Hashicorp improves ILM to allow organizations to operate at scale

HashiCorp announced their latest Infrastructure Lifecycle Management (ILM) features at HashiConf 2024 in Boston, with enhancements for Terraform, Packer and Nomad, among others.

These innovations focus on simplifying infrastructure management and optimizing workflows for organizations operating at scale.

Terraform Stacks in public beta

One of the key announcements was the public beta of HCP Terraform Stacks. This new functionality helps organizations scale infrastructure faster and easier by aggregating multiple Terraform modules into a stack. This reduces the need for manual dependency management and enables consistent infrastructure creation and customization with a single action.

In addition, Terraform Stacks introduces the ability to manage Kubernetes workloads from a single configuration, which reduces the complexity of Kubernetes deployments and shortens time-to-market. The new “deferred changes” feature helps deal with unknown values, making planning large-scale deployments easier.

Packer and Nomad bring enhancements for access and GPU support

HCP Packer now provides enhanced metadata insights into CI/CD pipelines, allowing organizations to identify risks in the infrastructure before they manifest. With the introduction of bucket-level RBAC, teams can refine access to specific buckets, providing a more secure image management environment.

Nomad, HashiCorp’s workload management tool, now has support for Multi-Instance GPU (MIG), which is important for organizations that use GPUs for demanding tasks such as machine learning and AI. This new functionality allows multiple users to share GPU resources, resulting in better utilization of expensive hardware.

With these new features, HashiCorp reaffirms their commitment to making infrastructure management less complex and more secure. By providing automation and enhanced observation capabilities, it enables companies to manage their cloud infrastructures at scale without sacrificing security or efficiency.

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