Category Archives: Amazon

Amazon CloudFront is often introduced as a content delivery network, but that definition is too shallow for architecture work. In an SAA-C03 design, CloudFront changes where requests terminate, how often origins are contacted, what data is cached, and which request attributes become part of the cache key. It can improve performance and reduce origin load, […]

Amazon Route 53 routing policies are easiest to understand when DNS is treated as a decision layer rather than as a traffic proxy. For SAA-C03 architecture work, the important question is what information Route 53 can use when answering a DNS query and what the client will do with that answer afterward. The service can […]

Distributed systems become easier to reason about when messaging is treated as an architectural contract rather than as a menu of AWS services. In the SAA-C03 context, the useful question is not whether Amazon SQS, Amazon SNS, or Amazon EventBridge can move a message. All three can participate in event-driven designs. The harder question is […]

Event-driven architecture diagrams are appealing because every box appears independent. A producer emits an event, a queue or bus carries it, Lambda runs some code, and another service receives the result. The difficult parts are hidden between the arrows: duplicate delivery, retries, backpressure, ordering, poison messages, concurrency, partial failure, schema changes, and the question of […]

DynamoDB performance problems are often blamed on “not enough capacity” when the real issue is how requests are distributed. A table can have plenty of aggregate throughput and still throttle a hot partition. Conversely, a team can overprovision read and write capacity while inefficient access patterns consume far more units than the application actually needs. […]

Aurora is easy to describe as a managed relational database compatible with MySQL or PostgreSQL. That description is accurate but architecturally incomplete. The useful distinction is that Aurora separates compute instances from a distributed cluster volume. The writer and readers connect to the same logical storage system, while the storage layer replicates data across Availability […]

“Use Multi-AZ for availability and read replicas for scale” is a useful starting sentence, but it has become too simple for the current RDS landscape. A traditional Multi-AZ DB instance deployment has a standby that exists for failover and does not serve application reads. A Multi-AZ DB cluster, by contrast, has a writer and two […]

EBS, EFS, and EC2 instance store can all appear next to an EC2 workload, but they represent different persistence and sharing models. Choosing among them by price per gigabyte or a single performance number misses the design boundary. The important questions are whether data must survive instance replacement, whether multiple hosts need concurrent access, which […]

An S3 Lifecycle rule is easy to create and easy to get wrong. The dangerous version is a rule built from a price table rather than from the behavior of the data. A team sees a cheaper storage class, chooses an age threshold, and assumes the bill will fall. Later it discovers minimum-duration charges, retrieval […]

Choosing an AWS load balancer is not a contest between Application Load Balancer and Network Load Balancer feature lists. The decision starts with the traffic itself: which protocol the client speaks, where TLS should terminate, whether routing needs application context, whether source addresses must be preserved, how targets scale, and whether the “load balancer” is […]

EC2 cost decisions are often framed as a pricing problem, while scaling decisions are framed as a performance problem. In a real workload they are the same architecture problem viewed from two sides. The way a fleet scales determines how much stable usage exists to commit to, how much interruptible capacity is safe, which instance […]

Security groups and network ACLs are often taught as a comparison table: stateful versus stateless, resource-level versus subnet-level, allow-only versus allow-and-deny. Those differences are accurate, but they do not answer the harder design question. An architect needs to know which control should carry the everyday access policy, which one should provide a coarse boundary, and […]

A VPC diagram can look correct and still encode years of future friction. The lines between subnets may be neat, the route tables may have the expected default routes, and every workload may launch successfully on day one. The problems arrive later, when a new Availability Zone is added, an acquisition introduces overlapping address space, […]

AWS IAM becomes difficult when permissions are treated as a pile of JSON documents. The better mental model is an authorization decision. A principal makes a request to perform an action on a resource in a specific context. AWS gathers the policies that apply, evaluates explicit denies, determines which policies can grant or limit permission, […]

Amazon AWS AIP-C01: CI/CD Change Control for Generative AI A conventional application pipeline can look healthy while an AI application quietly changes behavior. A container image may be identical, an API contract may be unchanged, and every deployment check may pass, yet a new prompt, retrieval configuration, model version, embedding model, guardrail policy, or evaluation […]