distributed cache environment.
    • improves the performance of web applications by allowing retrieval of information from a fast, managed, in-memory caching system, instead of relying entirely on slower disk-based databases.
    • helps improve load & response times to user actions and queries, but also reduce the cost associated with scaling web applications
    • helps automatically detect and replace failed cache nodes, providing a resilient system that mitigates the risk of overloaded databases, which can slow website and application load times
    • provides enhanced visibility into key performance metrics associated with the cache nodes through integration with CloudWatch
    • code, applications, and popular tools already using Memcached or Redis environments work seamlessly, with being protocol- compliant with Memcached and Redis environments
  • ElastiCache provides in-memory caching which can
    • significantly lower latency and improve throughput for many
      • read-heavy application workloads for e.g. social networking, gaming, media sharing and Q&A portals or
      • compute-intensive workloads such as a recommendation engine
    • improve application performance by storing critical pieces of data in memory for low-latency access.
    • be used to cache results of I/O-intensive database queries or the results of computationally-intensive calculations.
  • ElastiCache currently allows access only from the EC2 network and cannot be accessed from outside networks like on-premises servers

ElastiCache Redis vs Memcached

AWS ElastiCache Redis vs Memcached


  • Redis is an open source, BSD licensed, advanced key-value cache & store
  • ElastiCache enables the management, monitoring and operation of a Redis node; creation, deletion and modification of the node
  • ElastiCache for Redis can be used as a primary in-memory key-value data store, providing fast, sub millisecond data performance, high availability and scalability up to 16 nodes plus up to 5 read replicas, each of up to 3.55 TiB of in-memory data
  • ElastiCache for Redis supports (similar to RDS features)
    • Redis Master/Slave replication.
    • Multi-AZ operation by creating read replicas in another AZ
    • Backup and Restore feature for persistence using snapshots
  • ElastiCache for Redis can be vertically scaled upwards by selecting a larger node type, however it cannot be scaled down
  • Parameter group can be specified for Redis during installation, which acts as a “container” for Redis configuration values that can be applied to one or more Redis primary clusters
  • Append Only File (AOF)
    • provides persistence and can be enabled for recovery scenarios
    • if a node restarts or service crash, Redis will replay the updates from an AOF file, thereby recovering the data lost due to the restart or crash
    • cannot protect against all failure scenarios, cause if the underlying hardware fails, a new server would be provisioned and the AOF file will no longer be available to recover the data
    • Enabling Redis Multi-AZ is a Better Approach to Fault Tolerance, as failing over to a read replica is much faster than rebuilding the primary from an AOF file

Redis Read Replica

  • Read Replicas help provide Read scaling and handling failures
  • Read Replicas are kept in sync with the Primary node using Redis’s asynchronous replication technology
  • Redis Read Replicas provides
    • Horizontal scaling beyond the compute or I/O capacity of a single primary node for read-heavy workloads.
    • Serving read traffic while the primary is unavailable either being down due to failure or maintenance
    • Data protection scenarios to promote a Read Replica as primary node, in case the primary node or the AZ of the primary node fails
  • ElastiCache supports initiated or forced failover where it flips the DNS record for the primary node to point at the read replica, which is in turn promoted to become the new primary
  • Read replica cannot span across regions and may only be provisioned in the same or different AZ of the same Region as the cache node primary

Redis Multi-AZ

  • ElastiCache for Redis shard consists of a primary and up to 5 read replicas
  • Redis asynchronously replicates the data from the primary node to the read replicas
  • ElastiCache for Redis Multi-AZ mode
    • provides enhanced availability and smaller need for administration as the node failover is automatic
    • impact on the ability to read/write to the primary is limited to the time it takes for automatic failover to complete
    • no longer needs monitoring of Redis nodes and manually initiating a recovery in the event of a primary node disruption
  • During certain types of planned maintenance, or in the unlikely event of ElastiCache node failure or AZ failure,
    • it automatically detects the failure,
    • selects a replica, depending upon the read replica with the smallest asynchronous replication lag to the primary, and promotes it to become the new primary node
    • it will also propagate the DNS changes so that the the primary endpoint remains the same
  • If Multi-AZ is not enabled,
    • ElastiCache monitors the primary node
    • in case the node becomes unavailable or unresponsive, it will repair the node by acquiring new service resources
    • it propagates the DNS endpoint changes to redirect the node’s existing DNS name to point to the new service resources.
    • If the primary node cannot be healed and you will have the choice to promote one of the read replicas to be the new primary

