Einführung der Lieferung und des Ready>-Programms von AWS Control Tower

Der AWS Control Tower bietet die einfachste Möglichkeit, eine sichere AWS-Umgebung mit mehreren Konten einzurichten und zu verwalten, und reduziert die Komplexität und den Zeitaufwand für die Einrichtung einer Governance für mehrere AWS-Konten. Wir freuen uns, Delivery Partner für AWS Control Tower vorstellen zu können, die Beratungsservices für AWS Control Tower anbieten, sowie Ready Partner für AWS Control Tower, die Softwareprodukte zur Unterstützung von AWS Control Tower anbieten. Partner von AWS Control Tower erhalten präskriptive Anleitungen zum Aufbau von Lösungen auf Control Tower und ihre Angebote werden von AWS Solutions Architects geprüft.
Quelle: aws.amazon.com

G5-instances von Amazon EC2 sind jetzt in der Region Stockholm verfügbar

Ab heute sind Amazon Elastic Compute Cloud (Amazon EC2)-G5-Instances, die von NVIDIA A10G Tensor Core GPUs betrieben werden, in Stockholm verfügbar. G5-Instances können für zahlreiche grafikintensive und Machine-Learning-Anwendungsfälle eingesetzt werden. Sie bieten im Vergleich zu Amazon-EC2-G4dn-Instances eine bis zu 3-mal höhere Leistung für grafikintensive Anwendungen und Machine-Learning-Inferenz sowie eine bis zu 3,3-mal höhere Leistung beim Trainieren von einfachen bis moderat komplexen Machine-Learning-Modellen.
Quelle: aws.amazon.com

Amazon Aurora unterstützt den Export von Clustern zu S3

Amazon Aurora unterstützt jetzt den Export von Datenbank-Clustern direkt nach S3 im Apache Parquet-Format, ohne vorher einen Snapshot zu erstellen. Kunden können den Export nach S3 auch direkt aus dem Aurora-Datenbank-Cluster heraus initiieren, wodurch sie Zeit, Kosten und den zusätzlichen Aufwand für die Erstellung/Beibehaltung von Snapshots für den Datenexport nach S3 sparen.
Quelle: aws.amazon.com

Discover why leaders need to upskill teams in ML, AI and data

Tech companies are ramping up the search for highly skilled data analytics, AI and ML professionals, with the race to AI accelerating the crunch.1 They are looking for cloud experts  who can successfully build, test, run, and manage complex tools and infrastructure, in roles such as data analysts, data engineers, data scientists, and ML engineers. This workforce takes vast amounts of data and  puts it to work solving top business challenges, including customer satisfaction, production quality and operational efficiency. Learn about the business impact of data analytics, ML and AI skillsFind out how Google Cloud ML, AI and data analytics training and certification can empower your team to positively impact operations in our latest IDC Business Value Paper, sponsored by Google. Key findings include:69% improvement in staff competency levels31% greater data accuracy in products developed29% greater overall employee productivityDownload the latest IDC Business Value Paper, sponsored by Google, “The Business Value of Google Cloud ML, AI, Data Analytics Training and Certification.” (#US48988122, July 2022).Google Cloud customers prioritize ML, AI and data training to meet strategic organizational needsOur customers are seeing the importance and impact of data analytics, AI and ML training on their teams and business operations. The Home Depot (THD) upskilled staff on BigQuery to derive business insights and meet customer demand, with 92% reporting that training was valuable, and 75% confirming that they used knowledge from their Google Cloud training on a weekly basis.2THD was challenged with upskilling IT staff to extract data from the cloud in support of efficient business operations. Additionally, they were working on a very short timeline (weeks as opposed to years) to train staff to enable a multi-year cloud migration completion. This included thousands of employees and a diverse range of topics. Find out how they successfully executed this major undertaking by developing a strategic approach to their training program in this blog.LG CNS wanted to grow cloud skills internally to provide a high level of innovation and technical expertise for their customers. They enjoyed the flexibility and ability to tailor content to meet their objectives, and have another cohort planned.3Looking to drive digital transformation and solution delivery, LG CNS partnered with Google Cloud to develop a program that included six weeks of ML training through the Advanced Solutions Lab (ASL). Read the blog to learn more about their experience.Gain the latest data analytics, ML and AI skills on Google Cloud Skills BoostDiscover the latest Google Cloud training in data analytics, ML and AI on Google Cloud Skills Boost. Explore the role based learning paths available today which include hands-on labs and courses. Take a look at the Data Engineer, ML Engineer, Database Engineer and Data Analystlearning paths today for you and your team to get started on your upskilling journey. To learn about the impact ML, AI and data analytics training can have on your business, take a look at the IDC Business Value Paper, available for download now.1. Tech looks to analytics skills to bolster its workforce2. THD executed a robust survey directly with associates to gauge the business gains of the training program. Over the course of two years, more than 300 associates completed the training delivered by ROI Training.3. Google Cloud Learning services’ early involvement in the organizational stages of this training process, and agile response to LG CNS’s requirements, ensured LG CNS could add the extra week of MLOps training to their program as soon as they began the initial ASL ML course.
Quelle: Google Cloud Platform

