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From Manual to Magic: Automating App Deployments with Ansible Tower
There was a time when deploying applications meant long checklists, careful coordination, and inevitable late nights. Every environment had slight differences, and the risk of “it works on my machine” loomed large.
Then came Ansible, and later, Ansible Tower—bringing structure, visibility, and automation to an otherwise fragile process.
In this post, I’ll share how I transformed application deployments from a manual, error-prone task to a fully automated and repeatable workflow using Ansible Tower.
🧱 The Manual Pain
Before automation, deploying apps like Tomcat or WebSphere involved:
- Logging into multiple servers manually
- Stopping services one by one
- Uploading builds over SCP
- Restarting services and hoping everything came back cleanly
- Constant cross-checking logs, versions, and configurations
This not only slowed things down but also left room for inconsistency, human error, and post-deployment firefighting.
🧰 Enter Ansible Tower
Ansible Tower is the web-based UI and API for Ansible. It allows for:
- Centralized playbook management
- Role-based access control
- Real-time job monitoring
- Scheduling
- Logging and auditing
It builds on the simplicity of Ansible while making it collaboration-friendly and enterprise-ready.
⚙️ What I Automated
I wrote playbooks and job templates in Tower to handle:
- Application stop/start across different environments
- Configuration updates specific to the environment
- Deployment of artifacts (WARs, EARs) to Tomcat/WebSphere
- Health checks and validation after deployment
Each component was modular and reusable. For example:
# handlers/main.yml
- name: restart tomcat
systemd:
name: tomcat
state: restarted
🧪 Workflow Breakdown
-
Trigger via Tower UI or API Developers or release engineers could trigger deployments without SSH access.
-
Inventory-Driven Logic Hosts were grouped by environment (
dev
,stage
,prod
), so the same playbook adjusted behavior dynamically. -
Credential Isolation SSH keys and secrets were stored securely in Tower, not shared in scripts.
-
Visual Logs and Job Outputs Tower provided real-time visibility—what task ran, where it failed, and who ran it.
🚀 The Impact
- Deployment time went from 40–60 minutes to under 10 minutes
- Reduced post-deployment incidents by over 70%
- Enabled junior engineers and support staff to run controlled deployments
- Auditable history of who did what and when
🧠 Lessons Learned
- Modular playbooks are key: Reusability saved time and debugging headaches.
- Fail early, fail clearly: Clear error messages and checks helped prevent messy rollbacks.
- Automation ≠ One-size-fits-all: Each app had quirks—building templates with flexibility was crucial.
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