![]() AWS Certified DevOps Engineer – Professional (DOP-C02): Focuses on continuous integration and continuous delivery (CI/CD) on AWS.Īdvanced understanding of DevOps principles, experience with AWS development and operations tools, and automation skills.ĭesign, build, and automate the delivery of complex and scalable applications on AWS using CI/CD pipelines and infrastructure as code.Troubleshooting complex systems and issues.Monitoring and logging for large-scale architectures.Continuous integration and continuous delivery (CI/CD) pipelines. ![]() ![]() High availability and disaster recovery for mission-critical systems.Cost optimization strategies and automation.Security in depth and compliance considerations.Designing multi-tier and enterprise-scale architectures.Advanced design principles and best practices for building on AWS (Well-Architected Framework).Specialty-level certifications or leadership roles in cloud environments Multiple-choice and hands-on lab questions on designing secure, scalable, cost-optimized, and fault-tolerant architecturesĮxperienced cloud architects, solutions architects, IT architects, and senior DevOps engineers Experience designing and deploying cloud solutions is encouraged.ĭesign, build, and deploy highly-complex enterprise solutions on AWS based on the Well-Architected Framework AWS Certified Solutions Architect – Professional (SAP-C02): Covers advanced design and deployment of enterprise-level solutions on AWSĪdvanced understanding of AWS services and architecture principles.Professional (Validate advanced skills and experience): AWS database services (Amazon RDS, Amazon DynamoDB, Amazon Aurora, Amazon Neptune).Specialty-Level Database Certifications or AWS Certified Solutions Architect – Professional (SAP-C02) Multiple-choice and hands-on lab questions covering database design, migration, deployment, operations, security, and troubleshootingĭatabase administrators, database developers, cloud architects, and DevOps engineers AWS Certified Database – Associate (DBS-C01): Focuses on working with relational and non-relational databases on AWS.īasic knowledge of database concepts and SQLĭesign, manage, and maintain relational and non-relational databases on AWS.Security and compliance for data on AWS.Machine learning basics and Amazon SageMaker.Data visualization with Amazon QuickSight.Data analysis with SQL and Amazon Athena.Data ingestion and transformation using AWS Glue and Lambda.AWS data analytics services (Amazon Redshift, Amazon Elasticsearch Service, Amazon Kinesis).Specialty-Level Data Analytics Certifications, AWS Certified Machine Learning – Specialty (MLS-C01) ![]() Multiple-choice and hands-on lab questions on data ingestion, storage, analysis, and visualizationĭata analysts, data scientists, developers, and business users wanting to leverage AWS for data analytics
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