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Research shows that over 90% of large organizations already deploy multicloud architectures, and their data is distributed across several public cloud providers. Additionally, data is also increasingly split across various storage systems such as warehouses, operational and relational databases, object stores, etc. With the proliferation of new applications, data is serving many more use cases such as data sciences, business intelligence, analytics, streaming and the list goes on. With these data trends, customers are increasingly gravitating towards an open multicloud data lake. However, multicloud data lakes present several challenges such as data silos, data duplication, fragmented governance, complexity of tools, and increased costs.With Google’s data cloud technologies, customers can leverage the unique combination of distributed cloud services. They can create an agile cross-cloud semantic business layer with Looker and manage data lakes and data warehouses across cloud environments at scale with BigQuery and capabilities like BigLake and BigQuery Omni. BigLake is a storage engine that unifies data warehouses and lake houses by standardizing across different storage formats including BigQuery managed table and open file formats such as Parquet and Apache Iceberg on object storage. BigQuery Omni provides the compute engine that runs locally to the storage on AWS or Azure, which customers can use to query data in AWS or Azure seamlessly. This provides several key benefits such as:A single pane of glass to query your multicloud data lakes (across Google Cloud Platform, Amazon Web Services, and Microsoft Azure)Cross-cloud analytics by combining data across different platforms with little to no egress costsUnified governance and secure management of your data wherever it residesIn this blog, we will share cross-cloud analytics use cases customers are solving with Google’s Data Cloud and the benefits they are realizing.Unified marketing analytics for 360-degree insightsOrganizations want to perform marketing analytics – ads optimization, inventory management, churn prediction, buyer propensity trends and many more such analytics. To do this before BigQuery Omni, customers had to use data from several different sources such as Google Analytics, public datasets and other proprietary information stored across cloud environments. This requires moving large amounts of data, managing duplicate copies and incremental costs to perform any cross-cloud analytics and derive actionable insights. With BigQuery Omni, organizations are able to greatly simplify this workflow. Using the familiar BigQuery interface, users can access data residing in AWS or Azure, discover and select just the relevant data that needs to be combined for further analysis. This subset of data can be moved to Google Cloud using Omni’s new Cross-Cloud Transfer capabilities. Customers can combine this data with other Google Cloud datasets and these consolidated tables can be made available to key business stakeholders through advanced analytics tools such as Looker and Looker Studio. Customers are also able to tie in this data now with world class AI models via Vertex AI.As an illustrative example, consider a retailer who has sales & inventory, user and search data spread across multiple data silos. Using BigQuery Omni they can seamlessly bring these datasets together and power several marketing analytics scenarios like customer segmentation, campaign management and demand forecasting etc.”Interested in performing cross-cloud analytics, we tested BigQuery Omni and really liked the SQL support to easily get data from AWS S3. We have seen great potential and value in BigQuery Omni for adopting a multi-cloud data strategy.” — Florian Valeye, Staff Data Engineer,Back Market, a leading online marketplace for renewed technology based out of FranceData platform with consistent and unified cross-cloud governanceAnother pattern is customers looking to analyze operational, transactional and business data across data silos in different clouds through a unified data platform. These data silos are a result of various factors such as merger and acquisitions, standardization of analytical tools, leveraging best of breed solutions in different clouds and diversification of data footprint across clouds. In addition to a single pane of glass for data access across silos, customers deeply desire consistent and uniform governance of their data across clouds. With BigLake and BigQuery Omni abstracting the storage and compute layers respectively, organizations can access and query their data in Google Cloud irrespective of where it resides. They can also set fine-grained row level and column access policies in BigQuery and consistently govern it across clouds. These building blocks enable data engineering teams to build a unified and governed data platform for their