Add comprehensive Kubernetes and container deployment documentation

[Copilot]

Overview

This PR addresses the community question about recommendations for running FinanceToolkit in Kubernetes by adding comprehensive deployment documentation.

Changes

New Documentation: DEPLOYMENT.md

Created a complete deployment guide (526 lines) that provides production-ready guidance for containerizing and orchestrating applications that use the FinanceToolkit. The guide includes:

Docker Containerization

• Complete Dockerfile example optimized for Python 3.10+
• Dependencies management and best practices
• Environment variable configuration for API keys

Kubernetes Deployment Patterns

• Basic Deployment configuration with resource limits and requests
• CronJob pattern for scheduled financial analysis tasks
• Service configuration for exposing REST APIs
• Horizontal Pod Autoscaler (HPA) for automatic scaling

Best Practices

• Resource management guidelines (memory and CPU allocation)
• API rate limiting strategies and caching with persistent volumes
• Security best practices:
  • Kubernetes Secrets for API key management
  • RBAC considerations
  • Network policies for egress control
• Monitoring and logging configurations
• Health check implementations (liveness and readiness probes)

Complete Working Examples

• Example 1: Daily scheduled financial analysis job using CronJob
• Example 2: REST API service with full deployment stack
• Sample Python application code demonstrating environment-based configuration

All YAML configurations have been validated for syntax correctness.

Updated README.md

• Added "Deployment Guide" to the table of contents
• Created new deployment section with overview and link to the full guide
• Positioned appropriately before the "Questions & Answers" section

Why This Matters

The FinanceToolkit is a Python library, not a standalone service, so deployment scenarios vary based on how users integrate it into their applications. This documentation:

1. Clarifies the deployment model - Explains that users are deploying applications that use the toolkit
2. Provides production-ready templates - Copy-paste-ready YAML configurations
3. Addresses real-world concerns - API rate limits, caching, security, and cost optimization
4. Supports multiple use cases - From scheduled batch jobs to real-time API services

Example Use Case

A user can now deploy a scheduled financial analysis job to Kubernetes by:

1. Containerizing their Python application using the provided Dockerfile
2. Storing their FinancialModelingPrep API key as a Kubernetes Secret
3. Deploying the provided CronJob YAML (with minimal customization)
4. Utilizing persistent volumes for caching to reduce API calls and costs

This documentation makes it straightforward to run FinanceToolkit-based applications in production Kubernetes environments with proper security, monitoring, and resource management.

Testing

• ✅ All 10 complete YAML configurations validated syntactically with PyYAML
• ✅ Documentation passed codespell checks
• ✅ Links verified and properly formatted
• ✅ Follows existing documentation style and structure

Closes the issue requesting Kubernetes deployment recommendations.

Original prompt

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This section details on the original issue you should resolve

<issue_title>Container orchestration question</issue_title>
<issue_description>Are there recommendations for running this in Kubernetes?</issue_description>

Comments on the Issue (you are @copilot in this section)

Fixes #194

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