domain-cloud-native

zhanghandong/rust-skills · updated Apr 8, 2026

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$npx skills add https://github.com/zhanghandong/rust-skills --skill domain-cloud-native
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summary

Design constraints and patterns for building stateless, observable cloud-native applications in Rust.

  • Enforces stateless design, graceful shutdown with SIGTERM handling, and 12-factor configuration via environment variables to support Kubernetes orchestration and zero-downtime deployments
  • Requires distributed tracing with tracing and OpenTelemetry, plus dedicated /health and /ready endpoints for liveness and readiness probes
  • Recommends key crates: tonic for gRPC services, kube and ku
skill.md

Cloud-Native Domain

Layer 3: Domain Constraints

Domain Constraints → Design Implications

Domain Rule Design Constraint Rust Implication
12-Factor Config from env Environment-based config
Observability Metrics + traces tracing + opentelemetry
Health checks Liveness/readiness Dedicated endpoints
Graceful shutdown Clean termination Signal handling
Horizontal scale Stateless design No local state
Container-friendly Small binaries Release optimization

Critical Constraints

Stateless Design

RULE: No local persistent state
WHY: Pods can be killed/rescheduled anytime
RUST: External state (Redis, DB), no static mut

Graceful Shutdown

RULE: Handle SIGTERM, drain connections
WHY: Zero-downtime deployments
RUST: tokio::signal + graceful shutdown

Observability

RULE: Every request must be traceable
WHY: Debugging distributed systems
RUST: tracing spans, opentelemetry export

Trace Down ↓

From constraints to design (Layer 2):

"Need distributed tracing"
    ↓ m12-lifecycle: Span lifecycle
    ↓ tracing + opentelemetry

"Need graceful shutdown"
    ↓ m07-concurrency: Signal handling
    ↓ m12-lifecycle: Connection draining

"Need health checks"
    ↓ domain-web: HTTP endpoints
    ↓ m06-error-handling: Health status

Key Crates

Purpose Crate
gRPC tonic
Kubernetes kube, kube-runtime
Docker bollard
Tracing tracing, opentelemetry
Metrics prometheus, metrics
Config config, figment
Health HTTP endpoints

Design Patterns

Pattern Purpose Implementation
gRPC services Service mesh tonic + tower
K8s operators Custom resources kube-runtime Controller
Observability Debugging tracing + OTEL
Health checks Orchestration /health, /ready
Config 12-factor Env vars + secrets

Code Pattern: Graceful Shutdown

use tokio::signal;

async fn run_server() -> anyhow::Result<()> {
    let app = Router::new()
        .route("/health", get(health))
        .route("/ready", get(ready));

    let addr = SocketAddr::from(([0, 0, 0, 0], 8080));

    axum::Server::bind(&addr)
        .serve(app.into_make_service())
        .with_graceful_shutdown(shutdown_signal())
        .await?;

    Ok(())
}

async fn shutdown_signal() {
    signal::ctrl_c().await.expect("failed to listen for ctrl+c");
    tracing::info!("shutdown signal received");
}

Health Check Pattern

async fn health() -> StatusCode {
    StatusCode::OK
}

async fn ready(State(db): State<Arc<DbPool>>) -> StatusCode {
    match db.ping().await {
        Ok(_) => StatusCode::OK,
        Err(_) => StatusCode::SERVICE_UNAVAILABLE,
    }
}

Common Mistakes

Mistake Domain Violation Fix
Local file state Not stateless External storage
No SIGTERM handling Hard kills Graceful shutdown
No tracing Can't debug tracing spans
Static config Not 12-factor Env vars

Trace to Layer 1

Constraint Layer 2 Pattern Layer 1 Implementation
Stateless External state Arc for external
Graceful shutdown Signal handling tokio::signal
Tracing Span lifecycle tracing + OTEL
Health checks HTTP endpoints Dedicated routes

Related Skills

When See
Async patterns m07-concurrency
HTTP endpoints domain-web
Error handling m13-domain-error
Resource lifecycle m12-lifecycle
how to use domain-cloud-native

How to use domain-cloud-native on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add domain-cloud-native
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/zhanghandong/rust-skills --skill domain-cloud-native

The skills CLI fetches domain-cloud-native from GitHub repository zhanghandong/rust-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/domain-cloud-native

Reload or restart Cursor to activate domain-cloud-native. Access the skill through slash commands (e.g., /domain-cloud-native) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.543 reviews
  • Dhruvi Jain· Dec 28, 2024

    Solid pick for teams standardizing on skills: domain-cloud-native is focused, and the summary matches what you get after install.

  • Harper Abbas· Dec 28, 2024

    Registry listing for domain-cloud-native matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Advait Thompson· Dec 8, 2024

    domain-cloud-native fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Advait Gupta· Nov 27, 2024

    domain-cloud-native has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Oshnikdeep· Nov 19, 2024

    We added domain-cloud-native from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Aditi Okafor· Nov 19, 2024

    Useful defaults in domain-cloud-native — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Advait Shah· Oct 18, 2024

    Solid pick for teams standardizing on skills: domain-cloud-native is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Oct 10, 2024

    domain-cloud-native fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Harper Ramirez· Oct 10, 2024

    I recommend domain-cloud-native for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chen Kapoor· Sep 13, 2024

    Useful defaults in domain-cloud-native — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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