Building Systems that Last

Amazon's first system was a single monolith. Its failure sparked a 30-year evolution that ultimately led to the creation of AWS.

#1about 9 minutes

Amazon's early monolith and database scaling challenges

The initial architecture of Amazon.com was a single monolith with a battery of relational databases that created a significant scaling bottleneck.

#2about 4 minutes

Decomposing the monolith into a service-oriented architecture

Amazon's first major architectural shift involved breaking the monolith into services, but an initial data-driven decomposition created new, large services that became bottlenecks themselves.

#3about 3 minutes

From microservices to infrastructure as a service

The move to smaller microservices improved developer productivity until the overhead of managing capacity and databases for each service led to the creation of internal infrastructure as a service platforms.

#4about 6 minutes

Designing for evolvability to accommodate future changes

Systems must be designed with evolvability as a core principle, allowing for continuous change and feature additions without downtime, as exemplified by Amazon S3.

#5about 4 minutes

Implementing cell-based architectures to isolate failures

A cell-based architecture isolates failures by partitioning customers and infrastructure into independent, self-contained units, thereby limiting the blast radius of any single outage.

#6about 3 minutes

Using sharding to dramatically reduce blast radius

By mapping customers to multiple overlapping cells (sharding), the blast radius of a failure is reduced from a fraction of cells to a much smaller fraction based on mathematical combinations.

#7about 4 minutes

Making cost a non-functional requirement in system design

Frugality is a key architectural driver where cost is treated as a primary non-functional requirement, and making cost metrics visible to engineers changes their behavior and improves efficiency.

#8about 3 minutes

How programming language choice impacts cost and sustainability

The choice of programming language has a significant impact on system cost and energy efficiency, with languages like Rust offering major advantages in performance and security over others like Python or Ruby.