CIRCUIT

Streamlining AEM instance setup with Ansible automation

Operating Adobe Experience Manager at scale has never been for the faint of heart. Whether you are standing up a fresh author environment for a marketing campaign or spinning up disposable publish farms for a regional launch, the manual steps compound quickly. From installing the JDK and configuring OSGi bundles to wiring runmodes and replicating content, every repetition introduces room for human error. Configuration management tools help, and Ansible has earned a quiet following among Java developers who like their automation declarative and their YAML readable.

In Australian enterprises, the pressure to automate infrastructure has grown alongside digital transformation across federal and state agencies. Teams in Canberra, Sydney, and Melbourne routinely deliver new AEM environments for short-notice campaigns, from ATO updates to Tourism Australia landings, often under tight change windows. Treating provisioning as code lets platform engineers respond without paging the on-call.

The recordings from past gatherings, including the talk captured for the CIRCUIT programme, walk attendees through the building blocks of a reliable Ansible playbook for AEM. You can revisit the conference FAQ for details on accessing those recordings.

For teams that already use Ansible elsewhere, adding AEM into the same inventory feels natural. The same roles that configure web servers or middleware can now author and publish an AEM dispatcher, an author instance, or a clustered publish tier. The reward is consistency that comes from a single source of truth describing how every node should look.

Why Ansible fits AEM provisioning

Ansible's agentless design is well matched to the way most Australian IT shops already operate. There is no need to install a daemon on every AEM host, which means fewer firewall negotiations and fewer exceptions to chase during audits. SSH is usually enough, and most corporate environments from Perth to Parramatta already have the keys in place.

Plain YAML lowers the bar for contributors who do not think of themselves as operations engineers. AEM architects in Melbourne banks have found that their Java developers can read and modify playbooks without learning a new domain-specific language. That accessibility shortens review cycles and makes it easier to standardise provisioning across distributed squads.

Compared to heavier alternatives, Ansible integrates smoothly with toolchains AEM developers already trust. A typical playbook might pull AEM installation media from an internal Nexus, apply OS-level configuration with the same modules used for application servers next door, and hand off to AEM-specific tasks such as unpacking the quickstart jar.

Anatomy of a provisioning playbook

A solid playbook for AEM usually begins with a role that prepares the host. This includes installing the supported JDK, configuring kernel parameters for the JVM, and ensuring file descriptors and limits are in place. From there, the playbook lays down the AEM runmode configuration files that distinguish author from publish and align with the dispatcher topology.

A common pattern in Australian deployments is to parameterise runmodes by region. A publish instance serving visitors from Sydney might be tagged with a runmode that points to specific replication agents and CDN origins, while a Melbourne-facing instance inherits a different set. Ansible variables make that branching straightforward.

Once the host is ready, the playbook downloads the AEM quickstart package, places the licence properties file in the right location, and starts the instance as a managed service via systemd. Idempotence is the real win. Running the playbook a second time on a healthy host should change nothing, which is exactly what change advisory boards want to see.

Handling author and publish differently

Author and publish instances look similar on the surface but behave very differently under the hood, and your automation should reflect that. An author tier usually carries heavier CPU and memory, has more OSGi bundles active, and is exposed only to internal users. Publish tiers sit closer to the edge, often behind a dispatcher and a CDN, and need to be hardened for untrusted traffic.

A well-designed playbook exposes these differences as variables rather than as separate playbooks. A single role can deploy either flavour, and a group_vars file decides which packages to install, which ports to open, and which health checks to run. For teams running AEM on AWS in the ap-southeast-2 region, this distinction also maps neatly to separate auto scaling groups.

For Australian government clients, where the Essential Eight often shapes the baseline, the split becomes even more useful. Publish instances can be configured to meet stricter controls without dragging the author environment through the same hardening, which slows down content authoring for no good reason.

Workflows, microservices, and companion automation

Provisioning is only half the story; once AEM is running, workflows and integrations need attention too. The session recordings from CIRCUIT cover several complementary patterns that pair well with automated provisioning.

Microservices that talk to AEM benefit from the same treatment. Whether you are standing up a Node.js front-end that consumes AEM content via the Assets HTTP API, or a Python service that mirrors product data into the JCR, Ansible can provision those sidecars alongside the AEM node. In Sydney fintechs and Brisbane retailers, this bundle is increasingly common.

Front-end build automation ties back into the same pipeline. The front-end tooling recording covers the build side, but the deployment story benefits from the same Ansible roles that manage the dispatcher. One role can clone the front-end repository, run npm ci, build the static assets, and copy the output into the dispatcher cache directory.

Common pitfalls and how to avoid them

The first pitfall is treating Ansible as a deployment tool rather than a configuration tool. Pushing the AEM quickstart jar from a developer's laptop is fragile; the binary should live in an artefact repository with a known version and checksum. This habit also keeps the playbook readable.

A second pitfall is letting workflow queues grow without bound. Persistent workflow entries can accumulate and slow down an author instance, especially when scripts create launchers that fire on every node update. Transient workflows, which execute and discard their record, are a useful remedy, and the transient workflows session recorded for CIRCUIT walks through the pattern.

A third pitfall is forgetting about secret management. AEM needs credentials for the admin user, replication agents, and external integrations, and these should never sit in plain text inside a playbook. Vault integration, or a secrets backend such as HashiCorp Vault, keeps the playbook portable while protecting the credentials. Australian teams subject to the Privacy Act and APRA CPS 234 will appreciate the audit trail that comes with a real secret store.

Finally, do not skip the test stage. A playbook that looks correct on paper can still misconfigure a dispatcher or skip a runmode directory on a fresh host. Running the playbook against a throwaway VM or a Terraform-managed cloud instance, then validating the AEM start logs and the Felix console, catches mistakes that would otherwise surface during a Saturday go-live.

Checklist for a first playbook

Before writing a single task, work out the structure of your provisioning effort. The four points below cover the essentials.

  • Define an inventory layout that separates author, publish, and dispatcher hosts, with group variables for runmodes and JVM settings.
  • Store the AEM quickstart jar, licence file, and OSGi bundles in an artefact repository, referenced by version rather than path.
  • Use Ansible Vault or an external secrets backend for every credential the playbook touches, and rotate those credentials through the same pipeline.
  • Add a smoke check that hits the Felix console and a sample content path, so a failed provision is caught before traffic is shifted.

Tick each item off before wiring the playbook itself, and the foundation will hold for every environment that follows.

Habits that keep the automation healthy

Once the playbook is in place, a few habits keep it useful for the next team that inherits it.

  • Version control every playbook, role, and variable file, and tag releases that correspond to AEM service pack upgrades.
  • Run the playbook through CI on every pull request with a small but representative set of hosts, and surface the diff for review.
  • Keep documentation close to the code, including the reasoning behind unusual variable defaults, so new team members in Perth or Parramatta can pick it up quickly.
  • Schedule periodic dry runs in a sandbox to catch drift introduced by manual changes.

These habits turn a one-off script into a long-lived platform asset.

Try wiring your next AEM environment through Ansible and watch the deployment window shrink from hours to minutes. Start with a single author instance, get comfortable with the playbook shape, and expand from there. Once the pattern is proven on one project, it tends to spread across teams on its own, and the conversation shifts from who can set this up to what to build once the platform is ready.