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Datadog Announces Kubernetes Autoscaling to Help Teams Intelligently Optimize Resources and Cloud Costs

Datadog Announces Kubernetes Autoscaling to Help Teams Intelligently Optimize Resources and Cloud Costs

datadog宣佈推出Kubernetes自動縮放功能,幫助團隊智能優化資源和雲成本
Datadog ·  06/26 12:00

New feature provides increased control and automation for Kubernetes environments

新功能提供了對Kubernetes環境的更多控制和自動化。

NEW YORK, June 26, 2024 /PRNewswire/ -- Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced Datadog Kubernetes Autoscaling, a set of capabilities that intelligently automates resource optimization and can automatically scale customers' Kubernetes environments based on real-time and historical utilization metrics. With this announcement, Datadog is the first observability vendor to enable customers to make changes to their Kubernetes environments directly from the platform.

2024年6月26日,紐約 / PRNewswire / -- Datadog納斯達克(DDOG)雲應用監控和安全平台宣佈了Datadog Kubernetes Autoscaling,這是一組能夠智能地自動優化資源的功能,並可以根據實時和歷史利用率指標自動擴展客戶的Kubernetes環境。Datadog是第一個允許客戶直接通過平台對Kubernetes環境進行更改的可觀察性供應商。

When deploying applications on Kubernetes, teams often choose to overprovision resources as a way to avoid infrastructure capacity issues from impacting end users. This can lead to a large amount of wasted compute and increased cloud costs. In fact, according to Datadog's recent report, State of Cloud Costs 2024, 83% of container costs were associated with idle resources. For this reason, it's critical organizations have a solution in place which can monitor resource usage and optimize infrastructure performance and computing costs while ensuring applications remain performant with enough resources to scale.

在Kubernetes上部署應用程序時,團隊經常選擇過量分配資源,以避免基礎架構容量問題影響最終用戶。這可能會導致大量計算資源的浪費和增加的雲成本。實際上,根據Datadog最新報告,83%的容器成本與閒置資源有關。因此,關鍵組織必須有一種解決方案,該解決方案可以監視資源使用情況並優化基礎架構性能和計算成本,同時確保應用程序保持性能良好,並具有足夠的資源進行擴展。Clo的狀態2024年雲服務器成本情況, Datadog Kubernetes Autoscaling不斷監視並自動調整Kubernetes資源。這可以爲組織的雲基礎架構帶來重大成本節省,並有助於確保工作負載的最佳應用性能,改善用戶體驗並提高容器資產的回報率。客戶能夠識別具有大量空閒資源的工作負載和群集,通過智能自動化實現一次性修復,或者啓用Datadog進行持續自動縮放工作負載。這些新功能使操作員能夠基於風險配置自己的成本和用戶體驗之間的權衡。

Datadog Kubernetes Autoscaling continuously monitors and automatically rightsizes Kubernetes resources. This leads to significant cost savings for an organization's cloud infrastructure and helps to ensure optimal application performance for workloads, improved user experiences and better ROI on container assets. Customers are able to identify workloads and clusters with a high number of idle resources, implement a one-time fix through intelligent automation or enable Datadog to automatically scale the workload on an ongoing basis. These new capabilities empower operators to decide the right balance on cost and user experience based on their risk profiles.

DDOG的產品副總裁Yrieix Garnier說:“容器是浪費成本的主要領域,因爲許多成本與閒置資源有關,但組織也無法冒險降低性能或沒有足夠的資源進行擴展。企業需要找到靈活控制和自動化的平衡點,這樣他們才可以在準備好採取自動化操作時進行操作。Datadog Kubernetes Autoscaling提供了這種平衡。通過將自動化Kubernetes調整與實時成本和性能數據連接起來,Datadog是唯一一個提供端到端可觀察性,安全性和資源管理的企業級統一平台,適用於任何基於Kubernetes的組織。

"Containers are a leading area of wasted spend because so many costs are associated with idle resources, but organizations also can't risk degrading performance or not having enough resources to scale. The key for businesses is to find a balance between control and automation where they can automate actions when they are ready," said Yrieix Garnier, VP of Product at Datadog. "Datadog Kubernetes Autoscaling provides this balance. By connecting automated Kubernetes rightsizing with real-time cost and performance data, Datadog is the only enterprise-grade, unified platform that provides end-to-end observability, security and resource management at scale for any Kubernetes-driven organization."