Redis Backup & Restore

  • Backup and Restore allows users to create snapshots of the Redis clusters
  • Snapshots can be used for recovery, restoration, archiving purpose or warm start an ElastiCache for Redis cluster with preloaded data
  • Snapshots can created on a cluster basis and uses Redis’ native mechanism to create and store an RDB file as the snapshot
  • Increased latencies for a brief period at the node might be encountered while taking a snapshot, and is recommended to be taken from a Read Replica minimizing performance impact
  • Snapshots can be created either automatically (if configured) or manually
  • ElastiCache for Redis cluster when deleted removes the automatic snapshots. However, manual snapshots are retained


  • Memcached is an in-memory key-value store for small chunks or arbitrary data
  • ElastiCache for Memcached can be used to cache a variety of objects
    • from the content in persistent data stores such as RDS, DynamoDB, or self-managed databases hosted on EC2) to
    • dynamically generated web pages for e.g. with Nginx or
    • transient session data that may not require a persistent backing store
  • ElastiCache for Memcached
    • can be scaled Vertically by increasing the node type size
    • can be scaled Horizontally by adding and removing nodes
    • does not support persistence of data
  • ElastiCache for Memcached cluster can have
    • nodes can span across multiple AZs within the same region
    • maximum of 20 nodes per cluster with a maximum of 100 nodes per region (soft limit and can be extended)
  • ElastiCache for Memcached supports auto discovery, which enables automatic discovery of cache nodes by clients when they are added to or removed from an ElastiCache cluster

ElastiCache Mitigating Failures

  • ElastiCache should be designed to plan so that failures have a minimal impact upon your application and data
  • Mitigating Failures when Running Memcached
    • Mitigating Node Failures
      • spread the cached data over more nodes
      • as Memcached does not support replication, a node failure will always result in some data loss from the cluster
      • having more nodes will reduce the proportion of cache data lost
    • Mitigating Availability Zone Failures
      • locate the nodes in as many availability zones as possible, only the data cached in that AZ is lost, not the data cached in the other AZs
  • Mitigating Failures when Running Redis
    • Mitigating Cluster Failures
      • Redis Append Only Files (AOF)
        • enable AOF so whenever data is written to the Redis cluster, a corresponding transaction record is written to a Redis AOF
        • when Redis process restarts, ElastiCache creates a replacement cluster and provisions it and repopulating it with data from AOF
        • It is time consuming
        • AOF can get big
        • Using AOF cannot protect you from all failure scenarios
      • Redis Replication Groups
        • A Redis replication group is comprised of a single primary cluster which your application can both read from and write to, and from 1 to 5 read-only replica clusters.
        • Data written to the primary cluster is also asynchronously updated on the read replica clusters
        • When a Read Replica fails, ElastiCache detects the failure, replaces the instance in the same AZ and synchronizes with the Primary Cluster
        • Redis Multi-AZ with Automatic Failover, ElastiCache detects Primary cluster failure, promotes a read replica with least replication lag to primary
        • Multi-AZ with Auto Failover is disabled, ElastiCache detects Primary cluster failure, creates a new one and syncs the new Primary with one of the existing replicas
    • Mitigating Availability Zone Failures
      • locate the clusters in as many availability zones as possible


