The AWS Certified Solutions Architect Associate SAA-C03 exam is the latest version of the AWS Solutions Architect Associate certification exam. This exam is designed for individuals who have a working knowledge of AWS services and can design and deploy scalable, highly available, and fault-tolerant systems on AWS.
The exam covers a range of topics, including:
- Designing resilient architectures
- Defining performant architectures
- Specifying secure applications and architectures
- Designing cost-optimized architectures
- Defining operationally excellent architectures
AWS Certified Solutions Architect Associate SAA-C03 Glossary
Here are some important terms and concepts related to the AWS Certified Solutions Architect Associate SAA-C03 exam:
- AWS (Amazon Web Services): A cloud services platform that provides a wide range of infrastructure services, such as computing power, storage options, and databases.
- IAM (Identity and Access Management): A service that allows you to manage access to AWS resources and services securely.
- VPC (Virtual Private Cloud): A virtual network that provides a secure and isolated environment for your AWS resources.
- EC2 (Elastic Compute Cloud): A service that provides scalable computing capacity in the cloud.
- S3 (Simple Storage Service): A scalable and durable object storage service that allows you to store and retrieve data from anywhere on the web.
- Auto Scaling: A service that allows you to automatically scale your AWS resources based on demand.
- ELB (Elastic Load Balancing): A service that automatically distributes incoming application traffic across multiple targets, such as EC2 instances or containers.
- Lambda: A service that allows you to run code without provisioning or managing servers.
- CloudFormation: A service that provides a common language for you to describe and provision all the infrastructure resources in your cloud environment.
- CloudWatch: A monitoring service that provides real-time monitoring and visibility into your AWS resources and applications.
- High availability: A design principle that aims to ensure that a system remains operational and accessible even in the event of hardware or software failures.
- Disaster recovery: A set of processes and procedures that allow a system to recover from a catastrophic event, such as a natural disaster or cyber attack.
AWS Certified Solutions Architect Associate SAA-C03 Exam Guide
Here are some official resources provided by AWS to help you prepare for the AWS Certified Solutions Architect Associate SAA-C03 exam:
- Exam guide: The AWS Certified Solutions Architect Associate SAA-C03 Exam Guide provides a detailed overview of the exam, including the topics covered, exam format, and sample questions. You can access the exam guide here: https://aws.amazon.com/certification/certified-solutions-architect-associate/
- Training courses: AWS offers a range of training courses to help you prepare for the exam, including classroom training, virtual training, and self-paced digital training. You can explore the available training courses here: https://aws.amazon.com/training/path-architecting/
- Whitepapers: AWS offers a range of whitepapers that cover various AWS services and topics related to cloud computing. These whitepapers can help you deepen your understanding of AWS services and prepare for the exam. You can access the AWS whitepapers here: https://aws.amazon.com/whitepapers/
- AWS documentation: AWS provides comprehensive documentation for all of its services, which can be a valuable resource when preparing for the exam. You can access the AWS documentation here: https://aws.amazon.com/documentation/
AWS Certified Solutions Architect Associate SAA-C03 Exam Tips and Tricks
Here are some tips and tricks to help you prepare for the AWS Certified Solutions Architect Associate SAA-C03 exam:
- Start with the exam guide: The AWS Certified Solutions Architect Associate SAA-C03 exam guide is an important resource that provides information on the exam format, content, and objectives. Make sure you read the guide thoroughly before starting your preparation.
- Create a study plan: Plan your study schedule and set realistic goals. Allocate sufficient time for each topic and try to cover all the important areas before the exam.
- Understand the AWS services: AWS provides a wide range of services, and it’s important to understand each service’s purpose, features, and benefits. Make sure you have a good understanding of services such as EC2, S3, RDS, IAM, and VPC, as these are frequently tested in the exam.
- Hands-on experience: It’s important to have hands-on experience with AWS services. Sign up for a free AWS account and try to implement various services on the platform. AWS provides a lot of free resources to help you get started, such as the AWS Free Tier and the AWS documentation.
- Practice with sample questions: Practice with sample questions to get a feel for the exam format and content. AWS provides sample questions on their website, and there are also many online resources that offer practice questions and exams.
