SAP-C02 vs SAP-C03: every change in the new exam

SAP-C03 keeps the exam length, time and price and rebuilds the content around five discipline-based domains. It adds 37 skills, moves the rest of SAP-C02 into new tasks, and changes the in-scope service list. This page follows the comparison AWS publishes in the exam guide.

	SAP-C02	SAP-C03
Available	Until November 16, 2026	From November 17, 2026
Questions and time	75 questions, 180 minutes	75 questions, 180 minutes
Price and passing score	$300, 720	$300, 720
Domains	4, organized by situation	5, organized by discipline

Should you take SAP-C02 or SAP-C03?

Exam on or before November 16, 2026. If you already score well on SAP-C02 practice exams, sit SAP-C02. It is the same certification, valid for three years from the day you pass, and you avoid learning the AI and container material SAP-C03 adds in the days that remain.

Exam from November 17, 2026. SAP-C03 is the only version. Most SAP-C02 preparation carries over, because networking, identity, multi-account governance, migration and disaster recovery all remain; budget extra time for the generative AI task, the responsible AI controls and the container and observability skills listed below.

Domains and weights

SAP-C02 domain	%	SAP-C03 domain	%
1. Design Solutions for Organizational Complexity	26%	1. Architecture Design and Implementation Built for the Cloud	25%
2. Design for New Solutions	29%	2. Security, Compliance, and Governance	25%
3. Continuous Improvement for Existing Solutions	25%	3. Cost-Optimized Architecture Design	15%
4. Accelerate Workload Migration and Modernization	20%	4. Resilience, Migration, and Business Continuity	15%
–		5. Operational Excellence and Automation	20%

In SAP-C02 a security question could sit in any of the four domains. In SAP-C03 security, cost, resilience and operations each have a domain and a line on your score report, which makes a weak area easier to see.

The 37 skills added in SAP-C03

Wording from the official guide. The last column is how many questions in our bank test the skill.

Skill	Added content	Our questions
1.1.3	Design serverless data processing and analysis pipelines (for example, by using Amazon Kinesis Data Streams, AWS Glue, Amazon Athena, AWS Lambda).	2
1.1.4	Design multi-step workflows that have durable execution patterns (for example, by using AWS Step Functions, durable Lambda functions).	4
1.1.7	Design service mesh architectures that facilitate microservice communication and observability (for example, by using Amazon VPC Lattice, Amazon ECS Service Connect).	3
1.1.8	Manage container images by configuring security scans and lifecycle policies (for example, by using Amazon ECR).	2
1.1.10	Design ingress patterns and optimize resources for specific usage patterns (for example, Application Load Balancer, Network Load Balancer, AWS Load Balancer Controller, Amazon API Gateway).	2
1.1.12	Design architectures that support real-time data processing by using WebSocket and publish-subscribe patterns (for example, by using API Gateway WebSocket APIs).	2
1.1.13	Design multi-tenant architectures that use tenant isolation patterns (for example, siloed or pooled resources, Amazon Cognito tenant context, row-level security, tenant-specific encryption).	3
1.2.1	Design generative AI integrations for applications, including for multi-account deployment patterns (for example, by using Amazon Bedrock).	3
1.2.2	Design AI agent architectures that integrate with tools (for example, by using Amazon Bedrock AgentCore, Amazon Bedrock Knowledge Bases).	3
1.2.3	Design ML inference architectures (for example, Amazon SageMaker AI endpoints).	2
1.2.4	Design RAG architectures, including ingestion and retrieval strategies (for example, Amazon Bedrock knowledge bases that use vector stores).	3
