> For the complete documentation index, see [llms.txt](https://docs.appfactor.io/52eJroWboQfTwsFl14gL/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.appfactor.io/52eJroWboQfTwsFl14gL/quickstart-guide/overview/features.md). # Features AppFactor’s end-to-end agentic orchestration platform is purpose-built for continuous software maintenance across complex enterprise environments. By combining full-stack contextual awareness - spanning infrastructure, runtime, application code, dependencies, and security posture - with enterprise-grade governance and control mechanisms, the platform enables organisations to systematically manage and reduce technical debt. Rather than treating maintenance as a reactive, manual effort, AppFactor automates discovery, assessment, remediation, containerisation, deployment, and validation within a controlled lifecycle framework. ## Discovery AppFactor automatically discovers applications, hosts, and their dependencies across on-premise and cloud environments, building a comprehensive inventory and architecture map in minutes. It identifies interdependencies, runtime characteristics, and technical debt to provide engineers with visibility into complex estate topology without manual effort. This automated discovery accelerates understanding of application makeup and supports dependency-aware migration planning. ## Application Assessment The platform performs deep, automated application analysis to assess cloud readiness, modernization opportunities, security risks, and architectural quality. It uses pattern-based evaluation to generate cloud-native readiness scores, identify bottlenecks and anti-patterns, and highlight technical debt across applications and workloads. Visualisation tools help teams prioritise optimization work and make data-driven decisions on modernization strategy. ## Migration AppFactor streamlines migration workflows by extracting application artefacts and metadata from source environments, analysing dependencies, and generating container-ready artefacts for target runtime environments. Through dependency mapping, wave grouping, and controlled extraction, build, and deployment phases, it reduces manual effort and risk in moving legacy applications into modern cloud platforms. ## Continuous Delivery The platform provides an application-centric continuous delivery control plane that works with existing CI processes to build and dispatch applications to hybrid and multi-cloud environments. It supports declarative workflows, reusable pipeline templates, and hybrid deployment targets, enabling consistent and repeatable delivery across AWS, GCP, Azure, and other environments. ## Modernization AppFactor accelerates modernization by automating containerisation, refactoring, dependency upgrades, and architecture improvements. It uses its agentic orchestration and AI-assisted analysis to recommend and apply modernization changes, helping teams transition applications to cloud-native forms without extensive manual rewrites. Continuous scoring and insights help guide technical debt reduction and future-proof design. ## Maintenance Once applications are deployed, AppFactor continues to support maintenance by tracking technical debt, security vulnerabilities, performance issues, and drift over time. Its orchestration layer can automate maintenance tasks such as dependency updates, patching, and refactoring, reducing engineering toil and keeping systems current, secure, and performant as part of a lifecycle-centric platform. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.appfactor.io/52eJroWboQfTwsFl14gL/quickstart-guide/overview/features.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.