DDOG的Kubernetes Autoscaling幫助組織平衡靈活性、控制和自動化,以便他們可以:

Datadog Kubernetes Autoscaling helps organizations balance flexibility, control and automation so that they can:

Datadog Kubernetes 自動縮放幫助組織平衡靈活性、控制和自動化,以便他們能夠:

  • Control Cloud Costs: Optimize cloud costs and improve application performance with automated resource scaling for Kubernetes workloads within the Datadog platform.
  • Simplify, Democratize and Automate Resource Optimization: Teams can leverage a unified view and an intuitive UI that displays Kubernetes resource utilization and cost metrics, making it simple for any team member to understand and scale resources.
  • Unify Monitoring and Resource Management: Datadog's unified, enterprise-grade platform gives organizations full visibility into how rightsizing impacts their workload and cluster performance, backed by high-resolution trailing container metrics, so teams can take action based on this rich context.
  • 控制雲成本:通過Data****台內的Kubernetes工作負載自動縮放功能優化雲成本並改善應用程序性能。
  • 簡化、民主化和自動化資源優化:團隊可以利用統一視圖和直觀的UI,顯示Kubernetes資源利用率和成本指標,使任何團隊成員都可以輕鬆理解和擴展資源。統一監控和資源管理:Datadog的統一企業級平台爲組織提供了完整的可見性,以了解權益調整對其工作負載和集群性能的影響,支持高分辨率的追蹤容器指標,因此,團隊可以根據這個豐富的上下文采取行動。
  • 統一監控和資源管理:Datadog 的統一企業級平台爲組織提供完整的可見性,使他們能夠了解權大小調如何影響他們的工作負載和集群性能,支持高分辨率的容器後繼指標,因此團隊可以基於這個豐富的上下文采取行動。

Datadog Kubernetes Autoscaling is now in beta. To learn more, please visit: https://www.datadoghq.com/blog/datadog-kubernetes-autoscaling.

Datadog Kubernetes Autoscaling現已進入Beta版現在是測試版本。。要了解更多信息,請訪問:https://www.datadoghq.com/blog/datadog-kubernetes-autoscaling.

About Datadog

關於Datadog

Datadog is the observability and security platform for cloud applications. Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security and many other capabilities to provide unified, real-time observability and security for our customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.

Datadog是面向雲應用的可觀測性和安全性平台。我們的SaaS平台集成和自動化基礎設施監控,應用程序性能監控,日誌管理,用戶體驗監控,雲安全和許多其他功能,爲我們的客戶的整個技術棧提供統一的實時可觀測性和安全性。 Datadog被各種規模的組織和多個行業使用,以實現數字轉型和雲遷移,在開發,運營,安全和業務團隊之間促進合作,在應用程序上市時間上加快速度,減少故障解決時間,並確保應用程序和基礎架構的安全,了解用戶行爲並跟蹤關鍵業務指標。

Forward-Looking Statements

前瞻性聲明

This press release may include certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended including statements on the benefits of new products and features. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control, including those risks detailed under the caption "Risk Factors" and elsewhere in our Securities and Exchange Commission filings and reports, including the Quarterly Report on Form 10-Q filed with the Securities and Exchange Commission on November 7, 2023, as well as future filings and reports by us. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

本新聞稿可能包括某些根據1933年修訂版的《證券法》或《證券法》第27A條以及1934年修訂版的《證券交易法》或《證券交易法》第21E條的“前瞻性聲明”,包括有關新產品和功能的好處的聲明。這些前瞻性聲明反映了我們針對我們的計劃,意圖,期望,策略和前景的當前觀點,這些觀點基於我們目前擁有的信息和我們所做的假設。實際結果可能與前瞻性聲明中描述的結果有所不同,並且受到一系列假設,不確定性,風險和因素的影響,這些因素超出了我們的控制範圍,包括在我們的證券交易委員會文件和報告中的“風險因素”和其他地方所詳細描述的風險,包括在2023年11月7日向證券交易委員會提交的《第10-Q表格季度報告》以及我們今後提交的文件和報告。除法律要求外,我們不承擔更新本發佈中包含的任何前瞻性聲明的責任或義務,也不承擔因新信息,未來事件,期望變化或其他原因導致的責任或義務。

Contact
Dan Haggerty
press@datadoghq.com

聯繫人
丹·哈格蒂
press@datadoghq.com

SOURCE Datadog, Inc.

資料來源:Datadog,Inc。

譯文內容由第三人軟體翻譯。


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