1.3.5	Design hybrid compute patterns (for example, by using Amazon EKS Anywhere, Amazon ECS Anywhere, AWS Outposts, AWS Local Zones).	1
1.4.4	Design IPv6 adoption and dual-stack migration strategies.	2
1.5.1	Design data lake and lakehouse architectures (for example, by using Amazon S3, AWS Lake Formation, Amazon Redshift Spectrum, Apache Iceberg).	2
1.5.2	Design real-time and batch analytics pipelines (for example, by using Amazon EMR, Amazon Redshift, Amazon Managed Streaming for Apache Kafka [Amazon MSK], Amazon AppFlow).	1
1.5.7	Design data cataloging and cross-account data sharing patterns (for example, AWS Glue Data Catalog, Lake Formation, AWS Clean Rooms).	2
2.1.2	Design application authentication and authorization solutions (for example, by using Amazon Cognito user pools, identity pools, OAuth 2.0, Amazon EKS Pod Identity).	4
2.1.5	Design workload identities for hybrid and multi-cloud environments (for example, by using IAM Roles Anywhere).	3
2.2.4	Design post-quantum cryptography strategies (for example, by using AWS KMS with Module-Lattice Digital Signature Algorithm [ML-DSA], Module-Lattice-Based Key-Encapsulation Mechanism [ML-KEM]).	3
2.4.4	Design data residency controls such as AWS Region-specific deployments and transfer restrictions.	2
2.4.5	Implement compliance evidence collection and reporting solutions (for example, by using AWS Artifact).	2
2.4.6	Implement risk assessment solutions for cloud architectures such as threat modeling and mitigation strategies.	2
2.5.1	Implement content filtering and compliance controls for generative AI services (for example, by using Amazon Bedrock Guardrails).	5
2.5.2	Implement access controls for generative and agentic AI applications (for example, by using Amazon Bedrock AgentCore Identity).	4
2.5.3	Design human oversight workflows that include approval mechanisms for AI operations (for example, by using AWS Step Functions).	3
3.1.4	Optimize costs for AI/ML workloads by selecting the appropriate service tier, implementing batching strategies, and designing caching patterns (for example, by using Amazon Bedrock, Amazon SageMaker AI).	5
3.2.5	Optimize data transfer costs for AI/ML workloads by using strategies such as cross- Region inference routing.	2
3.4.5	Design cost-effective observability solutions that include features such as log filtering, metric aggregation, and retention optimization.	3
4.2.6	Implement multi-cluster container strategies to provide high availability and disaster recovery (for example, by using Amazon EKS, Amazon ECS).	6
5.2.2	Implement security scanning in pipelines to assess vulnerabilities and sign artifacts (for example, by using Amazon Inspector, Amazon ECR image scanning).	3
5.2.3	Configure multi-account and multi-Region deployment pipelines that include features such as role delegation and artifact promotion (for example, by using CodePipeline cross-account deployments).	5
5.2.4	Evaluate AI/ML applications and validate outputs (for example, by using Amazon Bedrock Evaluations).	3
5.3.2	Implement monitoring for containerized applications (for example, by using Amazon ECS, Amazon EKS with Container Insights).	3
5.3.5	Monitor metrics for AI/ML workloads, including model performance, AI agent performance, inference latency, and model drift.	3
5.3.6	Design monitoring solutions for the user experience by using strategies such as synthetic transactions and real user monitoring (for example, by using Amazon CloudWatch Synthetics, Amazon CloudWatch RUM).	2
5.4.2	Configure controlled remediation solutions that have safety constraints (for example, circuit breakers, rate limits, bulkhead patterns, retry patterns with exponential backoff).	4
5.4.5	Configure automated runbooks and incident response procedures for operational tasks such as patching, remediation, and scaling.	2