data users without having to deal with the complexity of building and managing complex data pipelines. Furthermore, with BigQuery Omni’s integration with Dataplex and Data Catalog, you can discover, search your data across clouds and enrich your data by adding relevant business context with business glossary and rich text.”Several SADA customers use GCP to build and manage their data analytics platform. During many explorations and proofs of concepts, our customers have seen the great potential and value in BigQuery Omni. Enabling seamless cross-cloud data analytics has allowed them to realize the value of their data quicker while lowering the barrier to entry for BigQuery adoption in a low-risk fashion.” — Brian Suk, Associate Chief Technology Officer,SADA, one of the strategic partners of Google Cloud.Simplified data sharing between data providers and their customersA third emerging pattern in cross cloud analytics is data sharing. Several services have the business need to share information such as inventory data, subscriber data to their customers or users who in turn analyze or aggregate the data with their proprietary data and oftentimes share the results back with the service provider. In several cases, the two parties are on different cloud environments, requiring them to move data back and forth. Consider an example from a company like ActionIQ that operates in the customer data platform (CDP) space. CDPs were designed to help activate customer data, and a critical first step of that was unifying and managing that customer data. To enable this, many CDP vendors built their solution choosing one of the available cloud infrastructure technologies and copied data from the client’s systems.“Copying data from client applications and infrastructure has always been a requirement to deploy a CDP, but it doesn’t have to be anymore” — Justin DeBrabant, Senior Vice President of Product, ActionIQ.While a small percentage of customers are fine with moving data across cloud environments, the majority are hesitant to onboard new services and would rather prefer providing governed access to their data sets. “A new architectural pattern is emerging, allowing organizations to keep their data at one location and make it accessible, with the proper guardrails, to applications used by the rest of the organization’s stack”addsJustin at ActionIQ.With BigQuery Omni, services in Google Cloud Platform can more easily access and share data with their customers and users in other cloud environments with limited data movement. One of UK’s largest statistics providers has explored Omni for their data sharing needs.”We tested BigQuery Omni and really like the ability to get data from AWS directly into BQ. We’re excited about managing data sharing with different organizations without onboarding new clouds” – Simon Sandford-Taylor, Chief Information and Digital Officer, UK’s Office for National StatisticsWith BigQuery Omni, customers are able to:Access and query data across clouds through a single user interfaceReduce the need for data engineering before analyzing dataLower operational overhead and risks by deploying an application that runs across multiple clouds which leverages the same, consistent security controlsAccelerate access to insights by significantly reducing the time for data processing and analysis Create consistent and predictable budgeting across multiple cloud footprints Enable long term agility and maximize the benefits every cloud investmentOver the last year, we’ve seen great momentum in customer adoption and added significant innovations to BigQuery Omni including improved performance and scalability for querying your data in AWS S3 or Azure Blob Storage, Iceberg support for Omni, Larger query result set size up to 10GB and Cross-cloud transfer that helps customers easily, securely, and cost effectively move just enough data across cloud environments for advanced analytics. BigQuery Omni has launched several features to support unified governance of your data across multiple clouds – you can get fine-grained access to your multi-cloud data with row level and column level security. Building on this, we are excited to announce that BigQuery Omni now supports data masking. We’ve also made it easy for customers to try and see the benefits of BigQuery Omni through the limited time free trial available until March 30, 2023. BigQuery Omni running on other public clouds outside of Google Cloud is available in AWS US East1 (N.Virginia) and Azure US East2 (US East) regions. We are also excited to share that we will be bringing BigQuery Omni to more regions in the future, starting with Asia Pacific (AWS Korea) coming soon.Getting StartedGet started with a free trial to learn about Omni. Check out the documentation to learn more about BigQuery Omni. You can also leverage the self paced labs to learn how to set up BigQuery Omni easily.
Quelle: Google Cloud Platform

