Published: September 3, 2026
Last Updated: September 3, 2026
Cloud teams spend a lot of hours on work a script could do faster and with fewer mistakes. Spinning up servers by hand, patching systems one at a time, chasing down a config that drifted overnight — none of that scales once your infrastructure crosses a handful of environments. Cloud automation exists to take that manual load off your team and put it into repeatable, auditable code instead.
Quick Answer: Cloud automation trims the manual provisioning work, and the two tools that matter most are Terraform and Ansible.
Definition: “Cloud automation uses software, scripts, and policies to handle provisioning, configuration, and management tasks across cloud infrastructure without manual intervention.”
What Is Cloud Automation?
Cloud automation swaps out manual provisioning, configuration, and management work for software, scripts, and policies that run on their own. It spans public, private, and hybrid clouds, and it’s become close to standard practice: 85 percent of enterprises now lean on cloud automation to handle repetitive infrastructure work.
It’s worth separating automation from orchestration, since the two get used interchangeably and shouldn’t be. Automation handles individual tasks — spinning up a VM, applying a patch, running a backup. Orchestration sequences those automated tasks into a full workflow across your entire environment, coordinating resource, workload, and service-level actions together, a distinction IBM draws directly in its own documentation.
Automation without governance is where things go wrong. A misconfigured Terraform module can fail silently and repeatedly in multi-team or hybrid-cloud setups, requiring manual intervention to catch, per Sedai’s own field observations. Build drift detection and review gates into your automation from the start, not after the first incident.
What Cloud Tasks Can You Automate?
Most cloud teams start with provisioning and scaling together, then move into monitoring, backups, and security once those basics are holding steady. The tasks that pay off fastest are repetitive and rule-based, the kind of work where doing it by hand is bound to introduce errors sooner or later.
Common candidates include:
- Infrastructure provisioning — launching and tearing down servers, storage, and networking through Infrastructure as Code (IaC), rather than clicking through a console by hand
- Autoscaling — compute resources adjust up or down automatically, tracking traffic and demand as they shift
- Configuration management — maintaining systems in a known, consistent state and alerting to drift before it causes an outage.
- Patching and updates — applying security and system patches on a schedule rather than waiting for someone to remember.
- Backups — backups run on a schedule across the whole environment, so nobody has to be the one to trigger them.
- Hybrid and multicloud syncing — one API layer runs the same policy code across on-premises systems and multiple clouds at once, rather than juggling a separate tool for every provider.
Start with whichever task on this list currently eats the most support tickets or after-hours pages. That’s usually provisioning or patching.
What Are the Benefits of Cloud Automation?
The clearest benefit of cloud automation is faster, more predictable delivery with fewer manual errors, and the case studies back that up with real numbers rather than vague claims. Red Hat reports that telecom provider One New Zealand cut delivery times by 40% and reduced costs for deploying new workloads by 45% after centralizing its cloud operations on Ansible Automation Platform.
The UK’s Department for Work and Pensions adopted the same platform. The jump was similar. Deployment times dropped from 50 minutes to 10, and the team no longer had to maintain separate codebases for different environments, according to Red Hat’s published case study.
Beyond speed, automation cuts down on the human error that comes from repetitive manual work, and it centralizes governance across data centers and hybrid clouds. Routine tasks fall away for IT staff too, freeing them up for higher-value work instead of babysitting deployments.
What Are the Best Cloud Automation Tools?
Between them, Terraform and Ansible cover most of what cloud automation actually needs. They now share the same corporate parent, following IBM’s $6.4 billion acquisition of HashiCorp, which closed in December 2024. That ownership change shows up in how the two tools are sold: increasingly marketed and bundled together, not pitched as competitors.
The two solve different problems:
- Terraform provisions infrastructure from code. State gets managed across multiple cloud providers. Pricing on Terraform Cloud runs $0.10 to $0.99 per resource per month, and its open-source core remains free.
- Using an agentless, SSH-based architecture, Ansible configures and manages systems that already exist, with no software required on target hosts. Red Hat sells Ansible Automation Platform as an annual subscription priced by the number of managed nodes, without a published list price, while Ansible Core stays free and open source.
Many teams run both: Terraform for provisioning, Ansible for configuration once resources exist. Enterprise buyers combining both platforms can often get a 20–30% discount over purchasing each tool’s enterprise tier separately, per the vendor bundling now common under IBM’s infrastructure portfolio. Kubernetes and Google Cloud’s Infrastructure Manager are worth evaluating too if your workloads are container-heavy or already sit inside Google Cloud.
For a broader rundown of automation software beyond the cloud-specific tools above, see the full IT automation tools roundup.
How Do You Build a Cloud Automation Strategy?
A cloud automation strategy works best when you automate one high-friction task at a time, instead of trying to take on everything at once. Start by identifying which manual process currently costs your team the most hours or causes the most incidents, then build automation around that single task before expanding.
A practical sequence to follow:
- Pick one repetitive task — provisioning, patching, or backups are usually the highest-friction starting points
- Choose the right tool for that task — Terraform for provisioning, Ansible for configuration
- Add drift detection and review gates before scaling the automation to more environments
- Standardize policies as code so the same rules apply across every cloud you use, not just one
- Expand gradually into orchestration, sequencing individual automated tasks into full workflows once each piece is stable on its own
This mirrors the broader approach covered in IT automation, which walks through the same principles across systems beyond just cloud infrastructure.
FAQ
1. What is an example of cloud automation?
Autoscaling is a simple one. A cloud platform adds or removes server instances on its own, tracking incoming traffic without anyone stepping in to adjust it. Automated backups and scheduled patching are two other everyday examples of things most teams keep running unnoticed.
2. What’s the difference between cloud automation and cloud orchestration?
Automation performs one thing at a time, such as provisioning a server or applying a patch. Orchestration puts together many automated processes into one coordinated effort through your entire environment. In many ways, automation is the individual bricks and orchestration is what puts them to work as a functioning process.
3. Is Terraform a cloud automation tool?
Yes. Terraform provisions and manages infrastructure on multiple cloud providers using code. Alongside Ansible, it’s one of the two most widely used cloud automation tools.
4. What are the benefits of cloud automation?
The 3 benefits most consistently reported are faster deployment, fewer manual errors, and centralized governance achieved across hybrid and multicloud environments, supported by tangible results like One New Zealand’s 40% faster delivery times after deploying Ansible Automation Platform.
5. How do you start automating cloud infrastructure?
Identify the single most time-consuming, error-prone manual task your team handles. Automate that one first with the right tool, then move into orchestration once it’s stable.
