SAA-C03, the AWS Certified Solutions Architect \u2013 Associate exam, assesses the ability to design secure, resilient, high-performing and cost-effective systems. It is not a test of memorizing console buttons. The labs in this article ask you to make and justify architecture decisions, then verify them under normal and failing conditions.<\/p>\n
Use only an authorized sandbox or personal test account. Cloud resources can incur charges even when an experiment is idle; never assume a Free Tier allocation covers every configuration. Each lab should produce a simple diagram, a stated requirement, observed test evidence, a cost estimate and a record of resource cleanup.<\/p>\n
The current SAA-C03 guide weights secure architectures at 30 percent, resilient architectures at 26 percent, high performance at 24 percent and cost optimization at 20 percent. Many problems span several domains. A database design affects cost, security, failover and application latency simultaneously, so do not organize your understanding as isolated service definitions.<\/p>\n
Write a one-paragraph workload description before building anything: the data classification, expected demand, failure tolerance, target recovery time, recovery point and budget. Compare two plausible designs. Make a prediction before a fault test, record what happened and explain which requirement would change your choice. A green dashboard is not evidence that a service meets a business objective.<\/p>\n
Protect the account’s root identity with multifactor authentication and use appropriately scoped roles for daily activity. Avoid long-lived credentials and production customer data. Tag test resources by owner and deletion date, set billing alerts, and inspect the current region’s charges for public addresses, databases, NAT gateways, load balancers, storage and logging.<\/p>\n
Select CloudWatch metrics and CloudTrail events that can answer a specific question. Management events and detailed S3 object data events have different purposes and potentially different costs. Maintain a journal of both successful and denied requests. Teardown includes checking lingering snapshots, addresses, log groups, load balancers and gateways; closing the console does not delete infrastructure.<\/p>\n
Create public and private subnets in a VPC across two Availability Zones. Associate explicit route tables, then draw the packet path from a client to an application tier and from that tier to a database. A subnet’s label does not define its connectivity: routes, address assignment, gateways and filtering determine the actual exposure.<\/p>\n
Launch a small test application privately and choose an authorized administration path such as Systems Manager Session Manager, with its necessary endpoints and permissions. Limit inbound traffic with security groups and compare their stateful behavior with network ACL rules. Try a connection that must fail as well as one that must succeed.<\/p>\n
Use VPC routing and subnet isolation<\/a> to distinguish an internet gateway, outbound NAT gateway and VPC endpoint. They solve different connectivity needs. Verify that the private component can reach the intended service without accepting arbitrary inbound internet connections.<\/p>\n Record route-table decisions and any VPC Flow Log observations. If a request fails, identify the blocking layer rather than opening all ports. Remove the temporary VPC components and confirm that chargeable NAT gateways and public addresses are gone.<\/p>\n Deploy two small web instances in different Availability Zones behind an Application Load Balancer. Use an application-ready health endpoint, not merely a running host status. Configure an Auto Scaling group with a launch template and predict the effect of losing one instance on both existing and new requests.<\/p>\n Terminate a test instance through an authorized exercise and observe replacement time, target health and user-facing interruption. Next, make the application health endpoint fail without stopping the machine. The difference illustrates why an operating system can be healthy while the application is not capable of serving customers.<\/p>\n An EC2 Auto Scaling configuration<\/a> depends on subnet placement, health checks, launch permissions and policy settings. Use modest synthetic demand to observe scaling. Do not extrapolate a production throughput guarantee from a few minutes of sandbox traffic.<\/p>\n Compare the resilience gain against added cost. Application sessions kept only in the memory of one replaceable instance may be lost after failover. Explain when a shared session store, stateless design or improved draining behavior would be justified.<\/p>\n Create a private S3 bucket with Block Public Access and appropriate ownership controls. Upload harmless objects and inspect their encryption settings. S3 already encrypts new uploads with SSE-S3 by default; switching to SSE-KMS addresses different key-control requirements and can introduce separate permissions and request costs.