You avoid doubling ops work by keeping one deployment workflow, one identity and secrets model, one observability stack, and one on-call process for both providers, and by changing only the provider-s
In production, an AI agent’s cost is model tokens plus the infrastructure around them (orchestration services, code-execution sandboxes, networking, storage, and observability), and at moderate scale
Choose an inference deployment option by model type (proprietary vs open-weight), traffic shape, latency target, model features, data control requirements, and cost model. Managed model APIs are the f
Choose an AI agent sandbox by isolation strength, startup and lifetime behavior, state persistence, network and secret controls, and how it fits the tools and clouds you already use. Sandboxes are for
Business continuity for high availability services across on premises and cloud requires an application availability layer that keeps services running across sites, combined with data protection, reco
Get the benefits of Kubernetes by buying the layers a platform team would build: an automated managed Kubernetes tier that runs nodes for you, or a platform that delivers the same outcomes with no clu
Roll back a bad change by redeploying the last known-good version through the same pipeline that shipped the broken one, which only works if every deploy is versioned, health-gated, and reversible, an
A compliant application platform gives you audited infrastructure controls, but compliance is shared: you still need your own controls for data classification, identity, secrets management, and loggin
Structure multi-cloud governance as layered policy as code, with the same written rules enforced at four points: in the editor and pull request, in the CI plan check, at deploy or admission time, and