🤖AX Agents: Google's New Workload Type for Billions of Tasks
Google's AX Agents: A New Era for Task Workloads
TL;DR
Google's AX Agents offer a new kind of workload, neither microservices nor batch jobs, designed for massive density and fast stateful actor lifecycles. AX scales up to billions of tasks, providing sub-second resumption and dense multiplexing.
Google's AX Agents introduce a new kind of workload, designed for massive density and fast stateful actor lifecycles. AX allows for single tasks per agent or composing multiple tasks, and it scales up to billions of tasks. This is a big deal for developers and researchers who need to run untrusted agent code in a sandbox with strict isolation and CPU and memory limits. AX provides sub-second resumption for idle agents and dense multiplexing, turning idle waiting time into spare compute capacity. AX is built for ergonomics, rapid iteration, and joyful workflows, making it a game-changer for teams working with agent execution.
Key Points
AX Agents run tasks at scale, allowing for single tasks per agent or composing multiple tasks.
AX Agents apply tasks using the 'ax apply' command and create workspaces with 'ax create'.
AX Agents watch tasks with 'ax watch', get tasks with 'ax get', suspend tasks with 'ax suspend', and resume tasks with 'ax resume'.
AX Agents accumulate state, require strict isolation, and can burn money in a loop, but they offer sub-second resumption for idle agents.
AX Agents integrate generative AI directly into the platform, providing dense multiplexing and turning idle waiting time into spare compute capacity.
Why It Matters
If you're running complex workloads that require massive density and fast stateful actor lifecycles, AX Agents are a must-look. AX scales up to billions of tasks, providing sub-second resumption and dense multiplexing. This is a game-changer for teams working with agent execution, offering a new kind of workload that is neither microservices nor batch jobs.
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