<\/p>\n Test Amazon S3 server-side encryption<\/a> independently from access restrictions. An unauthorized read should be denied even if the object is encrypted. Then perform an allowed read with a narrowly scoped identity and document which bucket, IAM and key permissions were necessary.<\/p>\n Use CloudFront with a suitable private S3 origin access configuration to distribute permitted objects. A website endpoint and a REST origin have different behavior. Confirm clients cannot bypass the planned path to fetch protected objects, and test whether a changed object is still served from cache.<\/p>\n Set a lifecycle rule on disposable objects and describe its expected future behavior; a short lab cannot prove a multi-day storage transition. Compare request, retrieval and retention charges for the chosen S3 class. Remove distributions, test objects and other resources when finished.<\/p>\n Create a private RDS test database containing synthetic rows, and document its engine, networking, authentication and backup settings. Verify one allowed application connection and one denied access path. The database should not become publicly reachable merely because a lab is easier to debug that way.<\/p>\n Compare RDS Multi-AZ and read replicas<\/a>. A Multi-AZ high-availability configuration and an additional replica for eligible read demand meet different objectives. A replica is not automatically equivalent to a synchronized failover arrangement.<\/p>\n Where supported, initiate a controlled failover and measure client interruption. Specify recovery time and recovery point objectives separately. Then restore a small backup to a new identifier and check its data and security posture; a completed backup job alone is not proof that restoration will meet a time requirement.<\/p>\n Compare the cost and failure coverage of the available topologies, including the consequences of a regional outage. Delete temporary databases and unnecessary retained snapshots under the sandbox’s retention policy.<\/p>\n Represent a small application stack in CloudFormation with parameters, resource tags, output values and narrowly scoped permissions. Deploy it and compare the resources with your original diagram. The purpose is a reproducible configuration whose assumptions can be inspected, not a large template filled with untested resources.<\/p>\n Before an update, create a change set. Review whether the change creates, deletes or replaces anything important. Understanding CloudFormation template changes<\/a> matters because a small property edit can require resource replacement, especially dangerous for a database without a verified recovery plan.<\/p>\n Cause a harmless template validation failure, inspect the error, then document rollback behavior. Stack rollback cannot reverse arbitrary changes to application data. Some retained resources or snapshots need separate cleanup after stack deletion.<\/p>\n Separate the deployment identity from the runtime application’s identity. Both need least privilege; narrow runtime permissions do not compensate for an overpowered provisioning role. Save the working template in version control.<\/p>\n Create a small workflow where a request is written to SQS and a Lambda consumer records a synthetic result. The queue allows the request to be accepted while processing is temporarily unavailable, but the worker still needs a clear retry and error-handling strategy.<\/p>\n Test Amazon SQS visibility timeouts and retries<\/a> by making the consumer fail once. Observe delivery again and configure a dead-letter queue for repeated failures. Standard queues may deliver more than once, so the worker must avoid duplicating harmful side effects.<\/p>\n Contrast this asynchronous flow with SNS fan-out to multiple subscribers and an API Gateway plus Lambda synchronous response. A file conversion can run in the background; an interactive decision may need an immediate answer. Match the pattern to the user’s actual requirements.<\/p>\n Send malformed test input and inspect logs for correct error handling and accidental exposure of sensitive values. Track queue age and invocation metrics. Delete temporary event source mappings, queues, functions and log groups.<\/p>\n Use a disposable domain or authorized hosted zone to compare Route 53 simple, weighted, latency and failover policies. The distinction between Route 53 latency and geolocation routing<\/a> matters: latency rules use AWS network measurements, while geolocation follows geographic rules configured by the operator.<\/p>\n Test a health-check-based failover if practical, and observe the selected resolver when the primary endpoint is unhealthy. DNS caches and existing connections may delay a client transition. Record TTLs, resolver choice and the limitations of a short demonstration rather than promising instantaneous global recovery.<\/p>\nLab 2: Measure load balancing and EC2 recovery<\/h2>\n
Lab 3: Secure S3 objects and deliver public assets safely<\/h2>\n
Lab 4: Differentiate database failover, replicas and restoration<\/h2>\n
Lab 5: Reproduce changes using CloudFormation<\/h2>\n
Lab 6: Examine SQS retry behavior with Lambda<\/h2>\n
Lab 7: Test DNS assumptions, cost and final design evidence<\/h2>\n