Flexible committed use discounts — a simple new way to discount Compute Engine instances

Saving money never goes out of style. Today, many of our customers use Compute Engine resource-based committed use discounts (CUDs) to help them save on steady-state compute usage within a specific machine family and region. As part of our commitment to offer more flexible and easy ways for you to manage your spend, we now offer a new type of committed use discount for Compute Engine: flexible CUDs.Flexible CUDs are spend-based commitments that offer predictable and simple flat-rate discounts (28% off 1-year, and 46% off 3-years) that apply across multiple VM families and regions. Similar to resource-based CUDs, you can apply flexible CUDs across projects within the same billing account, and to VMs of different sizes and tenancy, to support changing workload requirements while keeping costs down. Today, Compute Engine flexible CUDs are available for most general-purpose (N1, N2, E2, N2D) and compute-optimized (C2, C2D) VM usage, including instance CPU and memory usage across all regions (refer to the complete list with more VM families to come). Similar to resource-based CUDs, flexible CUDs are discounts over usage, not capacity reservations. To ensure capacity availability, make a separate reservation, and CUDs will apply automatically to any eligible usage as a result.You can purchase CUDs from any billing account, and the discount can apply to any eligible usage in projects paid for by that billing account. When you purchase a flexible CUD, you pay the same commitment fee for the entirety of the commitment term, even if your usage falls below this commitment value. The commitment fee is billed monthly. Once a commitment is purchased, it cannot be canceled.For the best combination of savings and flexibility, you can combine resource-based CUDs and flexible CUDs together. You can have standard resource-based CUDs to cover your most stable resource usage and flexible spend based CUDs to cover your more dynamic resource usage. Every hour, standard CUDs apply first to any eligible usage followed by flexible CUDs, optimizing the use of your CUDs. Finally, any usage overage or usage that’s not eligible for either type of CUDs, will be charged based on your on-demand rates. Here is a quick summary of the differences between resource based CUDs and flexible CUDsWhat customers are saying about flexible CUDs“Media.net is a global company with dynamic resource requirements. With flexible CUDs, Media.net is able to quickly and easily save money on baseline workload requirements, while giving it the flexibility to use different machine types and regions. Media.net chose Spot VMs after exploring various options to support spiky workloads, as they provided Media.net with both deep discounts and simple, predictable pricing. Flexible CUDs and Spot VMs were the perfect combination to optimize costs for the dynamic capacity needs of the business.” — Amit Bhawani, Sr VP of Engineering, Media.net“As Lucidworks expands our product offerings, Google Cloud’s Flexible CUDs have been the perfect solution to optimize cost while giving us the flexibility to shift workloads to different regions based on customer demographics and different instance families based on performance characteristics.” — Matt Roca, Director of Cloud Governance and Security, LucidworksUnderstanding flexible CUDs You can purchase a flexible CUD in the Google Cloud console or via the API. A flexible CUD goes into effect one hour after purchase, and the discounts will automatically be applied to any eligible usage. Your flexible CUD is applied to eligible on-demand spend by the hour. If during a given hour, you spend less than what you committed to, you will not fully utilize your commitment or realize your full discount.For example: If you want to cover $100 worth of on-demand spend every hour by a flexible CUD, you will pay $54/hour (46% off) for 3 years (payable monthly), and receive a $100 credit that applies automatically to any eligible on-demand spend. The $100 credit burns down at the eligible on-demand rate for every eligible SKU, and expires if unused.Attributing flexible CUDs creditsIf you are running multiple projects within the same billing account, the credits from flexible CUDs are attributed proportionally across projects within the billing account and across SKUs within the same project according to their usage proportion.Planning for flexible CUDs purchasesA good way to think about how to purchase and use resource based CUDs with flexible CUDs is to first forecast and purchase resource based CUDs based on your steady state resource spend, to get the deepest discounts. A best practice is to use flexible CUDs for more variable and growing workloads, and to use on-demand VMs, or Spot VMs, for the rest of your usage. Get started with flexible CUDs todayBuilding a business in the cloud can be complicated; paying for it should be easy. We designed flexible CUDs to make it easy for organizations to enjoy significant discounts across a wide variety of Google Cloud resources in a way that’s simple and predictable. For more details on how to purchase and use flexible CUDs and to get started, refer to this documentation.
Quelle: Google Cloud Platform