Optimising AEM delivery with Varnish Cache

Adobe Experience Manager gives organisations a powerful platform for managing websites, digital assets, campaigns, and personalised experiences. Its flexibility can also create demanding workloads: every page request may involve Sling resolution, component rendering, repository reads, permissions checks, and calls to connected services.

Varnish Cache addresses a different part of the problem. As a high-performance HTTP reverse proxy, it stores complete responses in memory and serves repeat requests without sending them back to AEM. The result can be lower origin traffic, faster page delivery, and greater resilience during campaigns or sudden traffic spikes.

The strongest architecture treats Varnish as one layer in an AEM delivery chain rather than a replacement for AEM Dispatcher. A common production path places a CDN or edge service in front of Varnish, followed by Dispatcher and AEM Publish instances. Each layer needs a clear responsibility for caching, security, compression, and invalidation.

This approach is especially useful in Australia, where visitors may be distributed between Sydney, Melbourne, Brisbane, Adelaide, Perth, and regional areas. A well-designed cache reduces the effect of distance and limited origin capacity, while careful privacy controls help organisations meet obligations under the Privacy Act and Australian Privacy Principles.

Why Varnish fits an AEM publishing architecture

Varnish is designed to process HTTP traffic rapidly. It examines a request, looks for a usable object in its cache, and returns the stored response when the object is fresh. A request that would otherwise consume AEM Publish resources can therefore be completed at the reverse proxy.

AEM Dispatcher still has an important role. It provides request filtering, load balancing, cache management, and protection around the publish tier. Varnish can sit in front of Dispatcher to add high-speed object caching, flexible purge rules, and advanced control through VCL. The exact order depends on the deployment, but the boundary between layers must be documented and tested.

Cacheability is determined by the response, not by the page URL alone. Public HTML, CSS, JavaScript, image files, fonts, and immutable asset versions are usually strong candidates. Responses containing session identifiers, authentication state, shopping baskets, account information, or user-specific recommendations generally need to bypass shared caching.

AEM components should therefore be built with predictable output. Stable URLs, consistent canonicalisation, efficient selectors, and clean cache headers make the reverse proxy more effective. Varnish cannot correct an application that produces a different response for every request or adds unnecessary query-string variations.

Building a reliable request path

Begin with a simple request flow: the browser reaches the edge, the edge forwards eligible traffic to Varnish, Varnish checks its object store, and misses travel through Dispatcher to AEM Publish. Health checks should remove an unhealthy publish instance quickly, while multiple Varnish nodes prevent a single proxy from becoming a bottleneck.

TLS termination needs a deliberate decision. Some teams terminate HTTPS at a CDN or load balancer and send trusted internal traffic to Varnish; others terminate TLS directly at the caching tier. Whichever model is selected, forwarded host and protocol headers must be validated so AEM generates correct links, redirects, cookies, and absolute asset URLs.

Large or expensive backend operations deserve separate treatment. AEM may need to expose search services, product feeds, reporting endpoints, or structured content APIs, and these do not all benefit from identical TTLs. A related architecture can be explored through large data sets, where moving suitable data workloads away from the repository can reduce pressure on the publishing stack.

VCL rules should be kept readable and version-controlled. They commonly remove tracking parameters from the cache key, reject suspicious methods, normalise hosts, bypass requests with private cookies, and set different grace periods for different content classes. Every rule should have a test case, since a small header mistake can create either a cache leak or an unexpectedly low hit rate.

Managing freshness and invalidation

Time to live is the most visible cache setting, but it is not the complete freshness strategy. A short TTL limits stale content while increasing origin requests. A long TTL improves efficiency but requires dependable invalidation whenever an author publishes a change.

AEM activation events can trigger purge requests towards Varnish, directly or through an orchestration service. Purging by exact URL is precise, while tagging responses with a content identifier can support broader BAN or purge operations. For a site with shared navigation, regional campaign banners, or reused experience fragments, dependency-aware invalidation is often more practical than maintaining a long list of individual URLs.

Grace mode can preserve availability during a backend failure. Varnish may serve a recently expired object while it attempts to revalidate the response in the background. This is valuable during a campaign launch or an overnight incident, though the permitted stale window should be defined by business owners rather than chosen casually.

Cache warming can prepare important landing pages before a scheduled promotion. A controlled crawler can request the home page, campaign pages, category pages, and key assets after a deployment or purge. It should respect rate limits and exclude search results, forms, and personalised routes. Warming every URL can waste resources and hide inefficient publishing patterns.

Protecting privacy and personalised experiences

Shared caching must never return one visitor’s private response to another. Cookies such as login, session, cart, or personalisation identifiers should normally cause a bypass. The same caution applies to query parameters that carry account references, access tokens, or sensitive form data.

Australian organisations should consider the Privacy Act 1988, the Australian Privacy Principles, and any sector-specific requirements when designing logs and cache storage. IP addresses, request parameters, and response fragments can become personal information depending on context. Retention policies should cover Varnish logs and monitoring data, not just AEM and application databases.

A practical design separates public and private journeys. Anonymous visitors receive cacheable pages, while signed-in users are sent to an uncached route or receive a shell that retrieves private data through a controlled API. Cookie stripping should never be used as a shortcut if the origin relies on that cookie for authorisation or response selection.

Authoring traffic must stay away from the public cache. AEM author instances should use separate hostnames, access controls, and routing rules. Publishing teams also benefit when component governance reduces avoidable variations; template locking can help keep page structures consistent and reduce the number of unusual responses that need separate cache treatment.

Measuring performance across Australian users

A successful reverse proxy implementation needs evidence. Track cache hit ratio, byte hit ratio, origin request rate, backend response time, object age, purge volume, error rate, and the percentage of requests bypassing cache. A high hit ratio is useful, but it should be considered alongside real user measurements such as largest contentful paint and time to first byte.

Testing should cover Australian network conditions rather than relying on a single office connection. Compare delivery from Sydney and Melbourne with users in Perth, Brisbane, and regional locations. NBN performance varies by access technology and suburb, and mobile visitors may move between congested networks. A nearby CDN point of presence can reduce round-trip time, while Varnish protects the AEM origin from repeated requests.

Traffic patterns also reflect local behaviour. Retail sites may experience sharp evening peaks, sporting events can create sudden national demand, and government or education portals may receive concentrated traffic around application deadlines. Load tests should reproduce these patterns, including cache misses after a campaign purge.

Operational teams should monitor both the cache layer and the application layer. A rise in misses may indicate a cookie regression, a new query parameter, an incorrect host rule, or an overly short TTL. A rise in backend latency may indicate repository queries, external integrations, or insufficient publish capacity. Clear dashboards and alert thresholds allow engineers to address the cause instead of repeatedly adding hardware.

Use a staged rollout for production. Start with static assets and a small group of anonymous pages, compare origin load and response times, then expand coverage after security and purge tests pass. Record cache policies in the deployment repository, review them with developers and security specialists, and rehearse an emergency bypass so traffic can reach AEM safely when the proxy requires maintenance.

Adopt Varnish as part of a measured AEM performance programme. Map public and private routes, define ownership for TTLs and purge events, test Australian network paths, and review privacy controls before enabling broad caching. With disciplined headers, dependable invalidation, and continuous monitoring, the reverse proxy can make AEM faster, steadier, and better prepared for the peaks of the Australian digital market.