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3 مستودعات

Awesome GitHub RepositoriesCloud Execution Environments

Provides managed cloud infrastructure for dynamically scaling workflow task execution.

Distinct from Infrastructure Add-ons: Focuses on the execution environment for workflows, distinct from general infrastructure add-ons.

Explore 3 awesome GitHub repositories matching devops & infrastructure · Cloud Execution Environments. Refine with filters or upvote what's useful.

Awesome Cloud Execution Environments GitHub Repositories

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  • prefecthq/prefectالصورة الرمزية لـ PrefectHQ

    PrefectHQ/prefect

    21,640عرض على GitHub↗

    Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep

    Allows scaling workflow execution on managed cloud infrastructure.

    Pythonautomationdatadata-engineering
    عرض على GitHub↗21,640
  • j3ssie/osmedeusالصورة الرمزية لـ j3ssie

    j3ssie/Osmedeus

    6,425عرض على GitHub↗

    Osmedeus is a security workflow orchestration engine that coordinates AI agents, shell commands, and scanning tools through declarative YAML pipelines. It functions as a distributed security scanner, a declarative workflow automator, and an AI agent framework for security, enabling automated multi-step security analysis with conditional branching, parallel execution, and distributed workers. The engine distinguishes itself through a hybrid runner model that executes workflow steps on the local host, inside Docker containers, or over SSH to remote machines, selected per step or module. It supp

    Executes named security workflows against targets on provisioned cloud workers.

    Go
    عرض على GitHub↗6,425
  • maiot-io/zenmlالصورة الرمزية لـ maiot-io

    maiot-io/zenml

    5,452عرض على GitHub↗

    ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself

    Defines runtime environments that pair cloud compute backends with durable storage providers for agent execution.

    Python
    عرض على GitHub↗5,452
  1. Home
  2. DevOps & Infrastructure
  3. Infrastructure Add-ons
  4. Cloud Execution Environments

استكشف الوسوم الفرعية

  • Security Scan ExecutionsRuns predefined or custom security scanning workflows across provisioned cloud instances. **Distinct from Cloud Execution Environments:** Distinct from Cloud Execution Environments: focuses on executing security scan workflows specifically, not general workflow task execution.
  • Security Workflow ExecutionsRuns YAML-defined security workflows across cloud instances and syncs results back locally. **Distinct from Cloud Execution Environments:** Distinct from Cloud Execution Environments: focuses on executing YAML-defined security workflows, not general workflow task execution.
  • Security Workflow Executions on Cloud InstancesExecutes a named flow or module against a target on one or more provisioned cloud workers. **Distinct from Cloud Execution Environments:** Distinct from Cloud Execution Environments: focuses on executing security workflows on cloud instances, not general workflow task execution.