Work accumulates for as long as arrivals exceed completions. The wait an arriving request sees is decided by how fast capacity grows and by what holds intake while it grows.
Akka adds nodes to the cluster as load arrives and places the new work across them. Backpressure holds intake to the rate the system sustains during the gap, and scale-to-zero releases the added capacity once the spike passes.
Arrivals above the completion rate leave a difference, and that difference accumulates for as long as the gap is open. Every waiting item is behind the items ahead of it, so the wait grows faster than the backlog does.
Agent work drains slowly for reasons a request-serving system does not have. A single run holds a model call, a tool call, and often a chain of both, so it occupies its slot for seconds or minutes. A backlog of runs clears at that pace.
A fixed pool of capacity turns the spike into a decision an operator makes under pressure. Provisioning for the peak removes that decision and pays for peak capacity in every hour that is not the peak.
Akka Automated Operations delivers elastic scaling to 10 million agentic transactions per second with scale-to-zero, on shared compute that carries the agents, memory, orchestration and endpoints together. A spike raises the cores in use for the length of the spike.
Verizon raised order processing capacity by 750% and cut response times from 6 seconds to 2.4 seconds on Akka.
A queue holds work that has not started and gives an operator somewhere to watch the backlog. A queue adds no capacity, so what drains the backlog is the capacity the runtime added.
Runs in progress continue where they are, and arriving work goes to the added nodes. A run that is moved between nodes resumes from its last completed step.
New nodes take time to start and join, and backpressure holds intake during that window. The wait is bounded and visible for the length of the gap.
The system is held to the rate it sustains and the excess waits inside a bound somebody chose. The caller receives a defined wait or a refusal carrying a reason.
Scale-to-zero means idle capacity is not provisioned. Akka bills on platform tier and service cores, so a system with no traffic is not paying a per-service minimum.
