# Building Burstables: Unleashing CPU Efficiency with Cgroups

## Building Burstables: Unleashing CPU Efficiency with Cgroups

The rise of cloud computing has fueled a constant quest for efficient resource utilization. One key technique emerging to address this need is the creation of “burstables” – virtual machines or containers designed to handle occasional spikes in demand without being consistently provisioned with excessive resources. A recent article on Ubicloud, authored by msarnowicz, delves into the technical intricacies of achieving this using Linux control groups (cgroups), offering a valuable resource for developers and system administrators.

The article, titled “Building Burstables: CPU slicing with cgroups,” explores how cgroups can be leveraged to precisely allocate CPU resources to different processes. Cgroups, a powerful Linux kernel feature, allow for the grouping and management of processes, enabling administrators to control resources like CPU, memory, and I/O bandwidth. The focus here is specifically on CPU slicing, a technique that divides available CPU time among different cgroups.

The core concept behind burstables is to provide a baseline level of CPU performance while allowing instances to “burst” beyond that baseline when needed. This is particularly useful for workloads that experience intermittent periods of high activity, such as web servers handling fluctuating traffic or background processes executing scheduled tasks. Without burstable configurations, these workloads would require being provisioned with resources sufficient to handle the peak load constantly, leading to significant resource waste during periods of low activity.

The Ubicloud article likely details the practical steps involved in configuring cgroups for CPU slicing. This would likely include:

* **Creating and configuring cgroups:** Setting up the hierarchical structure of cgroups and defining the resources to be managed within each group.
* **Setting CPU limits:** Utilizing cgroup parameters like `cpu.shares`, `cpu.cfs_period_us`, and `cpu.cfs_quota_us` to define the minimum CPU allocation and burst capacity for each instance.
* **Monitoring and tuning:** Observing the CPU usage of different cgroups and adjusting the limits to optimize performance and prevent resource starvation.
* **Considerations for performance:** The article likely touches upon potential performance bottlenecks and best practices for minimizing overhead when using cgroups for CPU slicing.

While the specific implementation details are not outlined in the provided information, the premise of the article highlights a critical aspect of modern cloud infrastructure: achieving optimal resource utilization. By providing a mechanism to fine-tune CPU allocation and enable burstable instances, cgroups offer a powerful tool for developers and system administrators to reduce costs, improve efficiency, and better serve fluctuating workload demands. The Ubicloud article appears to be a valuable contribution to this ongoing discussion, offering practical insights into building burstables and effectively utilizing the power of cgroups for CPU slicing.