選取您的 Cookie 偏好設定

我們使用提供自身網站和服務所需的基本 Cookie 和類似工具。我們使用效能 Cookie 收集匿名統計資料,以便了解客戶如何使用我們的網站並進行改進。基本 Cookie 無法停用,但可以按一下「自訂」或「拒絕」以拒絕效能 Cookie。

如果您同意,AWS 與經核准的第三方也會使用 Cookie 提供實用的網站功能、記住您的偏好設定,並顯示相關內容,包括相關廣告。若要接受或拒絕所有非必要 Cookie,請按一下「接受」或「拒絕」。若要進行更詳細的選擇,請按一下「自訂」。

[O.SI.2] Centralize tooling for streamlined system instrumentation and telemetry data interpretation - DevOps Guidance
此頁面尚未翻譯為您的語言。 請求翻譯

[O.SI.2] Centralize tooling for streamlined system instrumentation and telemetry data interpretation

Category: FOUNDATIONAL

Centralized observability platforms are able to offer user-friendly, self-service capabilities to individual teams that simplify embedding visibility into system components and their dependencies. These tools streamline the onboarding process and offer auto-instrumentation capabilities to automate the monitoring of applications.

Adopt an observability platform that provides observability to teams using the X as a Service (XaaS) interaction mode as defined in the Team Topologies book by Matthew Skelton and Manuel Pais. The platform needs to support ingesting the required data sources for effective monitoring, and provide the desired level of visibility into the system components and their dependencies.

Onboarding to the platform should be easy for teams, or support auto-instrumentation to automatically monitor applications for a hands-off experience. This enables the organization to achieve real-time visibility into system data and improve the ability to identify and resolve issues quickly.

The observability platform should offer capabilities to follow requests through the system, the services it interacts with, the state of the infrastructure that these services run on, and the impact of each of these on user experience. By understanding the entire request pathway, teams can identify where slowdowns or bottlenecks occur, whether this latency is caused by hardware or dependencies between microservices that weren't identified during development.

As the observability platform matures, it could begin to offer other capabilities such as trend analysis, anomaly detection, and automated responses, ultimately aiming to reduce the mean time to detect (MTTD) and the mean time to resolve (MTTR) any issues. This can lead to reduced downtime and improved ability to achieve desired business outcomes.

Related information:

隱私權網站條款Cookie 偏好設定
© 2025, Amazon Web Services, Inc.或其附屬公司。保留所有權利。