Designing IAM for distributed systems is rarely a matter of choosing the «right» technology. In practice, teams struggle with inconsistent identity propagation, unclear authorization boundaries, and approaches that work in isolation but fail once combined. Popular guidance often describes these patterns in isolation, leaving developers and architects to resolve contradictions and trade-offs on their own.
In this primer, Dimitrij Drus takes a pattern- and decision-driven approach to IAM architecture. Instead of promoting a single best practice, it focuses on how authentication, authorization, and identity propagation interact, and how architectural choices in one area directly affect security, operability, and failure modes in others.
Building on this perspective, the primer provides a structured way to reason about IAM patterns in distributed systems. It helps teams understand when a pattern fits, when it breaks, and which trade-offs they are implicitly accepting. By emphasizing architectural coherence over tooling decisions, it shows why resilient trust architectures require treating IAM concerns as connected design decisions rather than isolated implementations.
This concise guide covers, hands-on:
- Core IAM concepts and a reference architecture to establish a shared vocabulary
- Authentication patterns, focusing on architectural trade-offs rather than “one true way”
- Identity propagation patterns, including common failure modes and their impact on authorization
- Authorization patterns at different layers (edge, service, sidecar) and their operational implications
- Decision dimensions for selecting patterns systematically, such as policy characteristics, performance, and availability
- Practical recommendations, common pitfalls, and considerations for evolving IAM architectures
This primer is aimed at software architects, security engineers, platform and product teams, and developers—anyone tasked with designing or evolving trust foundations for distributed systems. It’s especially helpful for those looking for a pragmatic, cross-disciplinary framework for IAM decisions that hold up across architecture, operations, and governance.