Learn more about the latest release, StarlingX 9.0!


StarlingX Single-Core Platform

By Davi Frossard on 27/06/2023

Introducing the Single-Core Platform on StarlingX 8.0, for All-In-One (AIO) deployments.

The StarlingX 8.0 release came out recently with a new feature that allows AIO deployments of StarlingX to run on a single core. In this blog post, we will explore the changes made to the system to make this possible, and the benefits it offers.

What is StarlingX Single-Core Platform?

Platforms running on multiple cores often consume significant amounts of computational resources. By enabling the single-core platform functionality, the system can allocate more resources to efficiently manage larger workloads. This optimization leads to enhanced resource availability for end-user applications. To better illustrate this concept, see the diagram below:

StarlingX Single-Core Platform Diagram

The use of a single physical core for platform services is only suitable for Intel® 4th Generation Xeon® Scalable Processors or above and should not be configured for previous Intel® Xeon® CPU families. For All-In-One systems with older generation processors, two physical cores (or more) must be allocated. Moreover, the feature can only be enabled with Hyper-Threading (one single physical core with two logical cores), ensuring proper overall parallelism and robustness for the system.

Starting with StarlingX 8.0, the default number of cores assigned to the platform for AIO deployments has been set to 1. This adjustment requires a careful balance to ensure that the performance remains unaffected despite having only one platform core. In the following sections, we will dive into some specific changes made to each service. By examining these modifications, we will gain a comprehensive understanding of how the system can operate in a single-core environment while preserving performance and stability.

Platform Adjustments

System Inventory

System Inventory (sysinv) is a key component of StarlingX, responsible for maintaining a centralized and comprehensive inventory of hardware devices and system configuration data. The sysinv service plays a vital role in the overall orchestration and operation of the StarlingX infrastructure, while it also demands significant computational resources, creating opportunities for optimization.

Periodic and Runtime Tasks

Sysinv consists of three main services: sysinv-conductor, sysinv-agent and sysinv-api. These services are designed to monitor system changes at periodic time intervals and take appropriate action as they occur. To optimize for a single-core platform, some of the sysinv-conductor and sysinv-agent periodic tasks have been enhanced. The primary changes involved refactoring legacy code, extending periodic time intervals, and breaking down large tasks into smaller ones. This allowed to minimize CPU usage spikes by reassessing individual time intervals and distributing their execution over time.

Remote Procedure Calls (RPC)

In previous versions, RPC communication between sysinv-api, sysinv-conductor and sysinv-agent processes relied on RabbitMQ as the communication transport layer. RabbitMQ uses a broker architecture responsible for delivering messages with a dedicated process, resulting in increased overhead. To avoid that, a new brokerless backend was developed using a library built on top of ZeroMQ for message queuing and MessagePack for data serialization.

Services Scale-Down

Platform services are typically designed with threads or worker processes that are proportional to the number of available cores on the platform. However, simply reducing the number of cores to just one may not be sufficient, as each service also has a minimum scale requirement. The footprint of certain services was reduced seeking to find a balance between minimum scale and overall performance.

This process of scaling down resource usage involves reducing the number of threads and workers assigned to services such as postgres, etcd, containerd, memcached, keystone, barbican, docker-registry, docker-token-server, kube-apiserver, and kubelet. It is important to note that worker allocation rules remain the same, with the changes affecting only applications that run on single core.

Numerous studies have demonstrated that optimal efficiency is achieved when the number of threads aligns with the available cores. This approach also helps to prevent any process from monopolizing the CPU, promoting fair resource allocation across the system.

Database Tuning

Adjustments have been made to certain parameters of Postgres services. These modifications aim to ensure a harmonious balance between system demand and CPU usage. Specifically, changes have been implemented in the number of workers, autovacuum operators, and the frequency of autovacuum operations. By fine-tuning the tool's configuration, the system can achieve optimal performance while efficiently managing database operations.

Other Optimizations

As part of the platform optimization efforts, an investigation was conducted to identify services that consumed significant computational resources. As a result, the overall system overhead was reduced by merging related services (sysinv-agent and sysinv-fpga-agent) and removing components that were no longer necessary (sm-watchdog).


In conclusion, the introduction of the single-core platform feature in StarlingX 8.0 for AIO configurations allows the system to efficiently handle larger workloads, with greater availability of resources for end-user applications. Throughout this blog post, we explored the various changes made to the system, including platform core adjustments, scaling down services and other enhancements. These modifications ensure that even with a single platform core, StarlingX's overall performance remains unaffected.

For further information about the feature, refer to the project documentation Single Physical Core for Platform Function in All-In-One Deployments.

For the complete list of updates and new features in StarlingX 8.0, check out the release notes and the project documentation.

Visit the StarlingX website today for further information about the project, check out the code, or download the latest image to try out the new features.