The DevOps Challenge

What is it?

Modern software development demands efficient DevOps workflows, but as organizations scale they face severe bottlenecks in artifact retrieval, dependency resolution, and build pipeline execution.
 
Teams spread across different regions, or globally distributed, can experience inconsistent performance when pulling artifacts, images, and binaries across long distances or cloud-based storage solutions.

Without a solution, enterprises face slow builds, rising infrastructure costs, and delays that drain productivity and hold up deployments. As software teams scale, and with many enterprises now handling petabytes of artifact traffic through their distributed build pipelines each month, these challenges are not just technical inefficiencies; they are critical business risks that threaten profitability, agility, and innovation.

Understanding DevOps Workflows

DevOps workflows orchestrate the automation of software development, testing, deployment, and operations to ensure continuous delivery and reliability. At their core, these workflows integrate source code management, build automation, testing, artifact storage, and deployment tools, creating seamless pipelines for delivering software. 

Across distributed teams, these workflows need to be fast, efficient, and scalable, ensuring engineers can iterate quickly while maintaining system stability and cost efficiency.

Lost Productivity

Developers waiting on builds or troubleshooting failures instead of shipping releases.

Higher Costs

Unnecessary bandwidth, cloud, storage, and compute usage due to high traffic load.

Delayed Releases

Slower time-to-market and risk of deployment issues means slower innovation.

A well-architected caching layer removes the inefficiencies that drag down productivity and increase cost burdens.

• Caching is a high-speed storage mechanism that temporarily holds frequently accessed data to avoid redundant retrieval from slower or more expensive backend systems.
  
  
• In DevOps and CI/CD workflows, storing artifacts in cache means they can be quickly accessed without needing to be re-fetched or rebuilt from scratch.
  
  
• Cached data allows teams to reuse previously retrieved or computed results, significantly reducing latency and load on infrastructure while improving developer efficiency.

Reduce Dependency Resolution Time

Storing pre-fetched dependencies ensures they are instantly available instead of being retrieved from external repositories.

Accelerate CI/CD Pipelines

Locally cached build artifacts allow for near-instant retrieval, cutting down build times significantly.

Minimize Cloud Egress Costs

By caching frequently accessed objects close to where they are needed, organizations reduce expensive 
data transfer fees.

Scale Down Backend Infrastructure

By serving cached responses rather than hitting primary storage or backend services, caching reduces IOPS and CPU consumption, improving overall efficiency while minimizing infrastructure needs.

Boost Productivity

With fewer bottlenecks in build, test, and deployment workflows, engineers can focus on shipping code rather than waiting for slow processes.

Caching is widely used, and many DevOps teams rely on built-in caching layers, open-source tools or freemium caching solutions to improve artifact retrieval. These alternatives improve performance to an extent, but often lack the scale, stability, security, and efficiency required for enterprise-grade DevOps workflows.

Local and remote build caches

Bazel, Gradle, Maven

Local and remote caches for binaries and dependencies often lack cross-team consistency, struggle with multi-terabyte storage and are tied to specific tools, making standardization across diverse DevOps environments difficult.

Built-in caching layers in artifact repositories

Artifactory, Nexus

Artifact repositories offer basic caching but are optimized for storage, not high-speed delivery. They often introduce cloud egress costs and struggle with high-concurrency workloads, making them inefficient for CI/CD pipelines handling thousands of parallel builds.

Open-source caches

Nginx, Squid

Reverse proxies can cache artifacts but lack fine-grained invalidation, persistent multi-terabyte storage and customization capabilities needed for native DevOps integration, resulting in lower hit rates. Manual work is often required for cache purging and preloading.

Memory caching solutions

Redis, Memcached

Memory caches provide ultra-fast data retrieval by accelerating environments from the inside, within artifact management solutions. While powerful, they are volatile and lack persistence. Their internal scope means they can't protect or accelerate the entire application at scale.

To fully optimize artifact caching, look for the following technical capabilities:

A high-performance caching layer for DevOps artifact management

Varnish Enterprise is a high-performance HTTP caching engine built to accelerate any HTTP-based workload. Since most DevOps and CI/CD tools rely on HTTP, Varnish is an ideal solution for eliminating bottlenecks and enabling fast, reliable artifact caching at scale.

Unlike limited alternatives, Varnish Enterprise is purpose-built to handle high-performance  caching at petabyte scale while integrating seamlessly into software distribution networks. With programmability, high-speed security, and persistent object storage as standard, it empowers teams to customize, secure, and scale artifact delivery without compromise.

By slashing infrastructure and bandwidth costs, and ensuring ultra-fast artifact retrieval, Varnish Enterprise unlocks the full potential of DevOps workflows - delivering faster releases and highly efficient CI/CD pipelines.

Enterprises using Varnish Enterprise report measurable success across multiple KPIs:

Varnish Enterprise is a software-based, subscription solution. A low-friction proof of concept accelerates solution validation and delivers confidence that key business KPIs can be met.

Reverse Proxy Caching & Data Acceleration

Varnish functions as a high-performance reverse caching proxy, sitting in front of application servers or artifact repositories and intercepting HTTP requests. When possible, it serves cached content directly, bypassing the origin and accelerating access to frequently requested artifacts, binaries, and dependencies. Unlike forward proxies, which primarily serve outbound requests on behalf of clients, reverse proxies like Varnish optimize delivery for users by reducing latency and offloading backend infrastructure. Cached content remains accurate through cache control and revalidation strategies, ensuring freshness while preserving origin systems as the source of truth.

Massive Storage Engine (MSE)

A proprietary storage engine delivers memory-speed performance with disk-based persistence, supporting terabyte-to-petabyte-scale caching with efficient eviction.

Programmable Traffic & Cache Logic

Varnish Configuration Language (VCL) enables tailoring of cache behavior to exact needs, from request routing to custom caching policies. This deep flexibility enables native DevOps integration, so caching aligns seamlessly with build pipelines, deployment flows, and application logic.

Built-in Security

Varnish supports role-based access control, token authentication and TLS termination to ensure secure artifact delivery, without compromising speed. Security policies can be tailored in VCL, for seamless integration with existing authentication and access logic.

Instant Invalidation & Revalidation

Define custom policies to instantly purge or revalidate specific objects, enabling granular cache control and ensuring data stays current while avoiding staleness.

Edge Caching & Multi-Region Support

Globally distributed teams can access cached data from the nearest available node.