Modern digital products operate at unprecedented scales, processing enormous amounts of data and transactions daily. With such scale, failure poses serious risks to businesses and user experience. Service Level Objectives (SLOs) help define measurable metrics reflecting user experience. Reliability in this context signifies consistent performance, which is subjective and varies based on user perception of responsiveness and availability. Engineers need to consider various factors like asynchronous processing and dependencies when defining success metrics and ensuring that services perform reliably under load.
Reliability is the probability that a service will consistently perform as expected over a defined period of time. But to make that definition useful in practice, you need to answer two key questions: What exactly counts as "good enough"? And how do you measure it?
From a user's perspective, "good enough" is a moving target. Is the app responsive enough? Are key features always available? At what point does a delay or failure become noticeable - or, worse, frustrating?
System behavior needs to be measurable, observable, and predictable. One of the most effective tools for achieving that is the Service Level Objective (SLO).
Defining metrics that truly reflect user experience, especially in a high-load distributed system, requires an understanding of complex factors such as asynchronous processing, caching, sharding, and external dependencies.
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