Enterprises can Push the Limits of Edge Even Further!
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Whether with the cloud or within their own data centers, enterprises have undergone a period of remarkable consolidation and centralization of their compute resources. But with the rise of ever more powerful mobile devices, and increasingly capable cellular networks, application architects are starting to think beyond the confines of the data center, and looking out to the edge.
What exactly do we mean by edge? Think of the edge as distributed compute happening on a wide variety of non-traditional devices — mobile phones of course, but also equipment sensors in factories, industrial equipment, or even temperature and reaction monitoring in a remote lab. Edge devices are also connected devices, and can communicate back to the mothership over wireless or cellular networks.
Equipped with increasingly powerful processors, these edge devices are being called upon to perform tasks that have thus far been outside the scope of traditional IT. For enterprises, this could mean pre-processing incoming telemetry in a vehicle, collecting video in kiosks at a mall, gathering quality control data with cameras in a warehouse, or delivering interactive media to retail stores. Enterprises are also relying on edge to ingest data from outposts or devices that have even more intermittent connectivity, e.g., oil rigs or farm equipment, filtering that data to improve quality, reducing it to right-size information load, and processing it in the cloud. New data and models are then pushed back to the edge; in addition, we can also push configuration, software, and media updates and decentralize processing workload.
Edge isn’t all about enabling new use cases – it’s also about right-sizing environments and improving resource utilization. For example, adopting an edge model can also relieve load on existing data centers.
But while edge computing is full of promise for enterprises, there are many pieces that are still works in progress. Further, developing edge workloads is very different from developing traditional applications, which enjoy the benefits of persistent data connections and run on well-resourced hardware platforms. As such, cloud architects are still in the early days of figuring out how to use and implement edge for their organizations.
Fortunately, there are tools you can use to help ease the transition to edge computing — and that likely fit into your organization’s existing computing systems. Kubernetes, of course, but also higher level management tools like Anthos, which provides a consistent control plane across cloud, private data center and edge locations. Other parts of the Anthos family – Anthos Config Management and Anthos Service Mesh — go one step further and provide consistent, centralized management to your edge and cloud deployments. And there’s more to come.
For the remainder of this blog post, we’ll dive deeper into the past and current state of edge computing, and the benefits that architects and developers can expect to see from edge computing. In a next post, we’ll take a deeper look at some of the challenges that designing for edge introduces, and some of the advantages the average enterprise has in adopting the edge model. Finally, we’ll look at the Google Cloud tools that are available today to help you build out your edge environment, and look at some early customer examples that highlight what’s possible today — and that will spark your imagination for what to do tomorrow.
The evolution of edge computing
The edge is not a new concept. In fact, it’s been around for the last two decades, spanning many use cases that are prevalent today. One of the first applications for edge was to use content delivery networks (CDN) to cache and serve daily static website pages near clients, for example, web servers in California data centers serving financial data to European customers.
As connectivity has improved and software evolved, the edge has evolved too, and the focus has shifted towards using edge to distribute services. First, simple services expanded from static HTML to javascript libraries or image repositories. Common functions like image transformation, credit and address validation support services followed. Soon, organizations were deploying more complex cloudlet and clustered microservices installations, as well as distributed and replicated datasets. The term “endpoint” became ubiquitous, and APIs profilerated.
In parallel, there’s been an explosion of creativity in hardware, microcontrollers and dedicated edge devices. Fit-for-purpose products were deployed globally. Services like Google Cloud IoT Core extended our ability to manage and securely connect these dispersed devices, allowing platform managers to register tools and leverage managed services like Pub/Sub and Dataflow for data ingestion. And with Kubernetes, large remote clusters — mini private clouds in and of themselves — operate as self-healing, autoscaling services across the broader internet, opening the door to new models for applications and architectural patterns. In short, both distributed asynchronous systems and economies have blossomed.
What does this mean for enterprises? For the purposes of this series, edge means you can now go beyond the corporate network, beyond cloud VPCs, and beyond hybrid. The modern edge is not sitting at a major remote data center, nor is it a CDN, cloud provider, or in a corporate data center rack — it’s just as likely to look like 100 of these attached to a thousand sensors.
