Container Management Built for the Edge
A Streamlined, Resilient Alternative to Bulky Container Platforms
Container technology rapidly transforms how organizations develop, deploy, and scale applications, especially as the push for edge computing and hybrid cloud environments grows. From accelerating microservice deployments to enabling lightweight infrastructure at the edge, containerized workloads offer unmatched flexibility and efficiency. However, traditional container management software and platforms often introduce unnecessary complexity, requiring deep technical expertise and bulky infrastructure not optimized for distributed or resource-constrained environments.
Purpose-built for reliability, Scale Computing™ provides solutions for containerization on computing environments ranging from core data centers to the most remote edge locations. Instead of layering container management tools on top of an already complex stack, these solutions offer a streamlined, cost-effective alternative for edge computing without sacrificing performance, resilience, or manageability.
Simplified Container Management
With Scale Computing for container management, simplicity isn’t just a feature; it’s foundational. Here’s how our container infrastructure delivers measurable advantages across your IT operations:
Deploy containers and virtual machines in minutes with built-in orchestration and centralized management, no Kubernetes expertise required.
Run containerized workloads and VMs side-by-side on the same hardware to eliminate waste and maximize performance at the edge or core.
Easily scale up or down, add nodes without disruption, and deploy containers at the edge, in a centralized data center, or in hybrid environments, all from a single platform.
Scale Computing has been a true partner throughout this innovation journey, delivering what we need quickly and reliably. But more than that, it has actively participated in the process to ensure we build our solutions in a way that best enables them for success.
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Avolta Future-Proofs Retail & Hospitality IT
Avolta runs Windows VMs and Linux-based containers side by side, deployed seamlessly through UI or API integrations. This eliminates the need for fragmented appliances while improving deployment speed.
How Scale Computing Simplifies Containerized Workloads
Scale Computing simplifies containerized workload management with hyperconverged infrastructure, lightweight orchestration, and edge computing solutions.
Easy Implementation
Container deployments often involve many containers working together to support modern applications, such as microservices. Loosely-coupled architectures require rapid, easy, and consistent container deployment. It simply wouldn’t be effective to manually create and configure containers due to time constraints and the risk of human error. Built-in automation capabilities radically improve a DevOps team’s ability to programmatically deploy consistent containers across sites while reducing required manual intervention.
- Facilitate complete infrastructure-as-code container deployment
- Save time automating manual steps in site and application setup
- Reduce human error from manual setup
- Ensure deployment consistency across sites
- Enable consistent change control and more reliable updates through standardization
High Availability with Containers
Implementing high availability in container deployments is one of the biggest challenges. It is usually solved through a tool like Kubernetes (k8s), where the user implements redundancy at the container-cluster level. If k8s isn’t required beyond providing application-level redundancy, Scale Computing simplifies redundancy by ensuring both compute and data storage are provided at the infrastructure level through our existing, easy-to-use technology.
API-Driven Deployment and Automation
Automation is the difference between managing a few deployments and operating at real scale. Our expanding REST API capabilities, paired with a services-led operating model, make it easier to automate everyday platform operations, integrate with existing tooling, and standardize how environments are deployed and maintained, especially when you're rolling out containerized and VM-based workloads across many systems, distributed sites, and thousands of locations.
Our platform plugs cleanly into established automation workflows. With our Terraform Provider, we enable repeatable provisioning and lifecycle management of the underlying infrastructure resources (so environments can be created, changed, and torn down consistently). With a Red Hat Ansible-compatible Collection, teams can orchestrate configuration and day-to-day operational tasks in a way that fits existing automation practices, reducing manual effort and minimizing drift over time. Paired with our services-led operating model, teams execute rollouts faster and operate more consistently at scale—especially when limited local IT and strict uptime requirements make standardization essential.
Application Lifecycle Management (ALM) adds a higher-level control plane for deploying and running applications, supporting standardized rollout processes, updates, and ongoing management across distributed environments. Together, these capabilities help teams move from one-off scripts to a more durable automation strategy: consistent deployments, fewer repetitive tasks, and faster, safer change at scale.
Container Runtime Options
Choosing a container runtime ultimately involves a trade-off between flexibility and standardization. Some teams want the freedom to align with existing internal standards and tooling. Others want a single, consistent runtime that reduces variability across environments, especially when they're deploying across many sites with limited local IT support.
Our solutions give teams the latitude to run containerized workloads in a way that fits their environment and operating model, without forcing a one-size-fits-all runtime decision. That's especially valuable when different application teams have different requirements, or when you're evolving your container approach over time and don't want your infrastructure to be the constraint.
For teams that want a single, consistent runtime, our platform also supports a Docker-only path, which simplifies validation, troubleshooting, and repeatability. By reducing runtime variability, teams can more confidently deploy the same application pattern across environments and sites, with fewer "works here, breaks there" surprises. For many customers, that consistency—paired with our services-led operating model—is the fastest route to operational reliability and predictable outcomes at scale.
DevOps & CI/CD Pipelines
Developers want to build fast. Ops teams want to sleep at night. Scale Computing supports modern continuous integration/continuous delivery (CI/CD) workflows with a consistent infrastructure for both VMs and containers. By offering reliable container infrastructure with centralized management, Scale Computing supports agile workflows, CI/CD, and streamlined testing environments.
Scale Computing gives your DevOps toolchain flexible integration paths. Your team can self-service APIs and automation to connect to your existing CI/CD pipelines and workflows, or be backed by a services-led model where we handle integration end-to-end: implementing it in the POC, proving it works, and supporting it as you move toward production.
Whether you're building new microservices or iterating rapidly, you gain consistency from development to production, even in distributed environments.
Scale Computing keeps the focus where it belongs: running containers reliably on a resilient foundation, so your teams spend less time managing runtime differences and more time delivering applications.
Scale Computing keeps the focus where it belongs: running containers reliably on a resilient foundation, so your teams spend less time managing runtime differences and more time delivering applications.
SC//Insights: Containers
See What Others Have To Say About Scale Computing
We are proud to have over more than a thousand positive customer reviews on the most trusted third-party industry reviews websites. Read what our customers have to say on Gartner Peer Insights and G2.
