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 Unveils New Cloud Region in Delhi NCR to Power India’s Digitization
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In the past year, Google has worked to surface timely and reliable health information, amplify public health campaigns, and help nonprofits get urgent support to Indians in need. Now, we are continuing to focus on helping India’s businesses accelerate their digital transformation, deepening our commitment to India’s digitization and economic recovery. To support customers and the public sector in India and across Asia Pacific, we’re excited to announce that our new Google Cloud region in Delhi National Capital Region (NCR) is now open.
Designed to help both Indian and global companies alike build highly available applications for their customers, the Delhi NCR region is our second Google Cloud region in India and 10th to open in Asia Pacific.
What customers and partners are saying
Navigating this past year has been a challenge for companies as they grapple with changing customers demands and economic uncertainty. Technology has played a critical role, and we’ve been fortunate to partner with and serve people, companies, and government institutions around the world to help them adapt. The Google Cloud region in Delhi NCR will help our customers adapt to new requirements, new opportunities and new ways of working, like we’ve helped so many companies do in the region:
- InMobi scaled a personalized AI platform to support 120+ million active users. “With the arrival of the Google Cloud Delhi NCR, InMobi Group sees the opportunity to continue closing the gap between our users and products,” says Mohit Saxena, Co-founder and Group CTO of Inmobi. “Glance, especially, has been serving AI-powered personalised content to over 120 million active users. We can’t wait to continue giving them truly meaningful experiences that are speedy, scale well, and are relevant to them, by expanding the use of our current tools working on Google Cloud with the opening of a new region.”
- Groww now supports a sizable user base. “Google Cloud provides great technology that enables us to build and scale infrastructure to millions of users, and the new Google Cloud region in Delhi NCR will continue to help more businesses and startups in India access powerful cloud-based infrastructure, products and services,” says Neeraj Singh, Co-founder and Chief Technology Officer, Groww.
- HDFC Bank is positioned for the future. “At HDFC Bank, we are harnessing technology platforms to both run and build the bank. As we progress to be future ready, the objective is to invest in future technologies that give us scale, efficiency and resiliency. Towards this the Google Cloud region in Delhi NCR will enable us to enhance our resiliency and help us in building an active-active design framework for our new generation applications on cloud,” says Ramesh Lakshminarayanan, CIO, HDFC Bank.
- Dr. Reddy’s Lab built a modern data platform with Google Cloud. “At Dr Reddy’s, we pride ourselves in helping patients regain good health, acting quickly to provide innovative solutions to address patients’ unmet needs and in accelerating access to medicines to people worldwide. Our Google Cloud-powered data platform is helping us realize these objectives and we welcome Google’s investment in the new Delhi NCR region as helping us and other businesses in India make further contributions to our social and economic future,” says Mukesh Rathi, Senior Vice President & CIO, Dr. Reddy’s Laboratories.
- “To survive the disruption caused by the pandemic and to succeed in the long term, organizations need to become digital natives, so they can be more agile, explore new business models and build new capabilities that boost resilience. A cloud-first strategy plays a key role in enabling businesses to do this,” said Piyush N. Singh, Lead – India market unit & lead – Growth and Strategic Client Relationships, Asia Pacific and Latin America, Accenture. “Harnessing the potential of cloud requires the right data infrastructure and this expansion by Google Cloud will undoubtedly help Indian enterprises in their digital transformation journeys.”
A global network of regions
Delhi NCR joins 25 existing Google Cloud regions connected via our high-performance network, helping customers better serve their users and customers throughout the globe. As the second region in India, customers benefit from improved business continuity planning with distributed, secure infrastructure needed to meet IT and business requirements for disaster recovery, while maintaining data sovereignty.
With this new region, Google Cloud customers operating in India also benefit from low latency and high performance of their cloud-based workloads and data. Designed for high availability, the region opens with three availability zones to protect against service disruptions, and offers a portfolio of key products, including Compute Engine, App Engine, Google Kubernetes Engine, Cloud Bigtable, Cloud Spanner, and BigQuery.
Supporting India’s recovery with training and education
Google and Google Cloud will also continue to support our customers with people and education programs. We’re investing in local talent and the local developer community to help enterprises digitally transform and support economic recovery.
Through the India Digitization Fund, we expanded our efforts to support India’s recovery from COVID-19—in particular, through programs to support education and small businesses. In addition to expanding internet access, and investments to help start-ups accelerate India’s digital transformation, we’ve grown our Grow with Google efforts. Businesses can access digital tools to maintain business continuity, find resources like quick help videos, and learn digital skills—in both English and in Hindi.
Helping customers build their transformation clouds
Google Cloud is here to support businesses, helping them get smarter with data, deploy faster, connect more easily with people and customers throughout the globe, and protect everything that matters to their businesses. The cloud region in Delhi NCR offers new technology and tools that can be a catalyst for this change. To learn more, visit the Google Cloud locations page, and be sure to watch the region launch event here.
Google and NetApp Partnership Expansion to Ease Customers’ Cloud Migration
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As organizations continue to evolve to meet the needs of their stakeholders, they are increasingly looking to adopt the cloud and digitally transform their business. Since our partnership with NetApp began in 2018, we’ve been focused on delivering the infrastructure, tools, and services to help customers on their cloud migration journey and benefit from their data to better serve their customers.
