Terraform UI: Semaphore UI vs Gaia

Gaia separates its Java web application, MongoDB database and execution runner. The runner starts Terraform in Docker containers or Kubernetes pods, with a configurable limit on parallel jobs. Docker Compose assembles these services, while an experimental Helm chart provides a Kubernetes installation option.

Semaphore UI runs as a binary or native package, as well as in Docker or Kubernetes. A team moving routine automation off engineers’ laptops can start on an existing server and use the same service for Terraform provisioning and Ansible maintenance. The selected execution mode determines whether job containers are needed.

Gaia runs Terraform modules through a generated Terraform command sequence. Terraform provisioners can call Ansible or command-line programs when the runner image or remote target supplies the required tools. This can configure a newly provisioned resource, but the command remains attached to a Terraform run rather than becoming an independent Gaia operation. Its standard command construction does not provide a separate OpenTofu or Terragrunt template.

Semaphore UI has direct templates for Ansible, Terraform/OpenTofu, Terragrunt, Bash, PowerShell and Python. A team can create infrastructure with OpenTofu, configure packages with Ansible and run a Python readiness check. Later, the Ansible configuration or PowerShell maintenance operation can run by itself, without starting another Terraform lifecycle. The built-in Pro state backend also keeps Terraform/OpenTofu state and its history beside those jobs.

Gaia’s module author defines the source repository, Terraform version and variable schema. Users create stacks from that module and supply the values and cloud credential appropriate to their environment. The stack becomes a durable instance with its own state and jobs, which suits a catalog of independently requested infrastructure. Gaia validates required values and configurable regular expressions. Semaphore UI surveys validate required fields, integers and choices, without an equivalent configurable regex rule.

Semaphore UI calls the saved operation a Task Template. It brings together a repository, tool configuration, variables and any inventory or credentials the operation needs. Named Variable Groups reuse environment settings across templates, while survey fields collect launch inputs. For example, a service-restart template can offer a choice of service and environment instead of asking the colleague to construct a command. A provisioning template can use the same pattern for environment parameters.

Gaia runs plan, apply and destroy against a stack’s configured module, inputs and cloud credentials. Its built-in backend keeps that stack’s state, while the stack page collects outputs and job history. Separate test environments can therefore retain independent state and execution records even when they originate from the same module.

Semaphore UI uses a Task Template to select the Terraform/OpenTofu repository, workspace and configuration. Variable Groups reuse settings across related jobs, and survey forms collect inputs at launch. An engineer can prepare an environment-provisioning operation once, then let colleagues request it through that saved configuration. Each environment also needs its own variables, credentials and backend state. Gaia represents these as separate stack instances. In Semaphore UI, the team prepares the corresponding template, workspace and backend configuration. Workspace isolation depends on the backend, so selecting a workspace alone does not separate state for every backend. Terragrunt and OpenTofu are direct template choices alongside Terraform.

State is a separate part of that setup. Gaia includes a state backend for each stack without a commercial license. Semaphore UI uses the backend configured for the Terraform/OpenTofu code, and Pro also provides a built-in HTTP state backend with history and UI management. Keeping that backend in Semaphore UI puts the shared state next to the jobs that change it, rather than adding another state service.

Neither product applies a previously saved plan file by default. Gaia 2.4.0 displays the planning result, but its apply command does not use the saved plan file. Semaphore UI’s default execution also plans and applies separately. If approval must cover the exact proposed change, the procedure needs explicit storage and reuse of that plan.

Gaia keeps Terraform resources and outputs with each stack. A Terraform output can provide the host address needed by a provisioner or by another system, but it does not create an Ansible inventory resource in Gaia’s interface. Ansible invoked through a provisioner must receive or generate its inventory as part of that automation.

Semaphore UI stores Ansible inventories as reusable project resources. Teams can edit a static definition, use a file from Git or let Ansible inventory plugins discover hosts when a job runs. The same inventory can serve deployment, patching and certificate checks. This is especially useful when provisioning is only the start of the work and operators return to an existing fleet throughout its life.

Gaia separates the application from its runner. The runner requests pending Terraform steps and executes them in Docker containers or Kubernetes pods, with configurable concurrency. It can run near private infrastructure as long as it can reach the Gaia API and the services used by the module. The selected image supplies Terraform and any additional programs required by provisioners.

Semaphore UI can run jobs on its application server or on runners placed near the targets. This lets a small installation start without a container platform and lets a larger one reach separate networks through runners. Pro adds project runners and Docker job execution, while Enterprise adds Kubernetes job pods. Installing the web application in Docker and executing each job in its own container remain separate choices.