Edge, in short, is about having hardware and devices installed at remote locations that can process and communicate back the information they collect and generate. The edge management challenge, meanwhile, is being able to push configuration and software/model/media updates to these remote locations when they are connected.
Enable new use cases
Today, we have reached a new threshold for edge computing — one where micro-data-processing centers are deployed as the edge of a fractal arm, as it were. Together, they form a broad, geographically distributed, always-on framework for streaming, collecting, processing and serving asynchronous data. This big, loosely coupled application system lives, breathes and grows. Always changing, always learning from the data it collects — and always pushing out updated models when the tendrils are connected.
Right now, the rise of 5G is pushing the limits of edge even further. Devices enabled with 5G can transmit using a mobile network — no ISP required — enabling connectivity anywhere within reach of a cell tower. Granted, these networks have lower bandwidth, but they are often more than adequate for certain types of data, for example fire sensors in forests bordering remote towns that emit temperature or carbon monoxide data periodically. Recently, Google Cloud partnered with AT&T to enhance business use of 5G edge technology but there is so much more that can be done.
Reduce data center investments
In addition to enabling the digitization of a broad range of new use cases, adopting edge can also benefit your existing data center.
Let’s face it: data centers are expensive to maintain. Moving some data center load to edge locations can reduce your data center infrastructure investment, as well as compute time spent there. Edge services tend to have much lower service level objectives (SLOs) than data center services, driving lower levels of hardware investment. Edge installations also tend to tolerate disconnectedness, and thus function perfectly well with lower SLOs — and lower costs.
Let’s look at an example of where edge can really reduce costs: big data. Back in the day, we used to build monolithic serial processors — state machines — that had to keep track of where they were in processing in case of failure. But time and again, we’ve seen that smaller, more distributed processing can break down big, expensive problems into smaller, more cost-effective chunks.
Starting with the explosion of MapReduce almost 20 years ago, big-data workloads were parallelized across clusters on a network, and state management was simplified with intermediate output to share, wait for, or restart processing from checkpoints. Those monolithic systems were replaced by cheaper, smarter, networked clusters and data repositories where parallel work could be executed and rendered into workable datasets.
Flash forward to today, and we are seeing those same concepts applied and distributed to edge data-collection points. In this evolution of big data processing, we are scaling up and out to the point where observation data is so massive that it must first be prefiltered, and then preprocessed down to a manageable size and still be actionable. Only then should it be written back to the main data repositories for more resource-intensive processing and model building.
In short, data collection, cleanup, and potentially initial aggregation happens at the edge location, which reduces the amount of junk data sitting in costly data stores. This increases performance of the core data warehouse, and reduces the size and cost of network transfers and storage!
The edge is a huge opportunity for today’s enterprises. But designing environments that can make effective use of the edge isn’t without its challenges. Stick around for part two of this series, where we look at some of the architectural challenges typically encountered while designing for the edge and how we begin to address them.
Google is named a Leader in 2020 Magic Quadrant for Cloud Infrastructure and Platform Services
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The capability gap between hyperscale cloud providers has begun to narrow; however, fierce competition for enterprise workloads extends to secondary markets worldwide. Infrastructure and operations leaders should evaluate cloud providers with a broad range of use cases and a wide market presence.
Market Definition/Description
Cloud computing is a style of computing in which scalable and elastic IT-enabled capabilities are delivered as a service using internet technologies. Cloud infrastructure and platform services (CIPS) are defined as standardized, highly automated offerings, in which infrastructure resources (e.g., compute, networking and storage) are complemented by integrated platform services. These include managed application, database and functions as-a-service offerings. The resources are scalable and elastic in near-real time and are metered by use. Self-service interfaces are exposed directly to the customer, including a web-based user interface (UI) and an API. The resources may be single-tenant or multitenant, and can be hosted by a service provider or on-premises in the customer’s data center.The scope of this Magic Quadrant has changed, compared with its predecessor, the “Magic Quadrant for Cloud Infrastructure as a Service.” Gartner has developed this Magic Quadrant to reflect the changing dynamics of cloud services offered and the ways that enterprise customers adopt them. Ultimately, hyperscale cloud providers, and the broad array of services they offer beyond infrastructure as a service (IaaS), have found strategic importance in Gartner’s enterprise clients and the Magic Quadrant needed to evolve to reflect as much.The scope of the Magic Quadrant for CIPS includes IaaS and integrated platform as a service (PaaS) platforms. These include application PaaS (aPaaS), functions as a service (FaaS), database PaaS (dbPaaS), application developer PaaS (adPaaS) and industrialized private cloud offerings that are often deployed in enterprise data centers.