- Use whitepapers and documentation: AWS provides a lot of documentation and whitepapers on various topics, such as security, networking, and storage. Make sure you read these documents thoroughly as they contain valuable information that can help you prepare for the exam.
- Join study groups: Join online study groups and forums to discuss topics with other candidates and share knowledge and experiences. This can help you gain new insights and perspectives and reinforce your understanding of the topics.
Course Outline
Let us now have a look at the detailed course outline –
New AWS Certified Solutions Architect – Associate (SAA-C03) Exam Course Outline
Domain 1: Design Secure Architectures
Task Statement 1: Design secure access to AWS resources.
Knowledge of:
- Access controls and management across multiple accounts (AWS Documentation: Delegate access across AWS)
- AWS federated access and identity services (for example, AWS Identity and Access Management [IAM], AWS Single Sign-On [AWS SSO]) (AWS Documentation: Identity providers and federation)
- Next, AWS global infrastructure (for example, Availability Zones, AWS Regions) (AWS Documentation: Regions, Availability Zones, and Local Zones)
- AWS security best practices (for example, the principle of least privilege) (AWS Documentation: Security best practices in IAM)
- The AWS shared responsibility model (AWS Documentation: Shared responsibility model)
Skills in:
- Applying AWS security best practices to IAM users and root users (for example, multi-factor authentication [MFA]) (AWS Documentation: Best practices to protect your account’s root user)
- Further, Designing a flexible authorization model that includes IAM users, groups, roles, and policies (AWS Documentation: IAM Identities (users, user groups, and roles))
- Designing a role-based access control strategy (for example, AWS Security Token Service [AWS STS], role switching, cross-account access) (AWS Documentation: Define permissions to access AWS resources , Delegate access across AWS)
- Designing a security strategy for multiple AWS accounts (for example, AWS Control Tower, service control policies [SCPs])
- Determining the appropriate use of resource policies for AWS services (AWS Documentation: Identity-based policies and resource-based policies)
- Determining when to federate a directory service with IAM roles
Task Statement 2: Design secure workloads and applications.
Knowledge of:
- Application configuration and credentials security (AWS Documentation: Configuration and credential file settings)
- AWS service endpoints (AWS Documentation: Service endpoints and quotas)
- Control ports, protocols, and network traffic on AWS (AWS Documentation: Control traffic to subnets using Network ACLs)
- Secure application access
- Security services with appropriate use cases (for example, Amazon Cognito, Amazon GuardDuty, Amazon Macie) (AWS Documentation: Amazon Macie, Amazon GuardDuty, Cognito)
- Threat vectors external to AWS (for example, DDoS, SQL injection) (AWS Documentation: AWS Shield)
Skills in:
- Designing VPC architectures with security components (for example, security groups, route tables, network ACLs, NAT gateways) (AWS Documentation: VPC with public and private subnets (NAT))
- Determining network segmentation strategies (for example, using public subnets and private subnets) (AWS Documentation: VPC with public and private subnets (NAT))
- Integrating AWS services to secure applications (for example, AWS Shield, AWS WAF, AWS SSO, AWS Secrets Manager) (AWS Documentation: AWS Shield Advanced, Authenticating requests)
- Securing external network connections to and from the AWS Cloud (for example, VPN, AWS Direct Connect) (AWS Documentation: AWS Virtual Private Network, AWS Direct Connect)
Task Statement 3: Determine appropriate data security controls.
Knowledge of:
- Data access and governance (AWS Documentation: Management and Governance)
- Also, Data recovery (AWS Documentation: Elastic Disaster Recovery)
- Next, Data retention and classification (AWS Documentation: Data Classification)
- Encryption and appropriate key management (AWS Documentation: AWS Key Management Service)
Skills in:
- Aligning AWS technologies to meet compliance requirements (AWS Documentation: Security and compliance)
- Encrypting data at rest (for example, AWS Key Management Service [AWS KMS]) (AWS Documentation: AWS KMS concepts)
- Encrypting data in transit (for example, AWS Certificate Manager [ACM] using TLS) (AWS Documentation: Using SSL/TLS to encrypt a connection to a DB instance)
- Implementing access policies for encryption keys
- Further, Implementing data backups and replications (AWS Documentation: Replicating automated backups to another AWS Region)
- Implementing policies for data access, lifecycle, and protection
- Rotating encryption keys and renewing certificates (AWS Documentation: Rotating your SSL/TLS certificate)
Domain 2: Design Resilient Architectures
Task Statement 1: Design scalable and loosely coupled architectures.
