Continuous and agile approaches to software and application delivery have modernized and refined how developers operate. Infrastructure as Code (IaC) methodologies and tools like Terraform have been critical to this shift.
But these new efficiencies face increasing headwinds. Managing continuous software delivery at scale inevitably creates infrastructure challenges. For instance, the infrastructure needed to support software at different stages in the pipeline and across different pipelines varies, resulting in the need to create and manage a diverse range of configurations.
Additionally, the tools and methods used to create and manage infrastructure are complex, with configurations held in IaC, container, and configuration tool files. Each file’s structure reflects the discretion and skills of the practitioner, which often makes it hard to understand, change, share, and remediate its configurations. This is particularly true with Terraform.
In IaC, infrastructure is defined as code, and it provides practitioners great flexibility to easily define, edit, and distribute configurations. This helps ensure infrastructure is defined consistently and is reproducible. The use of IaC in a DevOps pipeline can result in faster and more efficient cloud provisioning.
Common challenges managing and controlling Terraform files at scale
What about the unintended consequences of all this power and flexibility?
Success with Terraform relies on high-level coding skills and an intimate working knowledge of the entire infrastructure stack. Without governance and adherence to best practices, IaC can easily lead to configuration sprawl, configuration drift, and/or invisible configurations bound to a particular designer’s knowledge.
As infrastructure definitions and configurations proliferate, new challenges arise. Practitioners involved in the delivery of software and IT services use different configuration and code-based tools to define what they need. This situation is exacerbated by developers defining and provisioning their own cloud infrastructure.
This has increased complexity and fragmentation, while making it difficult to understand what infrastructure is being used—and why. Fragmentation can occur across teams and throughout all software delivery pipelines. Applications are unique, as are the environments required to keep them updated and running. A single software delivery pipeline will likely require many iterations of infrastructure.
How auto-discovery provides control over Terraform assets
Our users leverage the Torque platform as a control plane for IaC tools like Terraform and Helm to understand what, when, why, and by whom infrastructure is being used. The control plane addresses infrastructure configuration sprawl, complexities, and fragmentation. And it does so in a consistent way without slowing development practices.
Learn more: Detect Terraform drift and IaC configurations proactively
Through this approach, our users connect code repositories to Torque to automatically discover IaC configurations and identify and model specific Terraform assets into standardized blueprints. From these blueprints, Torque users can provision, optimize, and decommission complete application environments on demand via secure self-service.
Automate discovery across Terraform assets
Simplify connect a GitHub, GitLab, or Bitbucket repository to Torque and it will automatically locate the folders and configuration files from existing IaC, such as Terraform, Helm, and AWS CloudFormation. Users then choose the configurations to import and model into environment blueprints.
The auto discovery process reveals what configurations are being used, when they were created, and when they were last used. This sets the stage for establishing accountability into infrastructure usage, allowing DevOps and development teams to get more out of their infrastructure investments.
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