Understanding the Vendor Profiles, Strengths and Cautions
CIPS providers that target enterprise and midmarket customers generally offer high-quality service, with excellent availability, good performance, high security and good customer support. Exceptions will be noted in this Magic Quadrant’s evaluations of individual providers. When we say “all providers,” we specifically mean “all the evaluated providers included in this Magic Quadrant,” not all CIPS providers in general. Keep the following in mind when reading the vendor profiles:
- All the providers have public cloud IaaS and PaaS offerings. Most also offer, or are in the process of building, industrialized private cloud offerings, in which every customer is on standardized infrastructure and cloud management tools. In some cases, the provider’s industrialized, on-premises offering may share similarities to hyperconverged infrastructure (HCI), but tethered to the cloud. However, this may not resemble the provider’s public cloud service in architecture or quality. A single architecture and feature set and cross-cloud management, for both public and private CIPS, make it easier for customers to combine and migrate across service models as their needs dictate. They also enable the provider to use its engineering investments more effectively. Gartner is beginning to describe the notion of cloud-provider-managed infrastructure, wherever it may exist, as “ distributed cloud.”
- All the providers target midmarket businesses and enterprises, as well as other companies that use technology at scale. Some of the providers may also target small businesses and startups. Just because a provider targets a segment, however, does not necessarily mean that it is well-suited to that segment’s needs. Furthermore, not all providers have the capacity to serve very-large-scale customers, and some have capacity constraints in particular regions.
- All the providers offer basic cloud IaaS — compute, storage and networking resources as a service. They also offer additional value-added capabilities, notably cloud software infrastructure services — typically middleware and databases as a service — including PaaS capabilities. These services, along with IT operations management (ITOM) capabilities as a service (especially DevOps-related services), are a vital differentiator in the market, especially for Mode 2 agile IT buyers.
- All the providers claim to have high security standards. However, the extent of the security controls provided to customers varies significantly. All the providers evaluated can offer solutions that will meet common regulatory compliance needs, unless otherwise noted. All the providers have undergone SOC 1, SOC 2 and SOC 3 audits, as well as SSAE 16, ISO/IEC 27001, ISO/IEC 27017 and ISO/IEC 27018 audits. This provides a relatively high level of assurance that the providers are adhering to generally accepted practices for the security of their systems, but it does not address the extent of controls offered to customers.
- Security is a shared responsibility. Customers need to correctly configure controls, and they may need to supply additional controls beyond what their providers offer. Furthermore, providers vary in their degree of transparency as to how services are architected, although customers typically have access to third-party assessment reports under a nondisclosure agreement (NDA).
- Monthly compute availability service-level agreements (SLAs) of 99.95% and higher are generally the norm. They are typically higher than availability SLAs for managed hosting. Service credits for outages in a given month are typically capped at 100% of the monthly bill; however, some providers have caps as low as 25%. This availability percentage is typically non-negotiable, because it is based on an engineering estimate of the underlying infrastructure reliability.
- Single-instance compute SLAs have become common for providers in this Magic Quadrant. It might be more accurate to say that there are usually two SLAs — one for the compute service, and one for individual instances. Some providers have a compute availability SLA that requires customers to use compute capabilities in at least two fault domains (sometimes known as “availability zones” or the like).
- Many providers have additional SLAs. These cover network availability and performance, customer service responsiveness and other service aspects.
- Infrastructure resources are not normally automatically replicated into multiple data centers. Customers are responsible for their own business continuity. Some providers offer optional disaster recovery solutions.
- All providers offer per-second metering of virtual machines (VMs). Some can offer shorter metering increments, which can be more cost-effective for short-term batch jobs. Unless otherwise noted, providers charge on a per-VM basis.
