Best Cloud Infrastructure Automation Software for Chef

Find and compare the best Cloud Infrastructure Automation software for Chef in 2025

Use the comparison tool below to compare the top Cloud Infrastructure Automation software for Chef on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

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    JFrog Platform Reviews

    JFrog Platform

    JFrog

    $98 per month
    An entirely automated DevOps platform designed for the seamless distribution of reliable software releases from development to production. Expedite the onboarding of DevOps initiatives by managing users, resources, and permissions to enhance deployment velocity. Confidently implement updates by proactively detecting open-source vulnerabilities and ensuring compliance with licensing regulations. Maintain uninterrupted operations throughout your DevOps process with High Availability and active/active clustering tailored for enterprises. Seamlessly manage your DevOps ecosystem using pre-built native integrations and those from third-party providers. Fully equipped for enterprise use, it offers flexibility in deployment options, including on-premises, cloud, multi-cloud, or hybrid solutions that can scale alongside your organization. Enhance the speed, dependability, and security of software updates and device management for IoT applications on a large scale. Initiate new DevOps projects within minutes while easily integrating team members, managing resources, and establishing storage limits, enabling quicker coding and collaboration. This comprehensive platform empowers your team to focus on innovation without the constraints of traditional deployment challenges.
  • 2
    Resolve Reviews

    Resolve

    Resolve Systems

    Resolve is the number one IT automation and orchestration platform. It powers more than a million automations every single day, from simple, high-volume tasks, to complex processes that go far beyond what you think is possible. We have more than a decade experience in automation and know how to create an intelligent automation platform and orchestration platform to meet today's growing demands of IT Operations and Network Operations teams. Resolve powers millions of automations every day, many of which go far beyond what you might imagine is possible. It sounds impossible, but it is true. Ask the customers who have cracked the code to automate complex tasks such as PIM testing, updating active loads balancers, CUCM Onboarding in seconds, true end–to-end patch management and interfacing with Watson for NLP. They also maintain infrastructure in segregated networks or hybrid cloud deployments. Continue reading to learn how we do it.
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    Canonical Juju Reviews
    Enhanced operators for enterprise applications feature a comprehensive application graph and declarative integration that caters to both Kubernetes environments and legacy systems. Through Juju operator integration, we can simplify each operator, enabling their composition to form intricate application graph topologies that handle complex scenarios while providing a user-friendly experience with significantly reduced YAML requirements. The UNIX principle of ‘doing one thing well’ is equally applicable in the realm of large-scale operational code, yielding similar advantages in clarity and reusability. The charm of small-scale design is evident here: Juju empowers organizations to implement the operator pattern across their entire infrastructure, including older applications. Model-driven operations lead to substantial savings in maintenance and operational expenses for traditional workloads, all without necessitating a shift to Kubernetes. Once integrated with Juju, legacy applications also gain the ability to operate across multiple cloud environments. Furthermore, the Juju Operator Lifecycle Manager (OLM) uniquely accommodates both containerized and machine-based applications, ensuring smooth interoperability between the two. This innovative approach allows for a more cohesive and efficient management of diverse application ecosystems.
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