Specify multiple specifications when you create pods to improve the creation success rate - Elastic Container Instance

When you create a large number of elastic container instances (pods), the resources that you can use may be insufficient. In this case, we recommend that you specify multiple specifications. The system tries to create the pods based on the sequence of the specified specifications. This improves the creation success rate.

Background information

If you specify multiple specifications when you create an elastic container instance, the system tries to use the specifications in sequence. This improves the creation success rate.

Note

During the retry, the instance remains in the Pending state.
The multi-specification mode is effective at the instance level and only affects the creation policy of a single instance.
You can also specify multiple zones when you use the multi-specification mode. This further improves the creation success rate.

Supported specifications

vCPU and memory specifications supported by Elastic Container Instance

Specifications supported in all regions where Elastic Container Instance is available

vCPU	Memory (GiB)	Bandwidth (bidirectional, Gbit/s, theoretical upper limit)
0.25	0.5 and 1	0.08
0.5	1 and 2	0.08
1	2, 4, and 8	0.1
2	1, 2, 4, 8, and 16	1
4	2, 4, 8, 16, and 32	1.5
8	4, 8, 16, 32, and 64	2
12	12, 24, 48, and 96	2.5
16	16, 32, 64, and 128	3
24	24, 48, 96, and 192	4.5
32	32, 64, 128, and 256	6
52	96, 192, and 384	12.5
64	128, 256, and 512	20

Specifications supported only in some regions

Important

The specifications contained in the following table are supported only in some regions. When you create an elastic container instance that has one of the following specifications, make sure that the corresponding specifications are supported in the specified region and zone. Otherwise, the instance cannot be created because no resources exist in the region and zone.
The regions that support the specifications contained in the following table include: China (Hangzhou), China (Shanghai), China (Qingdao), China (Beijing), China (Zhangjiakou), China (Hohhot), China (Ulanqab), China (Shenzhen), China (Heyuan), China (Guangzhou), China (Chengdu), and Singapore.
You cannot use the specifications in the following table to create preemptible instances.

vCPU	Memory (GiB)	Bandwidth (bidirectional, Gbit/s, theoretical upper limit)
2	6, 10, 12, and 14	1
4	6, 10, 12, 14, 18, 20, 22, 24, 26, 28, and 30	1.5
6	6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, and 48	1.5
8	10, 12, 14, 18, 20, 22, 24, 26, 28, 30, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, and 62	2.5

ECS instance families supported by Elastic Container Instance

x86-based enterprise-level computing instance families

x86-based ECS instance types are based on the x86 architecture. Each vCPU corresponds to a hyper-thread of a processor core. They deliver stable performance and are suitable for scenarios such as enterprise-level applications, database systems, video encoding and decoding, and data analysis.

Category	x86-based enterprise-level instance family
General-purpose instance families	g8a, g8i, g7a, g7, g6e, g6a, g6, g5, sn2, and sn2ne
Compute-optimized instance families	c8a, c8i, c7a, c7, c6e, c6a, c6, c5, sn1, and sn1ne
Memory optimized instance families	r8a, r8i, r7a, r7, r6e, r6a, r6, r5, se1ne, and se1
General compute category instance families	u1
Compute-intensive instance families	ic5
Instance families with high clock speeds	hfg8i, hfg7, hfg6, and hfg5 hfc8i, hfc7, hfc6, and hfc5 hfr8i and hfr7
Big data instance families	d1 and d1ne
Instance families with local SSDs	i2 and i2g

Enterprise-level heterogeneous computing instance families

GPU-accelerated ECS instance types contain GPUs and are suitable for scenarios such as deep learning and image processing. GPU-related Docker images can be directly run on a GPU-accelerated elastic container instance. A NVIDIA GPU driver is pre-installed in the instance. The supported driver and CUDA versions vary with GPU types.

Category	GPU-accelerated instance family	Driver and CUDA versions
vGPU-accelerated instance families	sgn7i-vws	NVIDIA 470.161.03 and CUDA 11.4
	vgn7i-vws
	vgn6i-vws
GPU-accelerated compute-optimized instance families	gn7e	NVIDIA 470.82.01 and CUDA 11.4 (default) NVIDIA 525.85.12 and CUDA 12.0 NVIDIA 535.161.08 and CUDA 12.2
	gn7i
	gn7s
	gn7
	gn6v
	gn6e
	gn6i
	gn5i
	gn5

Arm-based enterprise-level computing instance families
Arm-based ECS instance types are based on the ARM architecture. Each vCPU corresponds to a physical core of a processor. They deliver stable performance and provide exclusive resources. They are suitable for scenarios such as containers, microservices, website and application servers, high-performance computing, and CPU-based machine learning.
Category
Arm-based instance family
General-purpose instance families
g8y
Compute-optimized instance families
c8y
Memory optimized instance families
r8y
x86-based shared computing instance families
Shared ECS instance types are suitable for small and medium-sized websites and individuals. Compared with enterprise-level ECS instance types, shared ECS instance types emphasize the sharing of resource performance to maximize resource utilization. In this case, the stability of computing performance cannot be ensured, but the cost is reduced.
Category
x86-based shared instance family
Economy instance families
e

For more information about ECS instance families, see the following topics:

Configuration description

You can add the k8s.aliyun.com/eci-use-specs annotation to the metadata of the configuration file of a pod to specify specifications for the instance.

When you specify multiple specifications, you can specify vCPU and memory specifications or ECS instance types. You can also specify both of them.
Important
After the pod is created, you can check the specifications that are actually used by the pod in the k8s.aliyun.com/eci-instance-spec field in the YAML file of the pod. If the pod uses an ECS instance type, you are charged based on the ECS instance type. If the pod uses vCPU and memory specifications, you are charged based on the number of vCPUs and memory size.
You must specify specifications in a priority order. A maximum of five specifications can be specified.
If you want to create GPU-accelerated elastic container instances, elastic container instances that use local disks, or Arm-based elastic container instances, you can only specify corresponding specifications. The specifications that do not support the preceding features cannot be specified.

The following code provides sample configurations:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: test
  labels:
    app: test
spec:
  replicas: 2
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      name: nginx-test
      labels:
        app: nginx
        alibabacloud.com/eci: "true" 
      annotations:
        k8s.aliyun.com/eci-use-specs: 2-4Gi,ecs.c5.large,ecs.c6.large  # Sets the specifications that you want to use to create the pod. Replace the value by using the actual specifications.
    spec:
      containers:
      - name: nginx
        image: registry.cn-shanghai.aliyuncs.com/eci_open/nginx:1.14.2
        ports:
        - containerPort: 80

Category	Arm-based instance family
General-purpose instance families	g8y
Compute-optimized instance families	c8y
Memory optimized instance families	r8y

Category	x86-based shared instance family
Economy instance families	e