- Providers are increasingly offering bare-metal physical servers on a dynamic basis. These are priced by the second. Providers with a bare-metal option are noted as such.
- All the providers partner with carrier-neutral colocation exchanges. This enables customers to obtain connectivity from a variety of carriers that are located in these facilities. In addition, many customers require a small amount of supplemental colocation in low-latency proximity with their cloud provider. For example, they may have a large-scale database, specialized network equipment or legacy equipment, such as a mainframe.
- Some providers offer software marketplaces. In these marketplaces, software vendors specially license and package their software to run on that provider’s cloud IaaS offering. Marketplace software can be automatically installed, and can be billed through the provider, although the software vendor often provides support.
- All providers offer enterprise-class support with 24/7 customer service. This is provided via phone, email and chat, along with an account manager. Some offer a lower level of support, but allow customers to pay extra for enterprise-class support.
- All the providers will sign contracts with customers, can invoice and can consolidate bills from multiple accounts. All providers offer online sign-up and credit card billing, because they recognize that enterprise buyers prefer contracts and invoices. Some will sign “zero dollar” contracts that do not commit a customer to a certain volume.
- Some providers will sign a U.S. Health Insurance Portability and Accountability Act Business Associate Agreement (HIPAA BAA).
- Unless otherwise noted, all providers will sign the following contract addendums:
- An EU Data Protection Directive (95/46/EC) data-processing agreement (DPA), which includes the model clauses
- An EU General Data Protection Regulation (GDPR) DPA
- Managed and professional services are an optional but important accelerator for customer success. Almost all providers rely heavily on managed service providers (MSPs) and system integration (SI) partners for these services. However, most providers offer their own first-party professional services and some also offer first-party managed services offerings.
- All of the evaluated providers offer a portal, documentation, technical support, customer support and contracts in English. Some can provide one or more of these in languages other than English. Most providers can conduct business in local languages.
The service provider descriptions are accurate as of the time of publication. Our technical evaluation of service features took place between January 2020 and March 2020.
Format of the Vendor Descriptions
When describing each provider, we first summarize the nature of the company, then provide information about its industrialized cloud IaaS offerings in the following format:
- Locations: Cloud data center locations by country, languages in which the company does business and languages in which technical support can be conducted.
- Recommended Uses: These are the circumstances under which we recommend the provider. They are not the only circumstances in which it may be a useful provider, but they are the scenarios for which, in Gartner’s opinion, the provider is well-suited.
For a detailed technical description of CIPS offerings, along with a use-case-focused technical evaluation, see “Critical Capabilities for Cloud Infrastructure and Platform Services, Worldwide.”We also provide a detailed list of evaluation criteria in “Solution Criteria for Cloud Integrated IaaS and PaaS.” A detailed assessment of each provider against these criteria can be found in the Solution Scorecards. The results are also available in Gartner’s Cloud Decisions portal (see “Cloud Decisions’ Cloud Compare: Perform Real-Time IaaS Pricing and Performance Analysis”).
Magic Quadrant
Figure 1. Magic Quadrant for Cloud Infrastructure and Platform Services
Vendor Strengths and Cautions
Google is a Leader in this Magic Quadrant.
Locations: Google has multiple regions across Japan and the U.S., as well as a presence in Belgium, Singapore, Finland, Germany, the Netherlands, the U.K., India, Australia, Brazil, Canada and, Switzerland, as well as the Hong Kong and Taiwan markets.
Recommended Uses: Google has evolved by enhancing its strengths and attacking its limitations to providing a strong offering in every use case, other than the edge use case. Google has a future focus on building out hybrid capabilities and partnerships with telco providers.
Strengths
- Google’s open-source contributions, such as Kubernetes and TensorFlow, have been market-moving innovations that have changed the course of enterprise IT. Such innovations have served to enable other cloud service providers, but also brought developer “mind share” to Google Cloud Platform (GCP). Google’s long-term strategy is to bring additional open-source-focused partners into GCP as managed services.
- During the past year, GCP has experienced a noticeable increase in year-over-year market share in terms of IaaS and dbPaaS, albeit from a lower base, relative to other providers in this Magic Quadrant. Google has also made significant gains by closing a number of critical capability gaps between GCP and Microsoft Azure, its nearest competitor in terms of market share and capabilities.