Knowledge of:
- API creation and management (for example, Amazon API Gateway, REST API) (AWS Documentation: Amazon API Gateway)
- AWS managed services with appropriate use cases (for example, AWS Transfer Family, Amazon Simple Queue Service [Amazon SQS], Secrets Manager) (AWS Documentation: AWS Secrets Manager, AWS Transfer Family (AMS SSPS))
- Caching strategies Caching strategies)
- Design principles for microservices (for example, stateless workloads compared with stateful workloads)
- Event-driven architectures (AWS Documentation: Event-driven architectures)
- Horizontal scaling and vertical scaling
- How to appropriately use edge accelerators (for example, content delivery network [CDN]) (AWS Documentation: Content Delivery Networks (CDNs))
- How to migrate applications into containers (AWS Documentation: Migrate your Applications to Containers at Scale)
- Load balancing concepts (for example, Application Load Balancer) (AWS Documentation: Application Load Balancer)
- Multi-tier architectures (AWS Documentation: multi-tier application)
- Queuing and messaging concepts (for example, publish/subscribe) (AWS Documentation: Pub/Sub Messaging)
- Serverless technologies and patterns (for example, AWS Fargate, AWS Lambda) (AWS Documentation: serverless saga pattern by using AWS Step Functions)
- Storage types with associated characteristics (for example, object, file, block)
- The orchestration of containers (for example, Amazon Elastic Container Service [Amazon ECS], Amazon Elastic Kubernetes Service [Amazon EKS]) (AWS Documentation: Orchestrating the containers)
- When to use read replicas
- Workflow orchestration (for example, AWS Step Functions) (AWS Documentation: AWS Step Functions)
Skills in:
- Designing event-driven, microservice, and/or multi-tier architectures based on requirements (AWS Documentation: Event-Driven Architecture)
- Determining scaling strategies for components used in an architecture design
- Also, Determining the AWS services required to achieve loose coupling based on requirements (AWS Documentation: Loosely Coupled Scenarios)
- Determining when to use containers (AWS Documentation: Determining task size)
- Determining when to use serverless technologies and patterns
- Recommending appropriate compute, storage, networking, and database technologies based on requirements
- Using purpose-built AWS services for workloads (AWS Documentation: Database)
Task Statement 2: Design highly available and/or fault-tolerant architectures.
Knowledge of:
- AWS global infrastructure (for example, Availability Zones, AWS Regions, Amazon Route 53) (AWS Documentation: AWS Global Infrastructure, Regions and Availability Zones)
- AWS managed services with appropriate use cases (for example, Amazon Comprehend, and Amazon Polly) (AWS Documentation: Machine Learning (ML))
- Basic networking concepts (for example, route tables) (AWS Documentation: Configure route tables)
- Disaster recovery (DR) strategies (for example, backup and restore, pilot light, warm standby, active-active failover, recovery point objective [RPO], recovery time objective [RTO]) (AWS Documentation: Plan for Disaster Recovery (DR))
- Distributed design patterns (AWS Documentation: Design Interactions in a Distributed System to Prevent Failures)
- Failover strategies (AWS Documentation: Active-active and active-passive failover)
- Immutable infrastructure (AWS Documentation: Use immutable infrastructure with no human access)
- Load balancing concepts (for example, Application Load Balancer) (AWS Documentation: Application Load Balancer)
- Proxy concepts (for example, Amazon RDS Proxy) (AWS Documentation: Using Amazon RDS Proxy)
- Service quotas and throttling (for example, how to configure the service quotas for a workload in a standby environment) (AWS Documentation: AWS service quotas)
- Storage options and characteristics (for example, durability, replication) (AWS Documentation: Replicating objects)
- Workload visibility (for example, AWS X-Ray) (AWS Documentation: AWS X-Ray)
Skills in:
- Determining automation strategies to ensure infrastructure integrity (AWS Documentation: Protecting Compute)
- Determining the AWS services required to provide a highly available and/or fault-tolerant architecture across AWS Regions or Availability Zones (AWS Documentation: Architecture guidelines and decisions)
- Identifying metrics based on business requirements to deliver a highly available solution
- Implementing designs to mitigate single points of failure (AWS Documentation: Withstand Component Failures)
- Implementing strategies to ensure the durability and availability of data (for example, backups)
- Selecting an appropriate DR strategy to meet business requirements (AWS Documentation: Plan for Disaster Recovery (DR))
- Using AWS services that improve the reliability of legacy applications and applications not built for the cloud (for example, when application changes are not possible)
- Using purpose-built AWS services for workloads (AWS Documentation: Database)
Domain 3: Design High-Performing Architectures
Task Statement 1: Determine high-performing and/or scalable storage solutions.
