EV

evernote-deploy-integration

Set up production deployment pipelines and Docker configurations for Evernote API integrations.

Install

mkdir -p .claude/skills/evernote-deploy-integration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8439" && unzip -o skill.zip -d .claude/skills/evernote-deploy-integration && rm skill.zip

Installs to .claude/skills/evernote-deploy-integration

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Deploy Evernote integrations to production environments.
56 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Build production-ready Docker images
  • Deploy to Google Cloud Run with secret management
  • Configure AWS Lambda for serverless webhook processing
  • Manage Kubernetes deployments with probes
  • Verify production connectivity

How it works

The skill utilizes multi-stage Docker builds and cloud-native secret management to isolate credentials and ensure production-grade environment configuration.

Inputs & outputs

You give it
Evernote integration source code
You get back
Deployed production container or serverless function

When to use evernote-deploy-integration

  • Deploy to Docker
  • Setup Cloud Run deployment
  • Configure production environment

About this skill

Evernote Deploy Integration

Overview

Deploy Evernote integrations to production environments including Docker containers, AWS ECS/Lambda, Google Cloud Run, and Kubernetes, with proper secrets management and health checks.

Prerequisites

  • CI/CD pipeline configured (see evernote-ci-integration)
  • Production API credentials approved by Evernote
  • Cloud platform account (AWS, GCP, or Azure)
  • Docker installed for containerized deployments

Instructions

Step 1: Docker Deployment

Create a multi-stage Dockerfile that builds the app and produces a minimal production image. Set NODE_ENV=production and configure the Evernote SDK for production endpoints.

FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --production
COPY . .
RUN npm run build

FROM node:20-alpine
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/node_modules ./node_modules
ENV NODE_ENV=production EVERNOTE_SANDBOX=false
EXPOSE 3000
CMD ["node", "dist/index.js"]

Step 2: Google Cloud Run Deployment

Deploy the Docker image to Cloud Run with secrets mounted from Secret Manager. Cloud Run scales to zero when idle, making it cost-effective for webhook receivers.

gcloud run deploy evernote-app \
  --image gcr.io/PROJECT/evernote-app:latest \
  --set-secrets EVERNOTE_CONSUMER_KEY=evernote-key:latest \
  --set-secrets EVERNOTE_CONSUMER_SECRET=evernote-secret:latest \
  --allow-unauthenticated \
  --region us-central1

Step 3: AWS Lambda (Serverless)

Package the webhook handler as a Lambda function behind API Gateway. Use AWS Secrets Manager for credentials. Lambda is ideal for event-driven Evernote integrations (webhook processing, scheduled sync).

Step 4: Kubernetes Deployment

Create a Deployment with ConfigMap for non-secret settings and Kubernetes Secrets for API credentials. Include liveness and readiness probes that verify Evernote API connectivity.

Step 5: Deployment Verification

After deployment, verify: health check endpoint returns connected, a test note can be created and retrieved, webhook endpoint is reachable, and monitoring is reporting metrics.

For the full Dockerfile, Cloud Run config, Lambda handler, Kubernetes manifests, and deployment verification scripts, see Implementation Guide.

Output

  • Multi-stage Dockerfile for production builds
  • Google Cloud Run deployment with Secret Manager integration
  • AWS Lambda handler for serverless webhook processing
  • Kubernetes Deployment, Service, and Secret manifests
  • Deployment verification checklist and script

Error Handling

ErrorCauseSolution
Invalid consumer key in productionUsing sandbox credentialsVerify EVERNOTE_SANDBOX=false and production key
Secret not mountedMissing cloud secret resourceCreate secret in Secret Manager/AWS Secrets Manager
Health check failingEvernote API unreachable from cloudCheck network/firewall rules, verify DNS resolution
Cold start timeoutLambda initialization too slowIncrease timeout, use provisioned concurrency

Resources

Next Steps

For webhook handling, see evernote-webhooks-events.

Examples

Cloud Run webhook: Deploy a webhook receiver to Cloud Run that processes Evernote note change notifications, syncs changes to a database, and scales to zero between events.

Lambda batch processor: Deploy a scheduled Lambda that runs nightly to export all notes tagged "archive" to S3, using the sync API to fetch only changed notes since the last run.

When not to use it

  • Deploying with sandbox credentials in production
  • Committing secrets to version control

Prerequisites

CI/CD pipeline configuredProduction API credentials approved by EvernoteCloud platform accountDocker installed

Limitations

  • Requires production API credentials from Evernote

How it compares

It focuses on specific cloud-provider integrations like Cloud Run and Lambda rather than generic deployment scripts.

Compared to similar skills

evernote-deploy-integration side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
evernote-deploy-integration (this skill)024dReviewIntermediate
firecrawl-deploy-integration124dReviewIntermediate
exa-deploy-integration024dReviewAdvanced
deployment-pipeline-design62moReviewAdvanced

Try saying

Example prompts that trigger this skill in your AI assistant.

More by jeremylongshore

View all by jeremylongshore

analyzing-logs

jeremylongshore

Analyze application logs to detect performance issues, identify error patterns, and improve stability by extracting key insights.

14123

ollama-setup

jeremylongshore

Configure auto-configure Ollama when user needs local LLM deployment, free AI alternatives, or wants to eliminate hosted API costs. Trigger phrases: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs". Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

1167

backtesting-trading-strategies

jeremylongshore

Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".

1071

generating-database-seed-data

jeremylongshore

Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.

1033

cursor-codebase-indexing

jeremylongshore

Execute set up and optimize Cursor codebase indexing. Triggers on "cursor index setup", "codebase indexing", "index codebase", "cursor semantic search". Use when working with cursor codebase indexing functionality. Trigger with phrases like "cursor codebase indexing", "cursor indexing", "cursor".

885

testing-mobile-apps

jeremylongshore

Execute mobile app testing on iOS and Android devices/simulators. Use when performing specialized testing. Trigger with phrases like "test mobile app", "run iOS tests", or "validate Android functionality".

810

You might also like

firecrawl-deploy-integration

jeremylongshore

Deploy FireCrawl integrations to Vercel, Fly.io, and Cloud Run platforms. Use when deploying FireCrawl-powered applications to production, configuring platform-specific secrets, or setting up deployment pipelines. Trigger with phrases like "deploy firecrawl", "firecrawl Vercel", "firecrawl production deploy", "firecrawl Cloud Run", "firecrawl Fly.io".

12

exa-deploy-integration

jeremylongshore

Deploy Exa integrations to Vercel, Fly.io, and Cloud Run platforms. Use when deploying Exa-powered applications to production, configuring platform-specific secrets, or setting up deployment pipelines. Trigger with phrases like "deploy exa", "exa Vercel", "exa production deploy", "exa Cloud Run", "exa Fly.io".

01

deployment-pipeline-design

wshobson

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

670

genkit-infra-expert

jeremylongshore

Execute use when deploying Genkit applications to production with Terraform. Trigger with phrases like "deploy genkit terraform", "provision genkit infrastructure", "firebase functions terraform", "cloud run deployment", or "genkit production infrastructure". Provisions Firebase Functions, Cloud Run services, GKE clusters, monitoring dashboards, and CI/CD for AI workflows.

15

cloudflare

bilal-chajia

Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biase

00

terraform-module-library

wshobson

Build reusable Terraform modules for AWS, Azure, and GCP infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.

759

Search skills

Search the agent skills registry