- Gartner clients continue to associate GCP with its big data and data science capabilities, stemming from the use of services such BigQuery and Dataproc. However, the company is pressing into new territory with Anthos, GCP’s container and Kubernetes-based middleware layer, which is designed to support the development and deployment of cloud applications in a hybrid and multicloud model.
Cautions
- Some of Gartner’s clients remain cautious about Google’s commitment to serving the needs of enterprise clients when put in the context of SAP’s preference for Microsoft Azure, and GCP’s slowness in executing on some highly touted partnerships. GCP lacks enterprise-focused aPaaS capabilities and support for Oracle, and it continues to struggle with having an enterprise mindset in the field.
- From a financial perspective, GCP’s revenue is a small fraction of overall Google revenue and GCP’s criticality to the overall business is not as clear as its competitors. Furthermore, GCP’s success may erode the company’s overall healthy gross margins.
- Google’s much-vaunted network capabilities have been the source of a number of GCP outages during the last year, with devastating impact on customers. One outage was multiregional in scope, affecting GCP customers and Google consumer services, such as G Suite and YouTube. This resulted in complete GCP network unavailability for some customers.
New Histogram Features in Cloud Logging Make it Easier to Track Log Volumes, Errors and Anomalies!
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Visualizing trends in your logs is critical when troubleshooting an issue with your application. Using the histogram in Logs Explorer, you can quickly visualize log volumes over time to help spot anomalies, detect when errors started and see a breakdown of log volumes. But static visualizations are not as helpful as having more options for customization during your investigations.
That’s why we’re excited to announce that we recently added three new query controls along with separate colors for log severity to the histogram. These new features make it even easier to refine and analyze your logs by time range. The new histogram controls help find logs before or after the current period, jump to a specific time range represented in a histogram bar and zoom in/out of the current time window in the histogram.
Histogram colors
The histogram now makes it easier to view the breakdown of logs by severity with the introduction of color coding. For example, the severity colors make it easy to spot an increasing number of errors even when the volume of requests is relatively constant. Looking at the histogram below, the red vs blue shading makes it clear that there has been an increase in overall log volume and provides a visual breakdown of errors within that log volume.
Pan left/right to scroll through time
Sometimes in your troubleshooting journey, you may want to look at the logs directly before or after the current set of logs. Perhaps there was an unexpected spike in errors at the beginning of the time range and you need to see the logs in the time period directly preceding the current time range. Pressing the left arrow on the left side of the histogram shifts the time range earlier while the arrow on the right side of the histogram shifts the time range ahead. Either arrow will refine the time range in the query and rerun the query to return the logs in the new time range.
Zooming in or out
Zooming in or out from a given time range may be useful to visualize fine-grained details or a broader trend Clicking the zoom in or out icons in the upper right corner of the histogram refines the time range in the query and then reruns the query, returning the logs in the newly defined time range.
Scrolling to time
If you see a large spike in logs volume in the histogram, it’s useful to quickly review the logs generated during that spike. Clicking on the histogram bar that contains the spike now scrolls you to the logs generated during that time period.
Where to find the histogram
The histogram is a panel in Logs Explorer that can be displayed or hidden using the controls in the Page Layout menu. When you no longer want to display the histogram, click the “X” button in the upper right corner to quickly close it. To open it again, use the same Page Layout menu to enable the histogram display.
Get started with the histogram
These improvements move the histogram from a utility for visualization to an integral part of the troubleshooting journey. We are continuously working to launch new features that make Cloud Logging the best place to troubleshoot your Google Cloud logs. If you are not already a Cloud Logging user, review this getting started documentation or watch a quick video on troubleshooting services on Google Kubernetes Engine (GKE) to learn more. If you have specific questions or feedback, please join the discussion on our Google Cloud Community, Cloud Operations page.
AWS to Google Cloud Translator: Which AWS Database Service Is Equal to Google Cloud Database?
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There are multiple reasons a growing number of database administrators, enterprise architects, application developers and other technology practitioners are moving to Google Cloud’s various database services.
