Why Your DevOps Pipeline is Slower Than You Think, And How to Fix It

You’ve optimized your code. You’ve automated your tests. You’re using the latest CI/CD tools. So why are your builds still slow?

The answer often lies in artifact retrieval, dependency resolution and software distribution; critical but overlooked parts of the software delivery process. Every time your pipeline fetches dependencies from remote repositories (e.g., Maven, npm, PyPI) or distributes software artifacts across teams and environments, it can introduce unnecessary latency, variability and infrastructure costs.

Every developer has been there. Waiting for builds to finish, watching dependencies download, frustrated by slow pipelines. It’s easy to dismiss these delays as a minor inconvenience, but they add up fast:

• A 5-minute delay per build with 10 builds per day means 50 minutes wasted daily per developer
• With 100 developers, that means 83 hours lost per day, equating to nearly $1M/year in wasted productivity (assuming a $100K average salary).

That’s real money, lost to something as basic as slow artifact retrieval and inefficient software distribution.

How Delays Eat Away at DevOps Productivity

These performance issues typically arise due to a combination of factors:

Redundant downloads. CI/CD pipelines fetch the same artifacts from remote repositories on every build, even when they haven’t changed. This wastes bandwidth and introduces unnecessary delays.

Cloud latency and network delays. Every time an artifact is retrieved from a remote package repository (e.g., Maven Central, npm, PyPI, or Docker Hub), network latency adds unpredictable delays. This problem worsens when builds are distributed across multiple regions.

Inefficient caching. Caches that don’t persist across builds, jobs, or teams can force redundant downloads.

Overloaded artifact repositories. When multiple builds request the same files simultaneously, perhaps during peak hours or large-scale releases, artifact repositories (e.g. Artifactory, Nexus, or AWS S3) experience contention, leading to increased response times and higher failure rates.

Cloud egress costs and delays. Frequent external artifact downloads result in higher cloud egress fees, increasing costs while slowing down artifact retrieval due to rate limits and throttling.

What is Artifact Caching?

Artifact caching is the practice of storing and reusing previously downloaded software dependencies and artifacts to avoid redundant network requests. By caching artifacts closer to where they are needed, DevOps teams can dramatically reduce build times, lower cloud costs and improve software distribution efficiency. This is particularly important for large-scale DevOps workflows, where software needs to be distributed across multiple teams, regions and cloud environments.

Why Traditional Caching Methods Fall Short

Many teams rely on outdated or insufficient caching methods that fail to scale with DevOps demands:

Built-in package manager caches. These only work per machine and are frequently cleared, making them unreliable for distributed teams.

CDNs. Effective for static content but struggle with software artifacts and dynamic builds that require rapid updates.

DIY caching proxies. Solutions like Squid or NGINX can cache artifacts but require extensive manual tuning, lack DevOps-specific optimizations and don’t support granular caching for dependencies.

Because software distribution involves pushing artifacts across multiple environments, relying on inefficient caching means developers in different locations experience inconsistent performance, long download times and higher cloud fees.

How Varnish Enterprise Fixes This

Varnish Enterprise acts as a high-performance caching and software distribution layer that sits between your CI/CD pipeline and artifact repositories, drastically reducing latency, improving software distribution efficiency and ensuring high availability for DevOps teams.

Varnish Enterprise enables DevOps teams to:

• Cache dependencies and software artifacts, with no need to repeatedly download the same files.
• Speed up software distribution across regions, reducing latency for global DevOps teams.
• Handle CI/CD traffic spikes effortlessly, ensuring smooth performance even at peak demand.
• Reduce software distribution costs by minimizing redundant downloads.

Unlike traditional caching solutions, Varnish Enterprise is designed to fit seamlessly into modern DevOps workflows, offering:

• Cloud-native caching. Deploy in AWS, Azure, Google Cloud and on-prem environments.
• Custom cache locations. Optimize performance by placing caches closer to developers.
• Programmability & automation. Offers VCL (Varnish Configuration Language) for fine-tuned control over caching policies.
• Cache persistence. Massive Storage Engine offers efficient, persistent caching of vast quantities of data, optimized for both very large and small objects.
• Tooling integration. Works with Kubernetes, Docker, Terraform and CI/CD tools.
• Security & compliance. Supports authorization-aware caching, ensuring only authenticated users can access cached artifacts.

Results in Action

Major enterprises globally are seeing huge success using Varnish Enterprise for DevOps productivity.

• One streaming service optimized its DevOps workflows with Varnish, achieving 85% lower artifact retrieval latency and reducing install times from 5 minutes to 1 minute.
• A major SaaS company using Artifactory cut artifact retrieval time by 85% and reduced CI/CD failures by 30% after implementing Varnish Enterprise caching.

Technical Deep Dive

For a deeper look at how Varnish Enterprise accelerates artifact retrieval and optimizes software distribution, watch our on-demand webinar. Learn how to eliminate build delays, reduce cloud costs, and improve DevOps efficiency at scale. Varnish Technical Evangelist Thijs Feryn breaks down real-world caching strategies, showcases performance benchmarks and demonstrates how Varnish Enterprise integrates seamlessly into CI/CD pipelines to deliver faster, more reliable software builds.

If your team is pulling the same dependencies from the cloud on every build or struggling with slow software distribution. It’s time to cache smarter. Your developers (and your budget) will thank you.