Skip to main content
We begin by identifying common DevOps challenges and then show how GitOps—and specifically the Argo project—resolves them. Before examining what Argo does, let’s start with why this approach matters. The following story about a fictional company, Dasho, illustrates the typical pitfalls teams encounter when moving to Kubernetes and infrastructure-as-code. The situation will feel familiar to many. Dasho believed they were doing things correctly. They were migrating to a modern multi-cloud Kubernetes platform and wanted an infrastructure-as-code mindset. Their first attempt, however, was incomplete. A few developers applied changes manually against the cluster, while a few others committed changes to a single Git branch. With little automation and inconsistent version control, it quickly became impossible to track who changed what and when. They recognized the problem and added a CI/CD pipeline, which was a step forward — but it had a major flaw: it was a push-based pipeline, and the team’s culture did not shift. Developers still found it faster to run kubectl commands directly on the live cluster, bypassing the pipeline. For example, several different manifests were manually applied to the cluster: 
# Developers manually applied different manifests directly to the cluster:
kubectl apply -f deployment-v2.9.5.yaml
kubectl apply -f deployment-v3.0.1.yaml
kubectl apply -f deployment-v2.8.4.yaml
kubectl apply -f deployment-v2.8.4.yaml
This hybrid approach produced cascading failures across three main areas:
  • Security risks: Storing Kubernetes credentials outside the cluster to allow an external CI to push changes — plus more people with powerful access — expanded the attack surface.
  • Configuration drift: The cluster’s live state diverged from the intended state in Git, undermining reproducibility.
  • Unreliable disaster recovery: Because manual, unrecorded changes existed, applying what’s in Git would not restore the true working system after an outage.
Configuration drift: when manual or out-of-band changes cause the live environment to differ from the version-controlled desired state, making reproducibility and recovery unreliable.
Storing cluster credentials outside the cluster or granting widespread kubectl access increases risk. Prefer in-cluster controllers and limited, auditable access.
It was a ticking time bomb. Dasho’s core problem was a breakdown of trust: there was no single, reliable source of truth. That translated into instability and high operational risk.
A slide titled "Challenges" showing three colored cards labeled "Security risks", "Configuration drift", and "Disaster recovery." Each card has a matching white icon: a shield with a warning for security, a gear/controls for configuration drift, and stacked servers with a recovery/fire symbol for disaster recovery.
How do we solve these problems? The answer is GitOps. At its core GitOps uses Git as the source of truth. Changes to infrastructure or application configuration are made in Git. A controller inside the cluster continuously reconciles the cluster’s actual runtime state with the desired state in Git. This approach provides auditability, repeatability, and a clear workflow for changes. The Argo project is the leading open-source toolset for implementing GitOps and related automation on Kubernetes. Below we summarize how the primary Argo components address Dasho’s issues.

​
Argo CD

Argo CD is the continuous delivery engine for GitOps on Kubernetes.
  • Runs inside the Kubernetes cluster and implements a pull-based reconciliation loop: it watches Git repositories and ensures the cluster matches the desired state declared in Git.
  • Keeps credentials in-cluster (as Kubernetes Secrets), avoiding the need to expose cluster credentials to external CI systems.
  • Detects configuration drift and can automatically or manually revert out-of-band changes by reapplying the desired state from Git.
  • Supports disaster recovery by re-creating cluster state from manifests, Helm charts, and Kustomize resources stored in Git.

​
Argo Workflows

Argo Workflows is a Kubernetes-native workflow engine for orchestrating multi-step jobs as containers.
  • Define pipelines as steps or DAGs with containerized tasks.
  • Use it for build, test, linting, and other CI tasks that run inside Kubernetes, leveraging cluster scale and resource management.
  • Integrates with other Argo tools to create complete CI/CD automation.

​
Argo Rollouts

Argo Rollouts provides progressive delivery strategies to reduce release risk.
  • Supports canary, blue-green, and other progressive deployment patterns.
  • Integrates with monitoring and metrics systems (for example, Prometheus) to perform automated analysis during rollouts.
  • On metric regressions (e.g., increased error rates), Argo Rollouts can pause or roll back automatically to protect production.

​
Argo Events

Argo Events is an event-driven automation framework that connects external signals to in-cluster automation.
  • Listens for events from Git pushes, webhooks, S3, message queues, and more.
  • Triggers workflows, notifies systems, or initiates Argo CD syncs and Argo Rollouts.
  • Enables end-to-end event-driven CI/CD: e.g., a Git push → Argo Events → Argo Workflows build/test → success triggers Argo CD sync and Argo Rollouts deployment.
A presentation slide titled "Argo Project" showing four cards labeled ArgoCD, Argo Workflows, Argo Rollouts, and Argo Events. Each card has a colorful octopus/squid-themed illustration (rocket, swirling squid, cube with arrows, and a calendar-like icon).

​
Argo components at a glance

ComponentPrimary use caseKey benefit
Argo CDGitOps continuous delivery and reconciliationGit as single source of truth; drift detection and remediation
Argo WorkflowsContainer-native CI pipelines and batch jobsRun CI within Kubernetes with scalable resource control
Argo RolloutsProgressive delivery (canary/blue-green)Safer releases with automated metric-driven rollback
Argo EventsEvent-driven triggers and automationConnect external events to internal automation pipelines

​
Putting it all together

For Dasho, adopting the Argo suite resolved the major failures:
  • Argo CD restored trust by enforcing Git as the authoritative source and eliminating configuration drift.
  • Argo Workflows automated build and test steps inside the cluster.
  • Argo Rollouts enabled safe, progressive deliveries with metric analysis and automated rollback.
  • Argo Events connected external triggers to internal automation, creating a seamless event-driven pipeline.
The result: a shift from a chaotic, fragile environment to an automated, secure, and resilient cloud-native platform. This journey from chaos to control is exactly why the Argo Project is a foundational toolset for modern software delivery.
A presentation slide titled "Conclusion" showing a vertical timeline with four colorful numbered points summarizing Argo: enabled automation, security and resilience; transformed chaos into a controlled environment; shifted to a modern cloud-native platform; and is essential for modern software delivery. The layout has a turquoise left panel and the four short conclusions listed to the right.

Watch Video