Best of AWS — September 2025

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   Video

   CodeHead·35w

   Should YOU Become a Backend Dev?

   Backend development in 2025 involves managing complex microservices architectures, cloud infrastructure, AI integrations, and security concerns. While the core responsibilities remain building APIs and managing databases, developers now juggle dozens of services, navigate extensive cloud platforms like AWS, and handle AI model integrations. The role has expanded to include security engineering responsibilities, with constant focus on preventing data breaches. Despite the challenges of debugging distributed systems and handling 3 AM alerts, backend developers remain essential for keeping internet infrastructure running smoothly.

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   Article

   System Design Codex·32w

   How Amazon S3 Works Behind the Scenes

   Amazon S3 processes millions of requests per second and stores over 350 trillion objects using a microservices architecture. The system consists of five main layers: front-end services for request handling and authentication, metadata services for object indexing, storage services using erasure coding across multiple availability zones, durability services with checksums and auditing, and security services with IAM policies and encryption. This modular approach enables independent scaling and updates while achieving 11 nines of durability.

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   Article

   Hacker News·35w

   Will Amazon S3 Vectors Kill Vector Databases—or Save Them?

   AWS S3 Vectors offers 90% cost savings for vector storage but won't replace dedicated vector databases like Milvus. Instead, it fills the cold storage tier in a three-tier architecture (hot/warm/cold) that balances latency, cost, and scale. S3 Vectors excels at low-QPS scenarios and archival storage but struggles with high-performance search, frequent updates, and complex queries. The future lies in tiered vector storage where different solutions serve different performance and cost requirements.

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   Article

   InfoWorld·34w

   AI developer certifications tech companies want

   AI certifications are becoming increasingly valuable for developers as companies integrate AI into mainstream workflows. While not a guarantee for landing jobs, certifications from major platforms like AWS, Google, Microsoft Azure, and NVIDIA can help candidates stand out, especially for early-career developers. Industry experts emphasize that certifications work best when combined with practical experience and serve as validation of baseline competencies in rapidly evolving AI technologies. Popular certifications include AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, and Microsoft Azure AI Engineer Associate.

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   Video

   Tech With Lucy·34w

   The Future of Databases is here... (What you need to know)

   Modern databases are evolving to handle both transactional and analytical workloads in real-time, eliminating the need for complex multi-database architectures. Traditional setups require separate systems for applications and analytics, causing data delays and increased complexity. New unified database platforms can process transactions, run analytics, and support AI workloads simultaneously, enabling instant dashboards, real-time fraud detection, and live inventory systems. The future points toward databases that natively support vector search, unstructured data, and AI workloads without requiring multiple tools or complex data pipelines.

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