Where the SAP-C02 content went

SAP-C03 consolidates many SAP-C02 skills into fewer tasks. AWS states that the consolidation does not reduce the emphasis on these skills. Use this map to reuse your SAP-C02 notes.

SAP-C03 task	Content consolidated from SAP-C02
1.1 Design architectures built for the cloud	Task 1.4: Cross-account and cross-Region event routing patterns Task 2.4: Stateless applications with externalized state management; Auto scaling patterns for serverless and containerized workloads Task 3.3: Edge architectures for latency requirements Task 4.4: Event-driven architectures (messaging patterns, idempotency, ordering); Container orchestration for microservices
1.3 Design hybrid cloud integration patterns	Task 4.2: Data synchronization strategies for hybrid workloads Task 4.4: Integration patterns to modernize legacy systems
1.4 Design network architectures	Task 1.1: VPC architectures with subnet strategies and IP address management Task 1.2: Network security architectures (traffic inspection, filtering)
1.5 Design data, storage, and database architectures	Task 2.4: Database scaling solutions for high availability
2.1 Design identity security architectures	Task 1.2: Identity federation using standard protocols; Least-privilege access controls (cross-account access, temporary credentials); Data perimeter controls and external access validation
2.2 Design solutions to implement encryption and key management strategies	Task 1.2: Dedicated hardware security modules for compliance
2.3 Design multi-account governance and compliance solutions	Task 1.4: Organizational structures with guardrails and landing zones; Centralized logging and configuration management; Policy enforcement using SCPs and RCPs Task 3.2: Automated compliance monitoring
2.4 Design architectures to meet compliance requirements	Task 3.2: Solutions to meet regulatory requirements (data sovereignty); Audit trail management for regulated workloads
3.1 Design architectures based on AWS pricing models	Task 2.5: Rightsizing and scaling strategies based on performance Task 2.6: Cost-optimized architectures for workload requirements (Graviton, Step Functions, Lambda)
3.2 Optimize data transfer and network costs	Task 2.6: Data transfer cost optimization (private connectivity, Regional patterns); Cost-aware multi-Region data replication; Cost-effective network architectures (AWS Transit Gateway, AWS PrivateLink pricing) Task 3.3: Content delivery architectures and caching strategies
3.3 Design cost allocation and visibility solutions	Task 1.5: Policy-based tagging enforcement for cost allocation Task 3.5: Chargeback and showback capabilities; Cost monitoring and alerting solutions (budgets, anomaly detection)
3.4 Optimize storage and database costs	Task 1.3: Backup and disaster recovery with cost-optimized retention Task 2.6: Database cost optimization (capacity modes, reserved capacity); Intelligent storage tiering and lifecycle policies Task 3.5: Block storage cost optimization
4.1 Design migration strategies by using AWS frameworks	Task 4.2: Rehosting strategies Task 4.4: Refactor strategies (microservices decomposition, serverless adoption); Modernize legacy workloads (mainframes, applications, databases)
4.2 Design disaster recovery architectures	Task 2.2: Multi-Region disaster recovery solutions; Disaster recovery testing and validation procedures Task 3.1: Disaster recovery assessment and recovery procedures
4.3 Design solutions to meet business continuity and resiliency requirements	Task 1.4: Centralized backup governance and cross-account backup policies Task 3.1: Failover tests and recovery time measurement (AWS Fault Injection Service, Amazon Route 53); Chaos engineering with controlled failure scenarios Task 3.2: Data protection against ransomware and accidental deletion
5.1 Design infrastructure as code	Task 1.4: Multi-account and multi-Region infrastructure deployments Task 2.1: Infrastructure as code (declarative and imperative approaches) Task 3.2: Policy as code for validation, enforcement, and drift remediation; Secrets management in infrastructure code
5.2 Design CI/CD and DevSecOps pipelines	Task 2.1: CI/CD solutions for automated build and deployment pipelines
5.3 Design observability and monitoring solutions	Task 1.4: Multi-account log aggregation with cross-account subscriptions Task 3.1: Observability with metrics, logs, and distributed tracing Task 3.3: Service-level objectives (SLOs) with measurable indicators
5.4 Design operational automation and resilient systems	Task 2.4: Auto scaling policies (target tracking, predictive scaling) Task 3.1: Health monitoring, capacity planning, and operational responses

Content removed

Three items from SAP-C02 are no longer in the blueprint: application upgrade path and delegating to AWS (SAP-C02 domain 2, task 1) and migration-tool security (SAP-C02 domain 4, task 2). The guide notes that these concepts may still be implicit in other SAP-C03 skills.

Service list changes

Added to the in-scope list (20)

Amazon Bedrock, Amazon Data Lifecycle Manager, Amazon MemoryDB, Amazon Security Lake, Amazon Verified Permissions, Amazon VPC Lattice, AWS Application Auto Scaling, AWS CDK, AWS Clean Rooms, AWS Cloud WAN, AWS CodeCommit, AWS Cost Categories, AWS Data Transfer Terminal, AWS Distro for OpenTelemetry, AWS Fault Injection Service, AWS Local Zones, AWS Resilience Hub, AWS Transform, AWS Verified Access, Reserved Instances.

Removed from the in-scope list

All AWS IoT services (AWS IoT Core, AWS IoT Device Defender, AWS IoT Device Management, AWS IoT Events, AWS IoT Greengrass, AWS IoT SiteWise, AWS IoT Things Graph, AWS IoT 1-Click)
End User Computing (Amazon AppStream 2.0, Amazon WorkSpaces)
Media Services (Amazon Elastic Transcoder, Amazon Kinesis Video Streams)
Individual AI/ML services were replaced by Amazon Bedrock and Amazon SageMaker AI as parent entries (Amazon Comprehend, Amazon Fraud Detector, Amazon Kendra, Amazon Lex, Amazon Personalize, Amazon Polly, Rekognition, Amazon Textract, Amazon Transcribe, Amazon Translate).
Individual services: Amazon CodeGuru, Amazon Lightsail, Amazon Managed Blockchain (AMB), Amazon Pinpoint, Amazon SES, AWS Amplify, AWS App Runner, AWS Batch, AWS CodeArtifact, AWS Data Exchange, AWS Device Farm, AWS Health Dashboard, AWS License Manager, AWS Proton, AWS Service Catalog, AWS Wavelength.

Newly listed as out of scope

Amazon Braket, Amazon Comprehend Medical, Amazon Interactive Video Service (Amazon IVS), Amazon Lightsail, Amazon RDS Custom for Oracle, Amazon Transcribe Medical, AWS DeepComposer, AWS DeepRacer, AWS Elemental MediaConvert, AWS Elemental MediaLive, AWS Ground Station.

The full current list with our question counts per service is on the in-scope services page.

Sources: Comparison of SAP-C02 and SAP-C03 (AWS exam guide), AWS Training and Certification blog, September 2026.

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