Knowledge of:
- Hybrid storage solutions to meet business requirements (AWS Documentation: Hybrid Cloud Storage)
- Storage services with appropriate use cases (for example, Amazon S3, Amazon Elastic File System [Amazon EFS], Amazon Elastic Block Store [Amazon EBS]) (AWS Documentation: Storage)
- Storage types with associated characteristics (for example, object, file, block)
Skills in:
- Determining storage services and configurations that meet performance demands (AWS Documentation: Storage Architecture Selection)
- Determining storage services that can scale to accommodate future needs (AWS Documentation: Storage)
Task Statement 2: Design high-performing and elastic compute solutions.
Knowledge of:
- AWS compute services with appropriate use cases (for example, AWS Batch, Amazon EMR, Fargate) (AWS Documentation: AWS Batch on AWS Fargate, Compute Services)
- Distributed computing concepts supported by AWS global infrastructure and edge services (AWS Documentation: Global infrastructure)
- Queuing and messaging concepts (for example, publish/subscribe) (AWS Documentation: Pub/Sub Messaging)
- Scalability capabilities with appropriate use cases (for example, Amazon EC2 Auto Scaling, AWS Auto Scaling) (AWS Documentation: Amazon EC2 Auto Scaling)
- Serverless technologies and patterns (for example, Lambda, Fargate) (AWS Documentation: Serverless)
- The orchestration of containers (for example, Amazon ECS, Amazon EKS) (AWS Documentation: Orchestrating the containers)
Skills in:
- Decoupling workloads so that components can scale independently (AWS Documentation: Event-Driven Architecture)
- Identifying metrics and conditions to perform scaling actions (AWS Documentation: Monitor CloudWatch metrics)
- Selecting the appropriate compute options and features (for example, EC2 instance types) to meet business requirements (AWS Documentation: Amazon EC2 Instance Types)
- Selecting the appropriate resource type and size (for example, the amount of Lambda memory) to meet business requirements
Task Statement 3: Determine high-performing database solutions.
Knowledge of:
- Firstly, global infrastructure (for example, Availability Zones, AWS Regions) (AWS Documentation: Global infrastructure)
- Caching strategies and services (for example, Amazon ElastiCache) (AWS Documentation: Caching strategies)
- Data access patterns (for example, read-intensive compared with write-intensive) (AWS Documentation: Best practices for Amazon RDS)
- Further, Database capacity planning (for example, capacity units, instance types, Provisioned IOPS)
- Also, engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations) (AWS Documentation: Heterogeneous database migration)
- Database types and services (for example, serverless, relational compared with non-relational, in-memory) (AWS Documentation: Database)
Skills in:
- Configuring read replicas to meet business requirements
- Designing database architectures (AWS Documentation: Database Architecture Selection)
- Determining an appropriate database engine (for example, MySQL compared with PostgreSQL) (AWS Documentation: Best practices for Amazon RDS)
- Determining an appropriate database type (for example, Amazon Aurora, Amazon DynamoDB)
- Integrating caching to meet business requirements
Task Statement 4: Determine high-performing and/or scalable network architectures.
