Description:
The Meshery documentation [docs.meshery.io](https://docs.meshery.io) is a critical resource for users and contributors. Currently built using Jekyll, the site faces limitations in build speed, scalability, and long-term maintainability. Hugo, a modern static site generator, offers significantly faster build times, better content organization, and an improved developer experience. This internship focuses on migrating the entire [docs.meshery.io](https://docs.meshery.io) site from Jekyll to the Hugo framework) as a reference architecture. The migration will involve porting all documentation content, assets, layouts, and configuration while preserving URLs, SEO, contributor workflows, and existing auto-generated documentation files.
Static site generators (Jekyll and Hugo), Markdown, HTML/CSS, Git/GitHub workflows, documentation engineering, basic Go templating (Hugo), CI/CD familiarity.
Description:
Meshery Models are declarative representations of infrastructure and applications. Within these models, Relationships define how different Components (e.g., Kubernetes resources, Cloud services) interact and depend on each other. These relationships are crucial for visualizing, understanding, and managing complex cloud native systems. This internship focuses on significantly expanding the breadth and depth of Meshery Relationships across a wide array of technologies supported by Meshery. As Meshery continues to integrate with more cloud-native technologies (Kubernetes, public clouds, and all CNCF projects), there's a growing need to accurately model the intricate relationships between their components - vital for providing users with comprehensive insights and control over their deployments.
DevOps, systems administration, solutions architecture. Experience with Kubernetes, AWS and its services.
Description:
Meshery is the open-source cloud native manager that empowers platform engineers to design and operate infrastructure. As infrastructure complexity grows, the need for intelligent assistance becomes critical. This project focuses on developing and enhancing a dedicated AI Adapter and AI Connections for Meshery. This adapter serves as the bridge between Meshery's core orchestration engine and various Large Language Models (LLMs). The goal is to enable "Natural Language to Infrastructure" capabilities, allowing users to describe their architectural intent (e.g., "Deploy a highly available Kubernetes cluster on AWS with Prometheus monitoring") and have Meshery auto-generate the visual topology and configuration manifests. The intern will work on decoupling the AI logic from the core platform, allowing users to "Bring Your Own Model" (BYOM)—supporting both cloud-based providers (OpenAI, Anthropic) and local inference runners (Ollama, LocalAI).
Description:
Meshery's *MeshSync* component acts as the real-time discovery engine, maintaining an up-to-date snapshot of all managed infrastructure. Currently, mapping the complex relationships between these resources (e.g., a Service selecting Pods which are mounted to PVCs) relies on relational or in-memory lookups that can become inefficient at scale. This project involves integrating a dedicated graph database (or an embedded graph processing library) into Meshery's architecture. The goal is to ingest discovered Kubernetes resources as "nodes" and their associations (OwnerReferences, Label Selectors, Annotations) as "edges." This shift will enable highly efficient traversal and querying of infrastructure data, powering more advanced capabilities like topology visualization, impact analysis, and dependency mapping.
Description:
Integrate a new architectural component into Meshery: a workflow engine, using Temporal. This project involves shifting Meshery off of sqlite over to postgres using gorm (golang). Interns will familiarize with concepts of orchestration engines, including chaining workflows, and content lifecycle management.
Golang, Temporal, ReactJS
Description:
Meshery Models are declarative representations of infrastructure and applications. Within these models, Relationships define how different Components (e.g., Kubernetes resources, Cloud services) interact and depend on each other. These relationships are crucial for visualizing, understanding, and managing complex cloud native systems. This project focuses on expanding Meshery Relationships across a wide range of technologies, including Kubernetes and major cloud providers, to better model their interactions and improve user insights. There is a growing need to accurately model these relationships to provide better insights and control over deployments. The next phase focuses on Cloud Solution Architecture through workload design by creating and publishing Meshery designs that use the newly developed relationships to represent real-world deployments. These designs will be turned into structured tutorials with hands-on labs using Meshery Playground, offering step-by-step guidance and interactive learning. All content will be reviewed by maintainers and published in Meshery’s official documentation.
DevOps, systems administration, and solutions architecture. Experience with Kubernetes and cloud platforms (AWS, Azure, GCP). Proficiency in Markdown and technical writing. Familiarity with cloud-native tools.
Description:
Meshery is the open-source cloud native manager that empowers platform engineers to design and operate infrastructure. As infrastructure complexity grows, the need for intelligent assistance becomes critical. This project focuses on developing and enhancing a dedicated AI Adapter and AI Connections for Meshery. This adapter serves as the bridge between Meshery’s core orchestration engine and various Large Language Models (LLMs). The goal is to enable "Natural Language to Infrastructure" capabilities, allowing users to describe their architectural intent (e.g., "Deploy a highly available Kubernetes cluster on AWS with Prometheus monitoring") and have Meshery auto-generate the visual topology and configuration manifests. The intern will work on decoupling the AI logic from the core platform, allowing users to "Bring Your Own Model" (BYOM)—supporting both cloud-based providers (OpenAI, Anthropic) and local inference runners (Ollama, LocalAI).
Description:
Meshery's CI/CD infrastructure spans a large and growing collection of GitHub Action workflows that have accumulated technical debt - inactive workflows, insecure patterns, and duplicated logic. This internship has two phases: first, a comprehensive audit and restructuring of existing workflows; second, the introduction of GitHub Agentic Workflows to bring Continuous AI capabilities to Meshery's repository automation. Agentic Workflows allow automation to be defined in plain markdown and compiled into guardrailed GitHub Actions that run AI agents (Copilot, Claude, Codex) on schedule or in response to events - enabling automated CI failure triage, PR analysis, issue management, documentation maintenance, and compliance scanning with minimal human intervention.
GitHub Actions workflow authoring, CI/CD concepts, YAML, supply chain security basics (secret hygiene, fork-safe triggers, pinned actions). Interest in AI-assisted automation is a plus.
Description:
Meshery Models are declarative representations of infrastructure, applications, and their relationships - the canonical artifacts through which Meshery understands and manages cloud native systems. Today, Meshery lacks a standardized, portable distribution mechanism for these models. OCI registries (Docker Hub, AWS ECR, GitHub GHCR, and others) have emerged as the universal artifact store for the cloud native ecosystem, and ORAS (OCI Registry As Storage) provides the Go-native tooling to push and pull arbitrary artifacts to any OCI-compliant registry. This internship implements end-to-end OCI registry support for Meshery Models - from new Connection and Credential types for major registries, to ORAS-powered push/pull logic in the Meshery server, to a redesigned Registry page in the Meshery UI that gives users full visibility and control over their model artifacts across registries.
Golang, REST API development, React. Familiarity with OCI image specifications, container registries, or ORAS is a plus.
Full-Time Terms:
About the Community
The Meshery community embraces developer-defined infrastructure. We empower developers to change how they write applications, support operators in rethinking how they run modern infrastructure, and enable product owners to regain full-control over their product portfolio. Our cloud native application and infrastructure management software enables organizations to expect more from their infrastructure. Our inclusive and diverse community stewards projects to provide learning environments, create and implement cloud native industry standards, deployment and operational best practices, benchmarks and abstractions, and more. Our pay-it-forward mentality with every contributor (mentee or not) is a shared commitment by all maintainers (and MeshMates - contributor onboarding buddies) to the open source spirit that pushes the project forward. New members are always welcome.
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