argoproj/argo

Features

• Kubernetes Job Orchestration - Orchestrates multi-step sequences of containers as isolated Kubernetes jobs using directed acyclic graphs.
• Directed Acyclic Graph Engines - Orchestrates complex container task dependencies by resolving a directed acyclic graph for execution sequence and parallelism.
• Job Schedulers - Triggers automated container workflows based on cron schedules or real-time external event triggers.
• Event-Driven Automation Engines - Triggers automated workflows in real time in response to external webhooks and API calls.
• CI/CD Automation Servers - Functions as a centralized platform orchestrating the building, testing, and declarative deployment of software.
• Container Workflow Orchestration - Manages distributed containerized tasks including data artifacts, resource placement, and complex execution logic.
• Workflow Orchestration - Manages the execution, state, and sequencing of complex multi-step automated workflows across a distributed cluster.
• Continuous Delivery Engines - Automates the synchronization of application state from version control to infrastructure for continuous delivery.
• Custom Resource Definitions - Defines workflow specifications as Kubernetes native objects that the controller monitors and synchronizes.
• Canary Deployment Controllers - Implements progressive release strategies by incrementally routing network traffic from old to new deployments.
• Progressive Delivery Strategies - Reduces release risk through automated Canary and Blue-Green deployment strategies.
• Event-Driven Workflow Triggers - Launches automated pipelines by mapping incoming webhooks and external signals to predefined workflow templates.
• GitOps Controllers - Automates application delivery by mirroring the state of a git repository directly into the cluster environment.
• Workflow Orchestrators - Defines and executes multi-step containerized task sequences as directed acyclic graphs within a Kubernetes cluster.
• Kubernetes Application Deployments - Synchronizes cluster state with configuration sources to automate continuous delivery of containerized applications.
• Workflow Event Triggers - Provides mechanisms for initiating automated workflows via webhooks, API calls, and external system events.
• State Reconciliation - Continuously synchronizes the actual cluster state with the desired workflow specification to trigger necessary actions.
• Batch Processing Schedulers - Runs recurring jobs on a fixed timetable using cron-based schedules for routine maintenance and data tasks.
• Cron Scheduling - Supports automated workflow instantiation based on standard cron calendar expressions.
• Workflow Data Pipelines - Passes parameters and artifacts between pipeline steps using cloud storage to maintain state.
• Workflow Schedulers - Automates the execution of workflows on a fixed timetable using standard cron-based schedules.
• Execution Flow Controls - Regulates resource consumption and pipeline logic using loops, conditionals, and timeouts.
• Inter-Step State Passing - Enables the movement of state and files between isolated containerized steps using cloud storage payloads.
• Workflow Run Management - Provides utilities to visualize execution progress, archive completed runs, and trigger retries for failed steps.
• Workflow Orchestration - Container-native workflow engine for Kubernetes orchestration.
• Automation and CI/CD - Container-native engine for orchestrating parallel workflows.
• Build Automation - Container-native workflow engine for Kubernetes.
• Continuous Delivery and GitOps - Workflow engine for container-native tasks on Kubernetes.

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