Knowledge of:
- Edge networking services with appropriate use cases (for example, Amazon CloudFront, AWS Global Accelerator) (AWS Documentation: Edge networking with AWS)
- How to design network architecture (for example, subnet tiers, routing, IP addressing) (AWS Documentation: VPC with public and private subnets (NAT))
- Load balancing concepts (for example, Application Load Balancer) (AWS Documentation: Application Load Balancer)
- Network connection options (for example, AWS VPN, Direct Connect, AWS PrivateLink) (AWS Documentation: AWS Direct Connect)
Skills in:
- Creating a network topology for various architectures (for example, global, hybrid, multi-tier) (AWS Documentation: Plan your Network Topology)
- Determining network configurations that can scale to accommodate future needs (AWS Documentation: AWS Foundational Security Best Practices controls)
- Determining the appropriate placement of resources to meet business requirements
- Selecting the appropriate load balancing strategy (AWS Documentation: Application Load Balancer)
Task Statement 5: Determine high-performing data ingestion and transformation solutions.
Knowledge of:
- Data analytics and visualization services with appropriate use cases (for example, Amazon Athena, AWS Lake Formation, Amazon QuickSight) (AWS Documentation: Amazon QuickSight, Use Amazon Athena and Amazon QuickSight to build custom reports)
- Data ingestion patterns (for example, frequency) (AWS Documentation: Data ingestion patterns)
- Data transfer services with appropriate use cases (for example, AWS DataSync, AWS Storage Gateway) (AWS Documentation: AWS DataSync)
- Data transformation services with appropriate use cases (for example, AWS Glue) (AWS Documentation: What is AWS Glue?)
- Secure access to ingestion access points (AWS Documentation: Managing data access with Amazon S3 access points)
- Sizes and speeds needed to meet business requirements
- Streaming data services with appropriate use cases (for example, Amazon Kinesis) (AWS Documentation: AWS Streaming Data Solution for Amazon Kinesis)
Skills in:
- Building and securing data lakes (AWS Documentation: Securing, protecting, and managing data)
- Designing data streaming architectures (AWS Documentation: Build Modern Data Streaming Analytics Architectures on AWS)
- Designing data transfer solutions
- Implementing visualization strategies (AWS Documentation: Visualizing data in Amazon QuickSight)
- Selecting appropriate compute options for data processing (for example, Amazon EMR)
- Selecting appropriate configurations for ingestion (AWS Documentation: Data ingestion methods)
- Transforming data between formats (for example, .csv to .parquet)
Domain 4: Design Cost-Optimized Architectures
Task Statement 1: Design cost-optimized storage solutions.
Knowledge of:
- Access options (for example, an S3 bucket with Requester Pays object storage) (AWS Documentation: Using Requester Pays buckets for storage transfers and usage)
- Learning AWS cost management service features (for example, cost allocation tags, multi-account billing) (AWS Documentation: Using Cost Allocation Tags)
- AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report) (AWS Documentation: Analyzing your costs with AWS Cost Explorer)
- Understanding AWS storage services with appropriate use cases (for example, Amazon FSx, Amazon EFS, Amazon S3, Amazon EBS) (AWS Documentation: Storage)
- Backup strategies (AWS Documentation: AWS Backup)
- Block storage options (for example, hard disk drive [HDD] volume types, solid state drive [SSD] volume types) (AWS Documentation: Amazon EBS volume types)
- Data lifecycles (AWS Documentation: Amazon Data Lifecycle Manager)
- Hybrid storage options (for example, DataSync, Transfer Family, Storage Gateway)
- Storage access patterns
- Storage tiering (for example, cold tiering for object storage) (AWS Documentation: Using Amazon S3 storage classes)
- Storage types with associated characteristics (for example, object, file, block) (AWS Documentation: Storage)
Skills in:
- Designing appropriate storage strategies (for example, batch uploads to Amazon S3 compared with individual uploads) (AWS Documentation: Best practices design patterns: optimizing Amazon S3 performance)
- Determining the correct storage size for a workload (AWS Documentation: Tips for Right Sizing)
- Determining the lowest cost method of transferring data for a workload to AWS storage
- Determining when storage auto scaling is required (AWS Documentation: Amazon EC2 Auto Scaling)
- Managing S3 object lifecycles (AWS Documentation: Managing your storage lifecycle)
- Selecting the appropriate backup and/or archival solution (AWS Documentation: Choosing AWS services for data protection)
- Selecting the appropriate service for data migration to storage services
- Selecting the appropriate storage tier
- Selecting the correct data lifecycle for storage (AWS Documentation: Managing your storage lifecycle)
- Selecting the most cost-effective storage service for a workload (AWS Documentation: Cost-effective resources)
Task Statement 2: Design cost-optimized compute solutions.
