Developers Practice Korean Server Kuaishou Guangsuan Cloud Image Management And Automated Deployment

to quickly locate the optical computing cloud image in the korean server region, it is recommended to use the "image market/custom image" filtering function of the console first or call the optical computing cloud api and filter by regional parameters (region=kr).

1. log in to the optical computing cloud console and select the region as south korea (kr). 2. use keywords and tags to filter the image list. for example, the image name contains "ubuntu", "centos" or the custom tag "quick find". 3. if using api: get /v1/images?region=kr&name=xxx&tag=fast-find.

to speed up searches, add unified tags to commonly used images (for example: quick search , stable, prod), and maintain a list of images (csv/json) for direct reference by ci/cd.

image management should focus on version control, label specifications, minimizing image size, regular patch updates, and automated snapshot strategies to ensure repeatable deployment and rapid rollback.

1. formulate the image naming rule: region-app-os-version (for example: kr-web-ubuntu20.04-v202605). 2. use snapshots and ami-style image management to regularly package production instances into images and create version numbers. 3. establish an image life cycle policy to automatically delete expired images and retain the latest n versions.

incorporate the image building process into ci (such as gitlab ci/github actions). each release triggers the image building and writes tags to facilitate quick search and rollback through tags.

it is recommended to combine terraform/ansible with cloud-init or image customization solutions to implement infrastructure as code (iac), automatically create instances through the optical computing cloud api and execute initialization scripts at startup to achieve end-to-end automated deployment.

1. use terraform to define network, subnet and instance resources, and specify the image id (from the optical computing cloud image ). 2. embed the cloud-init script in the instance resource to complete user and software installation. 3. use ansible to complete configuration management and application deployment after the instance is ready. 4. incorporate the entire process into the ci/cd pipeline to trigger automated deployment.

configure the image id and image label mapping (variables or parameterized templates) to select different images according to the environment (staging/prod) to facilitate quick switching on the korean server .

when deploying servers in south korea , you should pay attention to bandwidth, network latency, image preheating and regional cdn, and optimize the image volume and startup time to improve deployment speed and user experience.

1. compress and streamline the image, remove unnecessary software packages and enable image layer caching. 2. use the image pre-warm strategy to deploy and load necessary resources before traffic peaks. 3. deploy near-origin cdn or edge cache to reduce access latency for users in south korea.

enable and monitor instance startup time and network throughput, adjust mtu/tcp parameters, and enable concurrent pull rate limiting to avoid slow image distribution due to network congestion during batch deployment.

images should be hardened (minimum privileges, password login disabled, keys only), regularly patched, and snapshot backup and rollback processes established for rapid recovery and compliance auditing.

1. build an "immutable image" strategy, where all changes are published through new images rather than modifications within the instance. 2. remove sensitive information from the image and use the cloud key management service to inject credentials. 3. back up the image regularly and test the recovery process, and retain the backup strategy to meet rpo/rto requirements.

use iam roles to control image creation/deletion permissions and enable image operation audit logs. use automated recovery scripts to quickly restore services from the latest healthy image when a failure is detected.