2022年12月16日

容器化應用程序增加了雲成本組織正在為Kubernetes的雲成本管理而苦苦掙紮，一旦應用程序需求下降，就無法進行縮減，這是浪費雲支出的主要驅動力之一。這是CAST AI報告的主要發現之一，該報告深入分析了資源過度配置、雲成本過度支出以及由此導致的能源消耗浪費。該研究發現，平均而言，超過三分之一(37%)的雲原生應用程序的cpu從未被使用過，通過向適用的工作負載添加現貨實例，組織可以節省高達60%的成本。根據在亞馬遜網絡服務(AWS)、微軟Azure和穀歌雲平台(GCP)這三個全球最流行的雲服務上運行的應用程序的最高活動級別選擇集群進行分析。CAST AI的聯合創始人兼首席執行官勞倫特·吉爾(Laurent Gil)解釋說，過度配置有幾個原因，包括這對人類來說是一項“不可能完成的任務”。“超額配置是任何DevOps團隊的慣用手法，”他說。“想想看:開發人員和DevOps專業人員必須在600種不同形狀、內存和處理器中選擇正確的虛擬機組合。他們每隔幾秒鍾就得這麼做一次。”此外，DevOps團隊的主要優先事項一直是正常運行時間，幾乎所有DevOps團隊都有大量的內置超額配置，Gil說。他解釋了Kubernetes雲成本管理的一些最佳實踐，包括跟蹤每個已供應CPU的成本與請求CPU的成本。 “Why differentiate between the two? If you compare the number of requested versus provisioned CPUs, you can find a gap,” he says. “This gap is your cloud waste.” If you’re running a Kubernetes cluster that has yet to be optimized, you’ll see a difference between how much you’re provisioning and how much you’re actually requesting. “You spend money on provisioned CPUs and only end up requesting a small amount of them, so the price of individual requested CPUs grows,” Gil says. “Calculate how much you’re spending per requested CPU to make cost reporting more accurate.” He adds it’s also important to choose the right type and size of virtual machines, which starts with defining the organization’s requirements to provision only as much capacity as the workload really needs. “Cloud providers offer many different instance types matching a wide range of use cases with different combinations of CPU, memory, storage and networking capacity,” Gil says. “Each virtual machine type comes in one or more sizes to help you scale easily.” A third tip is to optimize Kubernetes autoscaling and ensure autoscaling policies don’t clash. “VPA automatically adjusts the requests and limits configuration to help you reduce overhead and cut costs. HPA, on the other hand, scales out – and more likely up than down,” he says. “That’s why you should make sure that your VPA and HPA policies aren’t interfering with each other.” He adds that when designing clusters for business- or purpose-class tier of service, it’s a good idea to review binning and packing density settings. Gil points out that spot instances are another great way to cut your Kubernetes bill, as they offer discounts reaching even 90% off the on-demand pricing. “But before jumping on this opportunity, take a look at your workload to see if it’s a good fit for spot instances,” he advises. He points out spot instances offer an incredible cost-saving opportunity, but they’re not a silver bullet and they might not be a good fit for every application out there. “That’s why it’s important to combine spot instance usage and automation with other cost management techniques,” he says. “For example, automated right-sizing, where the solution chooses the most cost-efficient virtual machine type and size for a given workload.” Finally, Gil recommends using an automation tool that does cloud optimization for the business. “AWS alone has some 400+ virtual machines on offer,” he notes. “What if your teams use different cloud providers? The manual effort of configuring resources, picking virtual machines and setting autoscaling policies will cost you more than its optimization impact.” He points out the market is full of cloud cost optimization and management solutions that take some or all of the above tasks off engineers’ shoulders, reclaiming time for teams to do more strategic work.