Why and How to extend CI/CD to the Edge

In today’s distributed computing environments, applications don’t just live in the cloud, they run at the edge, across thousands of locations. To support this shift, organizations need CI/CD pipelines that extend beyond centralized infrastructure. By connecting your CI/CD pipeline to the edge using cloud-native tooling, you unlock faster deployment, improved reliability, and scalable operations.

Why CI/CD Pipelines Need to Extend to the Edge

As more enterprises adopt distributed edge environments, the need to automate beyond traditional cloud deployments is becoming critical. Manually managing application updates across hundreds of locations isn’t scalable, and it slows innovation. By extending cloud-native CI/CD pipelines to the edge, organizations can streamline operations, accelerate development, and reduce the complexity of edge management and everyday operations.

There are significant business values of connecting the CI/CD pipeline to the edge:

1. Consistent Developer Experience Across Cloud and Edge

Using the same cloud-native tools for both cloud and edge deployments creates a unified self-service experience for developers. This consistency increases developer feature velocity, reduces friction across environments, and removes the need to reinvent processes for edge-specific use cases. Teams can ship updates faster  without creating silos between cloud and edge investments.

2. Faster Feedback Loops for Edge Deployments

Integrating the edge with your CI/CD pipeline means that application changes can be automatically tested and deployed to real-world environments, as easily as to the cloud. This early feedback accelerates iteration cycles, improves product quality, and allows organizations to deliver new features faster across their distributed infrastructure.

3. Minimal Training Required for Ops Teams

Since teams can continue using familiar tools like GitHub Actions, GitLab CI, or Jenkins, operational onboarding becomes easier. There’s no need to train staff on entirely new systems just to manage edge applications. Instead, existing knowledge of CI/CD systems is extended to edge environments, reducing rollout friction and long-term support costs.

Keep reading: CI/CD tools and Avassa: how to build a successful integration

What Makes CI/CD to The Edge Different from Cloud Deployments?

 While traditional CI/CD pipelines work well for centralized cloud infrastructure, edge deployments introduce new complexities. The difference lies primarily in the deploy phase, moving from a single orchestrator to a distributed, diverse edge network of tens, hundreds, or even thousands of sites.

Cloud CI/CD vs. Edge CI/CD

Challenges of Deploying CI/CD at the Edge

While extending CI/CD pipelines to the edge unlocks agility and automation, it also introduces new operational challenges, especially at scale. Edge environments are highly variable, decentralized, and less predictable than centralized cloud deployments.

Limited Connectivity and Bandwidth

Edge sites often operate in environments with unreliable or intermittent connectivity, requiring CI/CD systems to support offline operation and deferred synchronization.

Deployment Logic Across Thousands of Sites

Instead of one target cluster, edge deployments must intelligently route applications to hundreds or thousands of locations — based on hardware, location, and available resources.

Distributed Testing and Observability

Testing and monitoring can’t rely on a single control point. Validation and observability must be distributed, aggregating signals across many sites to ensure system-wide confidence.

Core Requirements for CI/CD at the Edge

Unlike centralized cloud environments, CI/CD for distributed edge deployments introduces operational complexity that cannot be addressed with traditional cloud tooling alone. Edge environments demand specialized capabilities to handle unreliable connectivity, heterogeneity across infrastructure, and large-scale coordination.

1. Complex Edge Deployment Logic at Scale

In an edge use case, deployment is not a single push to a central cluster, rather a coordinated rollout across hundreds or thousands of edge points of presence (POPs). This requires:

• Handling slow or intermittent network connections between the CI/CD system and edge nodes
• Supporting conditional logic for deployments based on location, site characteristics, or available hardware (e.g., deploying only to sites with cameras or specific compute capabilities)
• Managing error handling and retries across constrained or partially available infrastructure

2. Distributed Testing Across Edge Sites

Testing an edge deployment means more than checking a few canaries. Success requires:

• Running distributed probes across many sites, not just centrally
• Aggregating test results from across the fleet to validate a deployment globally

Using converged test signals, not isolated pass/fail outputs, to assess rollout readiness

3. Unified Edge Observability and Monitoring

Edge observability must be built in to enable safe and scalable operations. This includes:

• Monitoring application health across all edge nodes, not just at a central level
• Providing a global view of deployment health while enabling per-site drill-down for troubleshooting

Treating observability as a precondition to “done”,  a deployment isn’t complete until it’s being monitored end to end.

To handle the above complexities, edge CI/CD systems require:
✅ An orchestrator with multi-cluster deployment capabilities, supporting canary and rolling upgrades.
✅ A distributed testing model that uses converging signals across sites, not isolated probes.
✅End-to-end observability that tracks application state globally and per-site.

Key Capabilities Required in an Edge CI/CD Platform

A robust edge CI/CD platform must go beyond traditional pipelines and address the unique demands of distributed, resource-constrained edge environments. This includes multi-cluster edge orchestration to manage deployments across thousands of sites, canary and rolling updates to ensure safe, incremental rollouts, and converged testing mechanisms that aggregate validation signals from across the fleet. The platform should also enable edge deployment automation based on declarative logic, integrate with existing cloud-native CI/CD tools, and provide real-time observability into application health and rollout progress. All while functioning reliably in environments with limited or unstable connectivity.

Declarative Deployment Strategies for Dynamic Edge Environments

A fundamental difference between cloud and edge deployment is scope and specificity. At the edge, you’re not deploying every application to every site at all times,  you’re targeting based on context, hardware, and application need. This makes declarative deployment strategies essential for building scalable, resilient edge infrastructure.

Separate Application and Deployment Specifications

To manage this complexity, it’s important to distinguish between what you’re deploying and where you’re deploying to. This separation brings clarity and automation to your edge strategy.

• The application specification defines the structure of the application — its containers, services, resources, and configuration.
• The deployment specification defines where to deploy it, using abstract rules instead of hardcoded zones or site names.

This approach removes the burden from developers to memorize infrastructure details or manage sprawling spreadsheets to keep track of GPU availability, sensor presence, or hardware compatibility.

Using Logical Labels and Expressions for Flexibility

Rather than explicitly listing every site that should run an application, declarative deployment specifications use logical expressions and site labels to drive automation.

For example:

Deploy Application A to all edge sites labeled region:eu-north AND has_gpu:true AND camera:available.

This makes the deployment process scalable, maintainable, and infrastructure-aware, enabling smarter edge application placement across diverse environments.

Continuous Convergence Toward Desired State

Unlike traditional cloud deployments, edge deployment is not a one-time event. It’s a continuous process of reconciling current edge infrastructure with the defined deployment intent.

If a new camera is added to an edge node that matches a deployment rule, the system should automatically detect that change and deploy the relevant application — no human intervention required. This is the essence of continuous delivery at the edge: the platform continuously evaluates the desired state against the actual state across all sites, converging them over time.

We have in a previous article showed the details on how to set up Avassa as the edge deployment engine, meeting all the requirements in this article.

How Avassa Supports CI/CD at the Edge

Avassa bridges the gap between cloud-native DevOps workflows and the operational realities of the edge. By integrating with existing CI/CD pipelines, Avassa enables automated, policy-driven deployments to thousands of edge locations, complete with multi-cluster orchestration, canary rollouts, converged testing, and fleet-wide observability. Its declarative deployment model ensures applications are delivered exactly where and when they’re needed, based on dynamic infrastructure conditions without requiring custom scripts or manual coordination.

Read more in our white paper on Observability in the distributed edge: The full story.