Container Compute Service (ACS)

A cloud computing service that provides container compute resources that comply with the container specifications of Kubernetes

Why ACS

Compute power is delivered as serverless resources, which save you the need to manage and maintain nodes and clusters. ACS supports on-demand scaling and resource reservations, allowing you to use resources that are billed on a per-second basis. You can run the workloads of containerized applications and cloud services on top of ACS compute power at the same time.

  • Inclusive and Easy-to-use

    General-purpose and performance-enhanced pods are suitable for online business, and BestEffort pods are suitable for offline business. ACS allows you to quickly deploy workloads in the console or by using YAML files.

  • On-demand Scaling

    Creates tens of thousands of pods within a few minutes and adopts AHPA to further accelerate pod scale-out. This helps you easily handle unexpected traffic spikes.

  • Flexibility and Simplicity

    The core system components of Kubernetes clusters are fully hosted and clusters are automatically updated to patch versions, which greatly reduce the complexity of cluster O&M.

  • Elastic Resource Supply
    Flexible Resource Application

    The minimum compute resource specification is 0.25 vCores and 0.5 GiB of memory. The incremental step size of the CPU specification is 0.5 vCores, and the incremental step size of the memory specification is 1 GiB. You can flexibly apply for resources to reduce resource costs.

  • Pay-As-You-Go

    No fee is charged for cluster management and core system components. Resources are used on demand and billed on a per-second basis. You can also purchase savings plans to reduce costs based on a daily committed consumption. This helps you handle fluctuating workloads with cost-effectiveness.

  • Various Scenarios

    Applies to a wide array of scenarios. Container compute power can be provisioned in ACS clusters, ACK Pro clusters, and ACK One registered clusters on demand.

Feature

O&M and security
・By default, ACS is integrated with Managed Service for Prometheus, Simple Log Service, and CloudMonitor. With the preceding integrations, ACS enables observability and event-trigger alerting for clusters, pods, and applications from various perspectives.
・By default, ACS provides cluster inspections, diagnostics, and audit logging to scan security risks in Kubernetes clusters and resources.

Container computing
・To meet the requirements in various computing scenarios, ACS provides the following compute classes for pods: general-purpose, performance-enhanced, and BestEffort.
・ACS supports on-demand scaling and per-second pay-as-you-go billing. In addition, ACS supports savings plansthat provide discounts in exchange for daily usage commitments.

Kubernetes cluster management
・ACS is compatible with Kubernetes API operations and supports lifecycle management of enterprise-class containerized applications in Kubernetes clusters.
・ACS manages the key Kubernetes components and supports automatic and manual Kubernetes version updates.

Workload management
・ACS supports various workload types, including Deployment, StatefulSet, and Job.
・ACS supports manual scaling and allows you to configure auto scaling based on Horizontal Pod Autoscaler (HPA), CronHPA, and Advanced Horizontal Pod Autoscaler (AHPA)

Scenarios

ACS is oriented towards different business scenarios, defining various types of container computing power and computing quality, facilitating customers to choose according to their needs.

Container computing power type General-purpose (Default) General-purpose (BestEffort) Performance-enhanced (Default)
Applicable scenarios General-purpose online business:
Traffic fluctuations may occur in online business, such as microservices applications, web applications, and website applications. You can deploy the preceding types of online business in general-purpose pods to achieve cost-effectiveness. General-purpose pods can be launched within seconds and can be scaled at a large scale. This allows your business to handle traffic spikes and helps you avoid traffic loss and prevent resource waste that may occur when you manually scale workloads in advance.
Big data computing:
You can deploy latency-insensitive or fault-tolerant offline business, such as big data computing jobs, high-performance computing (HPC) applications, and audio and video processing tasks in BestEffort pods, which are cost-effective. This helps you make full use of computing resources to reduce resource costs. You can scale BestEffort pods at a large scale to reduce pending tasks and queuing requests, which greatly improves the efficiency of large-scale parallel computing jobs.
High-performance online business:
You can use performance-enhanced pods to deploy high-performance online business, such as high-performance gateway systems and high-performance gaming services.
Price vCPU From USD 0.00936/hour From USD 0.001872/hour From USD 0.01224/hour
Memory (GiB) From USD 0.0046/hour From USD 0.0009/hour From USD 0.006/hour

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