Semaphore UI saves cron and one-time schedules against prepared templates. A nightly backup, a recurring certificate check or a patching job can reuse the inventory, credentials and launch settings selected by the author. Manual and scheduled runs then appear in the same execution history.

Gaia 2.4.0 does not include a scheduling interface. An external scheduler can create a RUN or DESTROY job through POST /api/stacks/{id}/{jobType}, then start its plan through POST /api/jobs/{jobId}/plan. Applying the change is a separate POST to /api/jobs/{jobId}/apply after the plan finishes. A scheduler must handle that lifecycle and inspect the final job result, rather than treating creation of a job ID as a completed run.

Gaia guides a stack through planning and application. Its interface offers a separate confirmation after the plan, including for destroying a stack. Terraform provisioners can perform further actions inside that lifecycle, and an external system can coordinate multiple jobs through the API. Gaia does not provide a visual graph of independently reusable Ansible, Terraform and script operations.

Semaphore UI connects saved templates through a visual workflow, including approval, success and failure paths. A rollout can provision infrastructure, wait for approval, configure hosts and run a verification step, while each template stays available for later maintenance. Collected values can pass between steps using the local executor on the server or a runner. Generated files and saved Terraform plans still need accessible storage or an explicit transfer. Neither product applies a previously saved Terraform plan by default.

Gaia uses organizations to share modules, with administrator and user roles. A module author can make an approved Terraform definition available to a team, while users supply the configuration for their own stacks. GitHub and GitLab integrations combine OAuth2 sign-in with repository importing, and LDAP is also supported.

Semaphore UI Community organizes shared automation within projects. Project roles control who can view, run or edit automation within the project. Colleagues with execution permission can launch a deployment, backup or maintenance job and review its result. The engineer prepares the operation, while the colleague uses its saved configuration and launch inputs.

Enterprise adds custom roles and template-level execution permissions when access must be limited to selected operations. For example, a team can delegate a service-restart template without giving the operator general project-editing rights. That boundary comes from the role permissions and operation configuration together, rather than the survey form alone. Pro adds LDAP and OIDC sign-in for teams using a central identity provider. Semaphore UI Pro also adds TOTP two-factor authentication for local accounts.

Gaia supplies cloud credentials for AWS, Google Cloud and Azure. Its optional Vault integration uses the Transit engine for encryption and can request dynamic AWS credentials from a Vault secrets engine. These credentials support the Terraform stack lifecycle.

Semaphore UI’s Key Store supports the credentials used across the team’s procedures, including SSH keys and passwords for Ansible hosts. A prepared operation references those stored entries instead of requiring the operator to paste credentials at each launch. Pro adds secret lookup from HashiCorp Vault and OpenBao, while Enterprise adds AWS Secrets Manager, Azure Key Vault and Devolutions Server integrations, plus CyberArk through its PVWA API.

For example, one environment can use a cloud credential for provisioning and an SSH key for its subsequent Ansible configuration. Those remain separate credentials associated with the relevant operation. Both platforms can work with Vault, but Gaia’s encryption and dynamic-credential features differ from looking up a stored secret for a job. Gaia’s built-in credential types do not include connectors for the other secret stores listed above. Terraform code can retrieve secrets through its own data sources or external commands, with that lookup configured and maintained in the automation rather than Gaia’s credential interface.

Gaia records the user, status, timing and plan/apply steps of a stack job. That history helps a team inspect an environment’s provisioning changes and investigate the Terraform output. It is a record of stack operations rather than an Ansible host-reporting or administrative audit interface.

Semaphore UI keeps task history across the supported tools. Pro Ansible summaries add host and task results, helping an operator identify which servers failed a patch or certificate check. Its audit log records sign-ins and supported administrative actions separately from the task output. A team running both provisioning and host maintenance can therefore investigate those operations in the same service without treating Terraform state as a report of every action on a server. Pro adds audit filtering and export, including Syslog and Splunk HEC delivery for a team’s SIEM pipeline.

Gaia imports modules from GitHub or GitLab and exposes APIs for stacks, jobs and their results. A CI pipeline or external request service can create a stack job, start planning and decide when to apply it. A webhook-driven setup needs an adapter that performs those calls and follows the outcome. Semaphore UI provides a REST API and incoming integration webhooks that match requests and map their values into prepared task inputs.

For a team keeping Gaia’s Terraform catalog, an API integration can trigger a Semaphore UI Ansible configuration or maintenance template after provisioning completes. Semaphore UI then owns that operation’s inventory, credentials and execution record. This is a connection the team implements, not a built-in Gaia-to-Semaphore integration. Both projects also expose documentation and source code that a coding assistant can consult when drafting that connection or investigating configuration and job output.