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Liferay PaaS 導入チェックリスト
Liferay PaaS Go-Live Checklist Liferay Cloud is committed to your project's smooth launch. This go-live checklist should help you catch potential issues in advance and optimize your Cloud...
GitHubリポジトリの設定
Configuring Your GitHub Repository Your Liferay Cloud onboarding email contains a link to a GitHub repository hosted in the dxpcloud organization. This repository is a template for a team's...
GitHubリポジトリの設定
Configuring Your GitLab Repository Your Liferay Cloud onboarding email contains a link to a GitHub repository hosted in the dxpcloud organization. This repository is a template for a team's private...
Liferay SaaS 稼働開始チェックリスト
Liferay SaaS Go-Live Checklist Liferay Cloud is committed to your project's smooth launch. Here is a list of steps you should take to prepare in advance for your production environment to go live. ...
開発要件
Development Requirements Before beginning deployment in Liferay PaaS, developers planning to create modules should install the required tools. There are various development tools and frameworks...
Liferay PaaS体験:バックアップとリストア
Liferay PaaS Experience: Backup and Restore Backups in Liferay PaaS Experience capture two components of each environment's state: the CloudSQL database (via a database snapshot) and the document...
Liferay PaaS 体験:ユーザー管理
Liferay PaaS Experience: User Management Liferay PaaS Experience has no invite flow inside Argo CD, Argo Workflows, or Grafana themselves. Instead, you grant access to those tools from Customer...
アプリケーションメトリクス
Application Metrics With Liferay Cloud's built-in monitoring, you can track resources used by each environment service. These application metrics include memory and CPU usage, as well as network...
Liferay PaaS体験:オートスケーリング
Liferay PaaS Experience: Auto-Scaling Configure auto-scaling by editing Helm values in your GitOps repository. This is typically a developer or platform administrator's task rather than a general...
Liferay Cloudサービスへのログイン
Logging into Your Liferay Cloud Services By default, you must log in to access the web interfaces for the Liferay and Infrastructure services on any non-production environment (e.g., uat)....
Liferay PaaS 体験:ビルドとデプロイ
Liferay PaaS Experience: Builds and Deployment In Liferay PaaS Experience, customizations are delivered as overlays rather than as custom Liferay container images. An overlay is a set of artifacts...
Liferay PaaS 体験談:メトリクス
Liferay PaaS Experience: Metrics Grafana is the metrics interface for Liferay PaaS Experience environments. Liferay provisions and manages the full metrics stack: Google Managed Prometheus (GMP)...
Liferay PaaS体験:アラート
Liferay PaaS Experience: Alerts Grafana manages alerting for Liferay PaaS Experience environments. Liferay provisions a set of default alert rules that monitor the health of your environment and...
Liferay Cloud環境について
Understanding Liferay Cloud Environments A Liferay Cloud project can have multiple environments, each for a different purpose (e.g., development, staging, production, etc.). Each environment has a...
Liferay PaaS体験:シークレットの管理
Liferay PaaS Experience: Managing Secrets You manage secrets for your Liferay PaaS environments entirely through Argo CD, with no GCP account, IAM configuration, or gcloud access required. The...
Liferay PaaS の経験
Liferay PaaS Experience Liferay PaaS Experience is Liferay's managed cloud-native platform for deploying and operating Liferay DXP environments. Unlike Liferay PaaS, which centers around the...
Liferay PaaS体験:ログ
Liferay PaaS Experience: Logs Liferay manages the log collection and storage infrastructure. The Liferay container writes logs to standard output and error streams, and the platform forwards them...
管理と最適化
Manage and Optimize Liferay Cloud offers numerous tools to help you efficiently manage your projects. Resource Management The Liferay Cloud dashboard has built-in tools to help you track and...
Liferayサービスの拡張
Scaling the Liferay Service Liferay Cloud's auto-scaling feature adjusts the number of Liferay service instances based on demand to maintain performance. Configure the minimum and maximum number of...
環境自動一時停止によるリソースの最適化
Optimizing Resources with Environment Auto-Pause The Cloud platform monitors environment activity to detect idle periods. During inactivity, it scales down non-production environments (i.e, UAT and...

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