In this short series, I outline the notes that I took while preparing for the AWS Cloud Practitioner exam.
These are my personal notes that I have made while working through the A Cloud Guru exam practitioner course. They are in no way official notes from AWS.
I would advise you that if you do use my notes to help you revise for this exam, that you use them as a supplement to the most recent information in the White Papers, Exam Guide and go over your knowledge with practice exam papers.
Previous notes within this blog series:
- Cloud Computing and the Topics To Cover
- AWS Global Infrastructure
- AWS Cost Management
- Identity Access Management (IAM)
- Simple Storage Service (S3)
- CloudFront
- Elastic Compute Cloud (EC2)
- Roles
- Load Balancers
- Databases
- Domain Name System
- Elastic Beanstalk
- CloudFormation
- Architecting for the Cloud Best Practices: Part 1
Architecting for the Cloud Best Practices: Part 2
Databases
Relational Databases (Aurora)
- Scalability
- High availability – Multi AZ (spread across 3 AZ or more)
- Anti-Patterns – Wouldn’t use this is you have a need for joins or complex transactions, use No-SQL
Non-Relational Database (DynamoDB)
- Scalability
- High availability – Multi AZ (spread across 3 AZ or more)
- Anti-Patterns – Wouldn’t use this if you have a need for joins or complex transactions, use relational databases (Aurora or others). If you have large binary files (audio. video, and image), consider storing the files in Amazon S3
Data Warehouse (Redshift)
- Scalability
- High availability – Multi AZ (spread across 3 AZ or more)
- Anti-Patterns – Not meant for On Line Transaction Processing (OLTP)
Search (CloudSearch, Amazon ElasticSearch)
- Scalability
- High availability – Multi AZ (spread across 2 AZ or more)
Graph Databases (Amazon Neptune)
- Scalability
- High availability
Managing Increasing Volumes of Data
- Build a Data Lake
- A data lake is an architectural approach that allows you to store massive amounts of data in a central location so that it’s readily available to be categorized, processed, analysed, and consumed by diverse groups in your organisation.
- NO need to convert to predfined schema or what questions to ask about your data before
- Can be stored in S3
- Use Athena to run SQL queries on the db
Removing Single Points of Failure
- Introducing Redundancy
- Detect Failure
- Durable Data Storage
- Automated Multi-Data Centre Resilience (should probably be done on a region basis as well)
- Fault Isolation and Traditional Horizontal Scaling
- Sharding
Optimize For Cost
- Right Sizing
- Elasticity
- Take Advantage of the Variety of Purchasing Options e.g. Reserve Capacity, Spot Instances etc
Caching
- Application Caching. Using Elasticache
- Edge Caching e.g. CloudFront
Security
- Use AWS Features for Defense in Depth e.g. web application firewalls
- Share Security Responsibility with AWS
- Reduce Privileged Access
- Security as Code. Create golden environments and can be deployed easily using CloudFormation.
- Real-Time Auditing. AWS Cloud Trail
Read the Whitepaper the day before the exam!