Try Qwiklabs Free Working with Amazon ElastiCache for Redis lab

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. What does Amazon ElastiCache provide?
    1. A service by this name doesn’t exist. Perhaps you mean Amazon CloudCache.
    2. A virtual server with a huge amount of memory.
    3. A managed In-memory cache service
    4. An Amazon EC2 instance with the Memcached software already pre-installed.
  2. You are developing a highly available web application using stateless web servers. Which services are suitable for storing session state data? Choose 3 answers.
    1. Elastic Load Balancing
    2. Amazon Relational Database Service (RDS)
    3. Amazon CloudWatch
    4. Amazon ElastiCache
    5. Amazon DynamoDB
    6. AWS Storage Gateway
  3. Which statement best describes ElastiCache?
    1. Reduces the latency by splitting the workload across multiple AZs
    2. A simple web services interface to create and store multiple data sets, query your data easily, and return the results
    3. Offload the read traffic from your database in order to reduce latency caused by read-heavy workload
    4. Managed service that makes it easy to set up, operate and scale a relational database in the cloud
  4. Our company is getting ready to do a major public announcement of a social media site on AWS. The website is running on EC2 instances deployed across multiple Availability Zones with a Multi-AZ RDS MySQL Extra Large DB Instance. The site performs a high number of small reads and writes per second and relies on an eventual consistency model. After comprehensive tests you discover that there is read contention on RDS MySQL. Which are the best approaches to meet these requirements? (Choose 2 answers)
    1. Deploy ElastiCache in-memory cache running in each availability zone
    2. Implement sharding to distribute load to multiple RDS MySQL instances
    3. Increase the RDS MySQL Instance size and Implement provisioned IOPS
    4. Add an RDS MySQL read replica in each availability zone
  5. You are using ElastiCache Memcached to store session state and cache database queries in your infrastructure. You notice in CloudWatch that Evictions and Get Misses are both very high. What two actions could you take to rectify this? Choose 2 answers
    1. Increase the number of nodes in your cluster
    2. Tweak the max_item_size parameter
    3. Shrink the number of nodes in your cluster
    4. Increase the size of the nodes in the cluster
  6. You have been tasked with moving an ecommerce web application from a customer’s datacenter into a VPC. The application must be fault tolerant and well as highly scalable. Moreover, the customer is adamant that service interruptions not affect the user experience. As you near launch, you discover that the application currently uses multicast to share session state between web servers, In order to handle session state within the VPC, you choose to:
    1. Store session state in Amazon ElastiCache for Redis (scalable and makes the web applications stateless)
    2. Create a mesh VPN between instances and allow multicast on it
    3. Store session state in Amazon Relational Database Service (RDS solution not highly scalable)
    4. Enable session stickiness via Elastic Load Balancing (affects user experience if the instance goes down)
  7. When you are designing to support a 24-hour flash sale, which one of the following methods best describes a strategy to lower the latency while keeping up with unusually heavy traffic?
    1. Launch enhanced networking instances in a placement group to support the heavy traffic (only improves internal communication)
    2. Apply Service Oriented Architecture (SOA) principles instead of a 3-tier architecture (just simplifies architecture)
    3. Use Elastic Beanstalk to enable blue-green deployment (only minimizes download for applications and ease of rollback)
    4. Use ElastiCache as in-memory storage on top of DynamoDB to store user sessions (scalable, faster read/writes and in memory storage)
  8. You are configuring your company’s application to use Auto Scaling and need to move user state information. Which of the following AWS services provides a shared data store with durability and low latency?
    1. AWS ElastiCache Memcached (does not provide durability as if the node is gone the data is gone)
    2. Amazon Simple Storage Service
    3. Amazon EC2 instance storage
    4. Amazon DynamoDB
  9. Your application is using an ELB in front of an Auto Scaling group of web/application servers deployed across two AZs and a Multi-AZ RDS Instance for data persistence. The database CPU is often above 80% usage and 90% of I/O operations on the database are reads. To improve performance you recently added a single-node Memcached ElastiCache Cluster to cache frequent DB query results. In the next weeks the overall workload is expected to grow by 30%. Do you need to change anything in the architecture to maintain the high availability for the application with the anticipated additional load and Why?
    1. You should deploy two Memcached ElastiCache Clusters in different AZs because the RDS Instance will not be able to handle the load if the cache node fails.
    2. If the cache node fails the automated ElastiCache node recovery feature will prevent any availability impact. (does not provide high availability, as data is lost if the node is lost)
    3. Yes you should deploy the Memcached ElastiCache Cluster with two nodes in the same AZ as the RDS DB master instance to handle the load if one cache node fails. (Single AZ affects availability as DB is Multi AZ and would be overloaded is the AZ goes down)
    4. No if the cache node fails you can always get the same data from the DB without having any availability impact. (Will overload the database affecting availability)
  10. A read only news reporting site with a combined web and application tier and a database tier that receives large and unpredictable traffic demands must be able to respond to these traffic fluctuations automatically. What AWS services should be used meet these requirements?
    1. Stateless instances for the web and application tier synchronized using ElastiCache Memcached in an autoscaling group monitored with CloudWatch and RDS with read replicas.
    2. Stateful instances for the web and application tier in an autoscaling group monitored with CloudWatch and RDS with read replicas (Stateful instances will not allow for scaling)
    3. Stateful instances for the web and application tier in an autoscaling group monitored with CloudWatch and multi-AZ RDS (Stateful instances will allow not for scaling & multi-AZ is for high availability and not scaling)
    4. Stateless instances for the web and application tier synchronized using ElastiCache Memcached in an autoscaling group monitored with CloudWatch and multi-AZ RDS (multi-AZ is for high availability and not scaling)
  11. You have written an application that uses the Elastic Load Balancing service to spread traffic to several web servers. Your users complain that they are sometimes forced to login again in the middle of using your application, after they have already logged in. This is not behavior you have designed. What is a possible solution to prevent this happening?
    1. Use instance memory to save session state.
    2. Use instance storage to save session state.
    3. Use EBS to save session state.
    4. Use ElastiCache to save session state.
    5. Use Glacier to save session slate.

