paniolo-deployment-strategies
|
Works with
--- name: paniolo-deployment-strategies description: | license: MIT --- **Requires:** file-read, terminal (your platform's deploy CLI). No network access needed. # Deployment Strategies Skill ## Use When Use this skill when: - Preparing or executing staging/production deployments. - Updating environment configuration or secrets management steps. Execution workflow: 1. Run pre-deploy quality checks before deployment changes. 2. Use the appropriate deploy command for the change type (including cache purge when needed). 3. Keep env/secrets handling aligned with existing project conventions. 4. Verify deployment health immediately after rollout. Output requirements: - Summarize deploy/config changes and affected environments. - Include exact deploy and verification commands used. ## Common Scenarios - Deploying a frontend, an API service, or both - Configuring environment variables for staging or production - Adding new secrets or credentials - Running pre-deploy validation ## Deploy Workflow ### Pre-Deploy Checklist Always run before deploying to production: ```bash <your lint command> <your unit-test command> ``` ### Deploy Commands Most projects expose more than one deploy path, and the difference between them matters more than the names: - **A plain deploy** ships new code but may leave a CDN or edge cache serving the previous build to users. - **A deploy that also purges cache** is the one to use for any user-facing change — UI components, API behavior, bug fixes — so users see the new code immediately rather than a cached version. - **A staging deploy** targets the pre-production environment. Deploy there first whenever the change is not trivially reversible. Learn which of your project's scripts does which before the first production deploy, not during one. A deploy that silently skips cache invalidation looks identical to a successful one right up until users report stale behavior. ### Verify After Deploy Confirm health from outside the deploy tooling — a green pipeline is not evidence that users are served working code: ```bash curl https://<your-domain>/api/health ``` Then tail live logs for the first minutes of traffic. ## Environment Configuration Keep one variable per environment rather than branching on environment inside code, so a misconfiguration fails visibly at startup instead of silently selecting the wrong backend: ```env API_URL=http://localhost:3000 # Development API_URL=https://staging.example.com # Staging API_URL=https://api.example.com # Production ``` Non-secret configuration belongs in your platform's config file, committed to the repo. Values that differ per environment but are not sensitive — region, environment name, public endpoints — belong there rather than in secrets, so they stay reviewable. ## Secrets Management **Never commit secrets to git.** Use your platform's secret storage, which keeps values out of the repository and out of build logs. Two rules travel with it: - Secrets usually apply only to deployments created *after* they are set, so setting one is not complete until you redeploy. - Local development secrets go in gitignored `.env` files, never in the committed config. When a secret appears not to work, list what the deployed environment actually holds rather than trusting the config file. ## Sub-Skills - [Cache management + GitHub Actions CI/CD](../paniolo-cloudflare-cache-cicd/SKILL.md) - [Rollback, monitoring, troubleshooting](../paniolo-deployment-operations/SKILL.md) ## Do Not - Do not deploy to production without running lint and unit tests first. - Do not commit secrets to git — use your platform's secret storage. - Do not use a plain deploy for user-facing changes when your setup needs a cache purge. Users will see stale cached versions. - Do not use for active incident recovery — load `deployment-operations` instead. ## Skill Handoffs - If active production recovery is required, also load `deployment-operations`. - If CDN cache behavior must change with deploy, also load `cloudflare-cache-cicd`.
More Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