Knowledge of:
- AWS cost management service features (for example, cost allocation tags, multi-account billing) (AWS Documentation: Using Cost Allocation Tags)
- AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report) (AWS Documentation: AWS Cost Explorer)
- AWS global infrastructure (for example, Availability Zones, AWS Regions) (AWS Documentation: Global infrastructure)
- AWS purchasing options (for example, Spot Instances, Reserved Instances, Savings Plans) (AWS Documentation: Instance purchasing options)
- Distributed compute strategies (for example, edge processing) (AWS Documentation: Amazon SageMaker Distributed Training Libraries)
- Hybrid compute options (for example, AWS Outposts, AWS Snowball Edge) (AWS Documentation: Compute Services)
- Instance types, families, and sizes (for example, memory optimized, compute optimized, virtualization) (AWS Documentation: Memory optimized instances)
- Optimization of compute utilization (for example, containers, serverless computing, microservices)
- Scaling strategies (for example, auto scaling, hibernation) (AWS Documentation: Warm pools for Amazon EC2 Auto Scaling)
Skills in:
- Determining an appropriate load balancing strategy (for example, Application Load Balancer [Layer 7] compared with Network Load Balancer [Layer 4] compared with Gateway Load Balancer) (AWS Documentation: Elastic Load Balancing FAQs)
- Determining appropriate scaling methods and strategies for elastic workloads (for example, horizontal compared with vertical, EC2 hibernation) (AWS Documentation: Best practices for EC2 Spot)
- Determining cost-effective AWS compute services with appropriate use cases (for example, Lambda, Amazon EC2, Fargate)
- Determining the required availability for different classes of workloads (for example, production workloads, non-production workloads) (AWS Documentation: Workloads)
- Selecting the appropriate instance family for a workload
- Selecting the appropriate instance size for a workload (AWS Documentation: Tips for Right Sizing)
Task Statement 3: Design cost-optimized database solutions.
Knowledge of:
- AWS cost management service features (for example, cost allocation tags, multi-account billing) (AWS Documentation: Using Cost Allocation Tags)
- AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report) (AWS Documentation: AWS Cost Explorer)
- Caching strategies (AWS Documentation: Caching strategies)
- Data retention policies
- Database capacity planning (for example, capacity units) (AWS Documentation: Read/write capacity mode)
- Database connections and proxies (AWS Documentation: Using Amazon RDS Proxy)
- Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations) (AWS Documentation: Heterogeneous database migration)
- Database replication (for example, read replicas) (AWS Documentation: Working with read replicas)
- Database types and services (for example, relational compared with non-relational, Aurora, DynamoDB) (AWS Documentation: Database)
Skills in:
- Designing appropriate backup and retention policies (for example, snapshot frequency)
- Determining an appropriate database engine (for example, MySQL compared with PostgreSQL) (AWS Documentation: Best practices for Amazon RDS)
- Determining cost-effective AWS database types (for example, time series format, columnar format) (AWS Documentation: AWS Cloud Databases)
- Migrating database schemas and data to different locations and/or different database engines (AWS Documentation: Best practices for AWS Database Migration Service)
Task Statement 4: Design cost-optimized network architectures.
