Workflow orchestration

Create Workflow instance batches by count or list

createBatch() now accepts an options object that creates up to 100 Workflow instances in one call. The result lists the created instances and explains why any others were not created.

Call Workflows declared in `exports` through `ctx.exports`

A Worker can now call the Workflows it declares in the exports field of its Wrangler configuration through ctx.exports. You no longer need a workflows binding to call a Workflow from the Worker that defines it.

Declare Workflows in the `exports` configuration

You can now declare the Workflows a Worker defines in the exports field of your Wrangler configuration file. Previously, a Worker could only define a Workflow through a workflows binding, even when the Worker never called the Workflow itself.

Delete Workflow instances individually or in batches

You can now delete one or up to 100 Workflow instances and their stored state via the Workflows API or Wrangler 4.125.0 and later. Deleting an instance frees its stored state and stops its current execution. Storage billing is based on the average daily peak.

AWS Step Functions adds new AWS service integrations automatically, starting with AWS Lambda MicroVMs

AWS Step Functions now automatically adds AWS SDK integrations for new AWS services and capabilities within weeks of their release, starting with AWS Lambda MicroVMs, AWS Lambda Core and others.

Stream Workflow instance events in your Worker or via the API with.subscribe()

You can now stream Workflow instance events via WorkflowInstance.subscribe() and the GET /subscribe API endpoint. Workers and HTTP clients can react to workflow and step events, including attempts, sleeps, waits, and rollbacks, without polling for instance status.

Default instance retention for new Workflows on Workers Paid is seven days

Workflows created on or after September 10, 2026, on the Workers Paid plan retain completed and errored instance state for seven days by default (previously 30 days). The seven day default helps to reduce storage costs by default. The maximum retention limit remains 30 days.

Build and deploy Artifacts repos on every push

You can now run your CI/CD pipeline on your Artifacts repo by defining a CI Workflow with the CI SDK, automatically triggered on Artifacts push events.

Workflows now supports delay functions when retrying

With Workflows, you can configure built-in retry behavior for each step. Previously, you could configure step retries with fixed delay durations, such as seconds, minutes, or hours, and backoff strategies such as constant, linear, or exponential.

Workflows pricing adds per-step billing. Step and storage billing to start no earlier than August 10, 2026.

Workflows pricing now includes per-step billing. Requests and CPU time billing have been enabled since the initial public beta and is not changing.

Workflows rollback handlers now include step context

Workflows makes it easier to build reliable multi-step applications that can recover when downstream systems fail. Rollback handlers now receive the original step context via a ctx object for the step being rolled back.

Rollback support now available in Workflows

Workflows now supports saga-style rollbacks, allowing you to add compensating logic to each step.do() in case of downstream failures. If the instance fails, the rollback handlers will execute in reverse step-start order.

AWS Step Functions adds AgentCore-powered agentic reasoning step

AWS Step Functions now enables you to add AI agent reasoning steps to your workflow through an optimized integration with the managed harness (currently in preview) in Amazon Bedrock AgentCore.

Public Preview: Azure Functions now includes managed connectors to integrate with 1400+ of your favorite systems

Azure Functions now includes managed connectors - the same 1,400+ connector ecosystem behind Logic Apps and Power Platform - as first-class triggers and operations.

Public Preview: Azure Logic Apps Codeful Workflows with Logic Apps Standard SDK.

Modern integration and automation teams increasingly want the flexibility of writing workflows directly in code while still benefiting from managed orchestration, enterprise connectors, and cloud-scale operational capabilities.

Generally Available: Azure Logic Apps MCP Server.

As organizations adopt AI agents and MCP-based tooling, integration teams often need to build and maintain custom API layers just to make existing workflows callable by agents. This additional plumbing increases development effort, operational complexity, and time to production.

Public preview: Connector Namespace

Integrating apps with SaaS and line-of-business systems today means writing custom API client code, managing credentials, and handling retries, pagination, and webhooks for every service.

Public Preview: Azure Logic Apps Automation SKU for agentic business process automation.

As organizations move toward agentic automation, developers increasingly need a simpler way to combine workflows, APIs, and AI agents into production-ready business processes.

Public Preview: Knowledge as a Service with Azure Logic Apps.

Most RAG implementations today are complex. Teams must build ingestion pipelines, manage chunking and embeddings, configure vector stores, wire up retrieval layers, and then operate the entire system in production.

Public Preview: Azure Logic Apps now enables developers to invoke Microsoft Foundry Agents directly from workflows.

Organizations building AI agents often face a disconnect between where agents are built and where business processes are automated.