Some are being driven by missing features in offering from other providers such as AWS. In Gartner’s Magic Quadrant for Operational Database Management Systems, the research and advisory firm points out that, “AWS’s surveyed reference customers scored its overall product capabilities one standard deviation (STD) below the mean. Their responses identified missing features such as multiregion writes and autosharding.”
Others are moving to database services on Google Cloud Platform driven by a few benefits. According to Gartner, “Reference customers repeatedly commented on Google’s ease of use and implementation, reliability and integration (with other services and other systems). Reference customers scored Google a full STD above the mean for satisfaction with GCP’s pricing; it received the second-highest satisfaction score of any vendor in this Magic Quadrant.
If you are looking to leverage the power of Google Cloud database offerings—but were unsure of which database services comes closest to the service you are currently using, here’s a handy map to find your way.
Google Invests 1 Billion Euros on Germany to Support Growing Businesses
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In September 2001, the first-ever German Google employee switched on their computer in Hamburg. Since then, we’ve grown to more than 2,500 employees in four offices across Germany. Berlin, Frankfurt, Hamburg and Munich have long been our home, and we continue to invest in the growth of the local economy.
Today, 20 years after the start of “Google Germany”, we are pleased to present one of our most important investment programs to date in this country. With the expansion of our Cloud Region in Frankfurt in a new Google-owned Hanau facility, a new Google Cloud region in Berlin-Brandenburg, and a broad investment plan in renewable energy, our commitment is clear: Google is investing in Germany’s potential and supporting the transition to a digital and sustainable economy. Between now (2021) and 2030, this investment in digital infrastructure and clean energy will total approximately 1 billion euros.
Expanding our Frankfurt cloud region to support growing demand from German businesses and organizations
In Hanau, only 20 kilometers from the DE-CIX Internet hub in Frankfurt, Google is proud to be nearing completion of an additional cloud facility that will be fully operational in 2022. This expansion of our existing Frankfurt Google Cloud region will serve the growing demand for Google Cloud services in Germany.
The 4-story building is 10,000 square meters and was sustainably constructed with energy efficient infrastructure and adherence to our circular economy model for waste. The symbolic handover of the keys from developer NDC-Garbe, together with local government officials, took place on site yesterday.
A new cloud region in Berlin-Brandenburg
In addition to the Hanau expansion of our Google Cloud region in Frankfurt, we are pleased to announce that a new Google Cloud region will be located in Berlin-Brandenburg, further extending our ability to meet growing demand for cloud services in the country. When open, this will be our second Google Cloud region in Germany, providing enterprise customers with faster access to secure infrastructure, smart analytics tools and an open platform. Designed and dedicated to providing enterprise services and products for Google Cloud customers of all sizes and industries in Germany, the Berlin-Brandenburg region will have three zones to protect against service disruptions and join the existing network of 27 Google Cloud regions connected via our high-performance network.
One of the cleanest clouds in the industry becomes even cleaner
Since 2017, Google has matched 100% of our global, annual electricity use with renewable energy. Last year, we set out to run our business on carbon-free energy everywhere and at all times by 2030, enabling us to offer cloud customers one of the cleanest clouds in the industry, while helping Europe achieve its ambitious climate goals.
Today, we’re excited to announce that ENGIE Deutschland has been selected as Google’s carbon-free energy supplier in Germany. Under the terms of the agreement, ENGIE will assemble and develop, on Google’s behalf, a 140 megawatt (MW) carbon-free energy portfolio in Germany that has the ability to flex and grow with us as our needs change. This includes a new 39MW solar Photovoltaic system, and 22 wind parks in five federal states that will see their lives extended so they continue to produce electricity instead of being dismantled. This portfolio will ensure that the energy delivered to Google’s German facilities will be nearly 80% carbon-free by 2022 when measured on an hourly basis. This is a first but important step on Google’s journey to reach our goal of full electricity decarbonization by 2030.
This is the first energy supply of its kind in Europe, with a focus on sourcing carbon-free energy for every hour of Google’s operations. Not only will this new agreement draw the roadmap for the industry and more 24/7 carbon-free energy contracts in Europe, but it provides our cloud customers with two more regions where they can lower their carbon footprint. And importantly, by working with our energy suppliers to transform how clean energy is delivered to customers, Google is supporting the broader decarbonization of the German electricity grid.