AWS Storage Options – CloudFront & ElastiCache

Amazon CloudFront

  • is a webservice for content delivery
  • provides low latency by caching and delivering content from a global network of edge locations located nearest to the user
  • supports both HTTP to allows static, dynamic content and Real Time Messaging Protocol (RTMP) for streaming of videos
  • optimized to work as with Amazon services like S3, ELB etc. as well as works seamlessly with any non-AWS origin server

Ideal Usage Patterns

  • is ideal for distribution of frequently accessed static content, or dynamic content or for streaming audio or video that benefits from edge delivery


  • Infrequently accessed data
    • If the data is infrequently accessed, it would be better to serve the data from the Origin server
  • Programmatic cache invalidation
    • CloudFront supports cache invalidation, however AWS recommends using object versioning rather than programmatic cache invalidation.


  • is designed for low latency and high bandwidth delivery of content by redirecting the user to the nearest edge location in terms of latency and caching the content preventing the round trip to the origin server

Durability & Availability

  • provides high Availability by delivering content from a distributed global network of edge locations. Amazon also constantly monitors the network paths connecting Origin servers to CloudFront
  • does not provide durable storage, which is more of the responsibility of the underlying Origin server providing the content for e.g. S3

Cost Model

  • has two pricing components:
    • regional data transfer out (per GB) and
    • requests (per 10,000)

Scalability & Elasticity

  • provides seamless scalability & elasticity by automatically responding to the increase or the decrease in the demand


  • is a webservice that makes it easy to deploy, operate, and scale a distributed, in-memory cache in the cloud
  • helps improves performance of the applications by allowing retrieval of data from fast, managed, in-memory caching system
  • supports Memcached (object caching) & Redis (key value store that supports data structure) open source caching engines

Ideal Usage Patterns

  • improving application performance by storing critical data in-memory for low latency access
  • use cases involve usage as a database front end for read heavy applications, improving performance and reducing load on databases, or managing user session data, cache dynamically generated pages, or compute intensive calculations etc.


  • Persistent Data
    • If the application needs fast access to data coupled with strong data durability, Amazon DynamoDB would be a better option


  • Although ElastiCache provides low latency access to the data, the performance depends on the caching strategy and the hit ratio at the application level

Durability & Availability

  • stores transient data or transient copies of durable data, so the data durability is managed by the source
  • With the Memcached engine
    • all ElastiCache nodes in a single cache cluster are provisioned in a single Availability Zone.
    • ElastiCache automatically monitors the health of your cache nodes and replaces them in the event of network partitioning, host hardware, or software failure.
    • In the event of cache node failure, the cluster remains available, but performance may be reduced due to time needed to repopulate the cache in the new “cold” cache nodes.
    • To provide enhanced fault-tolerance for Availability Zone failures or cold-cache effects, you can run redundant cache clusters in different Availability Zones.
  • With the Redis engine,
    • ElastiCache supports replication to up to five read replicas for scaling. To improve availability, you can place read replicas in other Availability Zones.
    • ElastiCache monitors the primary node, and if the node becomes unavailable, ElastiCache will repair or replace the primary node if possible, using the same DNS name.
    • If the primary cache node recovery fails or its Availability Zone is unavailable, primary node can be failed over to one of the read replicas with an API call.

Cost Model

  • has a single pricing component:
    • pricing is per cache node-hour consumed

Scalability & Elasticity

  • ElastiCache is highly scalable and elastic.
  • Cache node can be added or deleted to the cache cluster
  • Auto Discovery enables automatic discovery of Memcached cache nodes by ElastiCache Clients when the nodes are added to or removed from an ElastiCache cluster.