Knowledge of:
- AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report) (AWS Documentation: AWS Cost Explorer)
- Load balancing concepts (for example, Application Load Balancer) (AWS Documentation: Application Load Balancer)
- NAT gateways (for example, NAT instance costs compared with NAT gateway costs) (AWS Documentation: Compare NAT gateways and NAT instances)
- Network routing, topology, and peering (for example, AWS Transit Gateway, VPC peering) (AWS Documentation: Transit gateway design best practices)
- Network services with appropriate use cases (for example, DNS) (AWS Documentation: Networking and Content Delivery)
Skills in:
- Configuring appropriate NAT gateway types for a network (for example, a single shared NAT gateway compared with NAT gateways for each Availability Zone) (AWS Documentation: NAT gateways)
- Configuring appropriate network connections (for example, Direct Connect compared with VPN compared with internet) (AWS Documentation: AWS Direct Connect FAQs)
- Determining strategic needs for content delivery networks (CDNs) and edge caching (AWS Documentation: Working with Content Delivery Networks (CDNs))
- Reviewing existing workloads for network optimizations (AWS Documentation: Optimize over time)
- Selecting an appropriate throttling strategy (AWS Documentation: Throttle API requests for better throughput)
- Selecting the appropriate bandwidth allocation for a network device (for example, a single VPN compared with multiple VPNs, Direct Connect speed) (AWS Documentation: Site-to-Site VPN single and multiple connection)
Let us now look at the differences between both the exams –
Differences
There are some differences between the exam guides for the SAA-C02 and the SAA-C03, but there is a lot of overlap from the SAA-C02, and it does reference some of the latest services and features within existing services. From a domain standpoint, there are still four different assessment domains to focus on, with minor differences as shown in the two domain tables for each exam.
For Old Version –
| SAA-C02 DOMAINS | % OF EXAM |
|---|---|
| Domain 1:Design Resilient Architectures | 30% |
| Domain 2: Design High-Performing Architectures | 28% |
| Domain 3: Design Secure Applications and Architectures | 24% |
| Domain 4: Design Cost-Optimized Architectures | 18% |
| TOTAL | 100% |
For the new Exam –
| SAA-C03 Domains | % of exam |
| Domain 1: Design Secure Architectures | 30% |
| Domain 2: Design Resilient Architectures | 26% |
| Domain 3: Design High Performing Architectures | 24% |
| Domain 4: Design Cost-Optimized Architectures | 20% |
| TOTAL | 100% |
Based on these comparisons, we can see that there is now a greater emphasis on cost management and security, as the percentages in these two areas have increased by 8%. When compared to the SAA-C02 exam guide, the new SAA-C03 exam guide contains a lot more information about what is in and out of scope. It also includes detailed information on what knowledge you should have for each domain, as well as the skills required to meet the domain’s requirements. Let us now look at some common queries –
Is this a beta Exam?
There is no beta for the new exam, which is unusual, and they are going straight from the SAA-C02 to the SAA-C03 with no overlap. As a result, you must either pass your SAA-C02 on or before August 29th, 2022, or study for the SAA-C03 and book your exam on or before August 30th, 2022.
Will the exam include exam labs or hands-on labs?
In the most recent update to the AWS Certified SysOps, Administrator Associate certification AWS introduced hands-on questions where you must use the AWS Management Console to complete a series of tasks. Some expected the new versions of other certifications to also include exam labs. They have not included exam labs in the new exam guide for the SAA-C03 so it looks like it will be multiple choice and multiple response questions only.
How can you prepare for the exam?
There are some resources that you can use to prepare –
Whitepapers
Candidates preparing for the AWS can benefit from AWS whitepapers. These are legitimate study resources that can help candidates understand AWS services. Whitepapers, on the other hand, are essentially pdf versions of the topics found on Amazon’s official certifications page. Whitepapers not only help you prepare better, but they also help you develop a strong strategy to focus on. Furthermore, AWS provides sample papers to candidates to help them gain additional knowledge and skills in preparation for certification exams.
AWS Training
AWS provides candidates with training to help them develop competence, confidence, and credibility through practical cloud skills. Candidates can learn at their own pace online or from an accredited AWS instructor built by AWS experts. This will be beneficial to both novices looking to improve their existing IT skills and professionals with cloud knowledge.
Practice tests
Finally, we reach the crux of your preparations: the AWS Certified Advanced Networking – Specialty Practice Tests. This is an important component that will help you prepare for the exam better. In other words, practice tests are useful because they allow you to assess your own weaknesses and strengths. So, by practicing, you will be able to improve your answering skills and save a significant amount of time.