What customers and partners are saying
As companies continue to grapple with changing customer demands, technology has played a critical role, and we’ve been fortunate to partner with and serve people, companies, and government institutions in Germany and around the world to help them adapt. The Google Cloud region in Berlin-Brandenburg and the expansion of our Google Cloud region in Hanau will help our customers — such as BMG, Delivery Hero, and Deutsche Bank — adapt to new requirements, new opportunities and new ways of working.
“We are very pleased about the symbolic handover of the keys to the building here in Hanau to Google Cloud,” said Hanau Mayor Claus Kaminsky. “With Google, we have a strong partner at our side who is supporting us in setting up Hanau’s economic future, both digitally and sustainably. The data center facility of Google Cloud embodies this transformation: We bring the cloud to us in Hanau and thus support the digital transformation of companies and public authorities. Not only in our city and Hesse, but throughout Germany and Europe. The new building meets high sustainability standards and the clean energy initiative presented today by Google is in line with our aspirations for sustainable digitalization.”
“Sustainability is a central pillar of Deutsche Bank’s strategy and we have made strong public commitments to be part of the solution,” said Bernd Leukert, Chief Technology, Data and Innovation Officer and Member of the Management Board at Deutsche Bank. “We welcome the new Google Cloud region in Germany, which will enable us to deliver additional resilience and performance for our German client base.”
Ralf Bernhard, Senior Originator Renewables, ENGIE, said: “ENGIE is excited to collaborate with Google based on a first-of-a-kind agreement which will support the company with its sustainability goals and ambitious carbon-free energy target. Thanks to our expertise in energy and risk management, we can seamlessly integrate renewable energy from existing plants and develop new assets to design a tailor made product that meets Google’s needs and plans to go even greener.”
20 years since Google first touched down in Germany, our commitment to helping Germany continue to lead in technical innovation is stronger than ever. We are excited to continue working with our partners in Hesse, Berlin and Brandenburg and across Germany to advance infrastructure and clean energy projects, help accelerate digital transformation, and secure a sustainable future for German and European companies and organizations.
What’s Google Cloud Firestore Database and What are it’s Benefits for Business and Developers?
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Cloud Firestore is a NoSQL document database that simplifies storing, syncing, and querying data for your mobile and web apps at global scale.
Cloud Firestore is a fast, fully managed, serverless, cloud-native NoSQL document database that simplifies storing, syncing, and querying data for your mobile, web, and IoT apps at global scale.
Its client libraries provide live synchronization and offline support, while its security features and integrations with Firebase and Google Cloud Platform (GCP) accelerate building truly serverless apps.
Here’s other stuff it’s good at:
Sync data across devices, on or offline
With Cloud Firestore, your applications can be updated in near real time when data on the back end changes. This is not only great for building collaborative multi-user mobile applications, but also means you can keep your data in sync with individual users who might want to use your app from multiple devices.
With Firebase Realtime Database, we felt we had built the best force-plate testing software on the market. Thanks to Cloud Firestore, in only two weeks, we built a system that’s significantly better and includes features we never thought possible to ship on Day 1.
Chris Wales, CTO, Hawkin Dynamics
Cloud Firestore has full offline support, so you can access and make changes to your data, and those changes will be synced to the cloud when the client comes back online. Built-in offline support leverages local cache to serve and store data, so your app remains responsive regardless of network latency or internet connectivity.
Simple and effortless
Cloud Firestore’s robust client libraries make it easy for you to update and receive new data while worrying less about establishing network connections or unforeseen race conditions. It can scale effortlessly as your app grows. Cloud Firestore allows you to run sophisticated queries against your data. This gives you more flexibility in the way you structure your data and can often mean that you have to do less filtering on the client, which keeps your network calls and data usage more efficient.
Enterprise-grade, scalable NoSQL
Cloud Firestore is a fast and fully managed NoSQL cloud database. It is built to scale and takes advantage of GCP’s powerful infrastructure, with automatic horizontal scaling in and out, in response to your application’s load. Security access controls for data are built in and enable you to handle data validation via a configuration language.
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