Harness is a CI/CD platform that unifies automation, security, and efficiency in software delivery. Designed for DevOps teams, it accelerates workflows with low-code pipeline design, Kubernetes-native support, and GitOps (Argo CD/Flux) integration. The platform minimizes risks through automated code quality scans, security testing, and rollback-ready deployments. Tailored for medium-to-large enterprises managing microservices and multi-cloud environments, Harness reduces operational overhead while speeding releases. Monitor pipelines via a unified dashboard, AI-driven insights for optimization, and scale confidently with enterprise-grade governance. Ideal for teams prioritizing speed without compromising compliance or reliability.
What is Harness?
Harness is a next-generation CI/CD platform designed to automate and optimize software delivery pipelines. By combining intuitive automation, robust integrations, and GitOps-driven deployments, Harness empowers teams to accelerate releases while ensuring code quality, security, and reliability.
Harness Key Features
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Low-Code Pipeline Builder: Visually design workflows with drag-and-drop simplicity.
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Kubernetes & Cloud-Native Support: Integrated with AWS EKS, Azure AKS, Docker, and hybrid environments.
GitOps (Argo CD/Flux): Automate deployments using Git as the single source of truth.
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AI-Powered Insights: Proactively identify risks, optimize pipelines, and reduce downtime.
Pipeline Setup
Repository Configuration:
- Store pipelines in Harness’s native repository or a custom Git repo (ensure the YAML path starts with .harness/).
- Create a Git connector to link your repository (e.g., GitHub, GitLab).
Infrastructure Selection:
- Choose execution environments: Harness Cloud, Kubernetes clusters (AWS EKS, Azure AKS, on-prem), or Docker containers.
- For Kubernetes, deploy a Harness Delegate (lightweight agent) via Helm to enable cluster communication.
Pipeline Execution
Define Workflow Steps:
- Build: Compile code, create Docker images, and publish artifacts.
- Test: Run unit, integration, and security scans (SonarQube, Snyk).
- Custom Actions: Integrate third-party tools from Harness’s extensive catalog.
for details click here.
Run & Monitor:
- Execute pipelines via the Delegate on your Kubernetes cluster.
- Track real-time logs, metrics, and statuses in Harness’s unified dashboard.
Deploying Applications with GitOps
GitOps Agent Setup
Install Argo CD or Flux: Download the override.yaml file for agent configurations (ArgoCD version, secrets, GitOps agent settings).
Deploy the agent using Helm:
- bash
- Copy
- helm install gitops-agent -f override.yaml harness/gitops-agent
GitOps Deployment Workflow
- Sync Policies: Define how often the agent checks Git for updates (e.g., every 5 minutes).
- Source: Link your Git repo containing Kubernetes manifests (e.g., Helm charts, Kustomize).
- Destination: Target cluster namespaces (production, staging).
- Automated Sync: Click Sync to deploy the latest Git state to your cluster.
- Beyond Automation: Comprehensive CI/CD Governance
Harness extends CI/CD beyond basic automation to ensure end-to-end software excellence:
Code Quality & Security:
- Integrate SAST/DAST tools (Checkmarx, OWASP) and enforce governance gates.
- Auto-fail pipelines on critical vulnerabilities.
Version Control & Rollbacks:
- Tag artifacts with semantic versioning.
- One-click rollbacks to stable versions during incidents.
Observability & Monitoring:
- Correlate deployment metrics with APM tools (Datadog, New Relic).
- Set alerts for performance degradation or errors.
- Feature Management:
- Enable canary releases, A/B testing, and feature flags for risk-free rollouts.
Why Harness for Medium & Large Enterprises?
As organizations scale, managing microservices, multi-cloud environments, and compliance becomes complex.
Harness addresses this by:
- Reducing Operational Overhead: Pre-built templates, AI-driven optimizations, and automated governance.
- Enhancing Collaboration: Unified visibility for Dev, Sec, and Ops teams.
- Future-Proofing Workflows: Native support for emerging technologies (AI/ML, serverless)