16. Dezember 2022

da Agency

Learn how Microsoft datacenter operations prepare for energy issues

The war in Ukraine and the resultant shortage of natural gas has forced the European Union (EU) and European countries to proactively prepare for the possibility of more volatile energy supplies—both this winter and beyond. Microsoft is working with customers, governments, and other stakeholders throughout the region to bring clarity, continuity, and compliance in the face of possible energy-saving strategies at the local and national level. In solidarity with Europe, where even essential services are likely to be asked to find energy savings, we have validated plans and contingencies in place to responsibly reduce energy use in our operations across Europe, and we will do so in a way that minimizes risk to customer workloads running in the Microsoft Cloud.

We want to share some of the contingencies and mitigations that our teams have put in place to responsibly operate our cloud services.

Supporting grid stability by responsibly managing our energy consumption

The power that is consumed by Microsoft from the utilities is primarily used to power our network and servers, cooling systems, and other datacenter operations. We have contingency plans to contribute to energy grid stability, while working to ensure minimal disruption to our customers and their workloads, including:

The scale and distribution of the Microsoft datacenters gives us the ability to reposition non-regional platform as a service (PaaS) services, internal infrastructure, and many of our internal non-customer research and development (R&D) workloads to other nearby regions, while still meeting our data residency and EU Data Boundary commitments.
Actively working with local governments and large organizations to closely monitor and respond to power consumption to ensure grid stability and minimal disruption to our customers’ critical workloads. We are working with local utility providers to ensure our systems are ready for a range of circumstances.
Our datacenter regions are planned and built to withstand grid emergencies. When needed, we quickly transition to backup power sources to reduce impact on the grid without impacting customer workloads.

Resilient infrastructure investment

Microsoft is responsible for providing our customers with a resilient foundation in the Microsoft Cloud—in how it is designed, operated, and monitored to ensure availability. We make considerable investments in the platform itself—physical things like our datacenters, as well as software things like our deployment and maintenance processes.

We strive to provide our cloud-using customers with “five-nines” of service availability, meaning that the datacenter is operational 99.999 percent of the time. However, knowing that service interruptions and failures happen for a myriad of reasons, we build systems designed with failure in mind.

We have Azure Availability Zones (AZs) in every country in which we operate datacenter regions. AZ’s are comprised of a minimum of three zone locations, each with independent power, cooling and networking, allowing customers to spread their infrastructure and applications across discrete and dispersed datacenters for added resiliency and availability.

Battery backup and backup generators are an additional resiliency capability we implement and are utilized during power grid outages and other service interruptions so we can meet service levels and operational reliability. We have contracted access to additional fuel supplies to maintain generator operations, and we also hold critical spares to maintain generator health. We are ready to use backup generators across Europe, when necessary, to keep our services running in case of a serious grid emergency.

Across our global infrastructure, it’s not unusual for us to work with a heightened operational awareness, due to external factors. For instance, severe winter weather events in Texas in 2021 caused substantial pressure on the Texas energy grid. Microsoft was able to remove its San Antonio datacenter from using grid power. Although Microsoft’s onsite substations were designed with redundancy, we were able to quickly transition to our tertiary redundant systems—generators. These systems kept the datacenters running, with zero impact to our cloud customers, while the utility grid could ensure residential homes stayed warm. During this event, we maintained 100 percent uptime for our customers, while removing our workloads from the grid.

Resiliency recommendations for cloud architectures

This is a challenging time for organizations monitoring the growing energy concerns in Europe. We are providing important infrastructure for the communities where we operate, and our customers are counting on us to provide reliable cloud services to run their critical workloads. We recognize the importance of continuity of service for our customers, including those providing essential services: health care providers, police and emergency responders, financial institutions, manufacturers of critical supplies, grocery stores and health agencies. Organizations wondering what more they can do to improve the reliability of their applications, or wondering how they can reduce their own energy consumption, can consider the following:

Customers who have availed themselves of high availability tools, including geo-redundancy, should be unaffected by impacts to a single datacenter region. For software as a service (SaaS) services like Microsoft 365, Microsoft Dynamics 365, and Microsoft Power Platform, the business continuity and resiliency are managed by Microsoft. For Microsoft Azure, customers should always consider designing their Azure workloads with high availability in mind.

We always encourage customers to have a Business Continuity and Disaster Recovery (BCDR) plan in place as part of the Microsoft Well-Architected Framework, which you can read more about. Customers who want to proactively migrate their Azure resources from one region to another can do so at any time. Find out how.
On-premises customers can reduce their own energy consumption by moving their applications, workloads, and databases to the cloud. The Microsoft Cloud can be up to 93 percent more energy efficient than traditional enterprise datacenters, depending on the specific comparison being made. Discover more here. Start your sustainability journey today.
Energy use in our datacenters is driven by customer use. Customers can play a part in reducing energy consumption by following green software development guidelines, including shutting down unused server instances, and sustainable application design. Further information available here.

We continue to improve the energy efficiency of our datacenters, in our ongoing commitment to make our global infrastructure more sustainable and efficient. As countries and energy providers consider options to reduce their consumption of electricity in the event of an energy capacity shortage, we are working with grid operators on this evolving situation. With the scale, expertise, and partnerships that we operate, we are confident that our risk mitigation activities will offset any potential disruption to our customers running their critical workloads in the cloud.
Quelle: Azure