Platform engineering
Also known as Platform engineering practice
Definition
Platform engineering is the practice of building and operating internal platforms that give software teams self-service ways to provision, develop, test, deploy, and run applications. It treats the platform as a product for internal developers and aims to reduce unnecessary cognitive load.
A platform is an internal product
Platform engineering creates a supported path through infrastructure and delivery complexity. The platform may provide templates, environments, service configuration, deployment workflows, observability, security controls, and documentation. Developers use those capabilities as customers, while the platform team maintains the service and its interfaces.
The goal is self-service with useful guardrails. A good platform removes repeated plumbing and makes the safe path easy to follow. It should preserve enough context for teams to understand what will happen and how to recover when the default does not fit.
Measure adoption and outcomes
Count of platform users or provisioned services is only an adoption signal. Pair it with time to create or change a service, failure and retry rates, support requests, developer feedback, and the delivery outcomes of teams using the platform. Compare adopters with a relevant baseline and account for differences in service type and maturity.
How Weave can help
Weave provides the development and delivery context for a platform experiment. A team can examine whether a new template or workflow changes pull request size, review waiting, code quality, cycle time, rework, or deployment patterns. Those signals help locate a change in the system. They do not replace platform telemetry, usage data, or conversations with developers about what became easier or harder.
How this relates to Weave
Weave can help a platform team see whether a platform change is associated with shorter delivery queues, smaller amounts of rework, faster review or deployment flow, and better quality signals. Use those observations with platform adoption data and developer feedback to understand whether the platform is making the intended work easier.
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