“Customers are looking to adopt flexible and scalable solutions that meet the needs of their business,” said Ronen Schwartz, SVP & GM, Cloud Volumes, NetApp. “Our long-standing partnership with Google Cloud continues to deliver innovative solutions for customers as they look to migrate and run their business critical applications in the cloud while unlocking the power of their data with industry-leading cloud services.”
Innovative, industry-first solutions have become the standard for our partnership. From the general availability of NetApp Cloud Volumes Service (CVS) for Google Cloud in 2019, to our collaboration on new architectures in 2020 with the release of the software-defined CVS powered by Google Kubernetes Engine (GKE), we continue to deliver first-of-its-kind enterprise file storage services together. In 2021, the pace of innovation has only increased—together, we delivered volume replication powered by SnapMirror, which efficiently copies volume data from one Google Cloud region to another for data consistency, development, testing, or disaster recovery.
We’ve also made our services available globally—you can now run Cloud Volumes ONTAP in all 28 Google Cloud regions, and CVS is now available in 19 regions, allowing you to access our services wherever you are around the globe. All of this is backed up by a 99.99% SLA for CVS, enabling high availability for your enterprise workloads.
Hundreds of customers including MailerLite, a leader in marketing automation, have benefitted from our joint services. MailerLite was looking to move millions of files to the cloud without disruption as they were facing availability, management, and maintenance challenges as their business scaled. By leveraging NetApp CVS on Google Cloud, MailerLite was able to migrate over 100 million files to Google Cloud in about an hour, removing their ongoing infrastructure overhead, saving developer hours, and eliminating the scalability limitations they previously experienced.
Expanding our partnership
Last week at Google Cloud Next ‘21, we announced we are expanding our strategic partnership in two ways to make it even easier for customers to migrate and run business critical applications on Google Cloud. First, NetApp will provide storage infrastructure for the newly announced Google Distributed Cloud Hosted, where data resides in customer-owned data centers and colocation facilities. This enables a safe and secure way to modernize an on-premises deployment while still meeting data security and privacy requirements.
Additionally, for customers looking to migrate their VMware workloads to Google Cloud, we announced preview access for NetApp Cloud Volumes as datastores for Google Cloud VMware Engine. By providing customers with the choice to scale compute and storage independently, customers can now reduce costs and complexity when migrating and running storage-bound workloads. This also allows customers to address regional disaster recovery use cases, making it easier and more cost-effective to move on-premises workloads into Google Cloud. To get started, you can sign up for preview access using the Registration for Preview Access form.
Looking forward
We’re excited for what’s to come with our partnership and committed to delivering value to customers across industries. Google Cloud is a Gold sponsor at this week’s NetApp Insight, and we invite you to join our spotlight session featuring Google Cloud and NetApp leaders. Additionally, we are leading multiple breakout sessions where you will hear from our product team on how you can accelerate cloud adoption with Google Cloud and NetApp. You can also learn more and get started today by visiting our NetApp on Google Cloud website.
Autonom8: Achieving growth and profits for businesses with Google Cloud
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With Google Cloud, Autonom8 can run a platform that accelerates and streamlines customer journeys in a scalable, reliable, cost-effective infrastructure, while using advanced optical character recognition to enable intelligent document processing.
About Autonom8
Headquartered in the United States and India, Autonom8 has built a low-code SaaS platform that allows businesses to digitize customer-facing workflows. The business aims to help clients reduce costs and improve interactions with their customers through automation and enablement of customer journeys.
Google Cloud results:
- Increased margins by up to 30% by switching from a home-grown OCR system to Cloud Vision AI
- Enables one DevOps team member to manage up to 30 customers
- Provides real-time information about customer journeys to enable businesses to respond quickly and accurately
- Ensures use of its platform with containerization in customers’ private data centers
- Reduced operating costs by up to 20% with localized scalability and architecture through GKE
Just as cars are evolving to become autonomous, smart and self-driving, enterprises can gain self-awareness, an ability to learn and an ability to adapt. This is the value proposition put forward by Autonom8, an India- and United States-based enterprise workflow management software business. “We provide a low-code, high-intelligence customer journey automation SaaS platform,” explains Ranjit Padmanabhan, Co-founder and Chief Technology Officer (CTO), Autonom8.
The Autonom8 platform includes components, such as A8Studio, a drag and drop location from which clients can create customer journeys, a chat platform that enables clients to create chatbots, and an analytics module. “With our platform and services, businesses can reduce costs and improve interactions with their customers by applying automation to accelerate and provide better customer journeys,” adds Padmanabhan.
Demand for Autonom8 is being driven by the changing customer demands of enterprises, including the expectation to interact with them over multiple channels, and the rising cost of building software with experienced developers. These trends place enterprises under growing pressure to increase the productivity of the people they do have, particularly those who are less technically inclined. In addition, changing consumer habits, regulations and the emergence of new technologies mean customer journeys cannot remain static and need to evolve.
Developing a microservices-based SaaS platform
From the start, Autonom8 planned to deliver a SaaS platform and initially deployed on a multinational cloud service, chosen due to the team’s familiarity with its products and the availability of credits. However, the company’s decision to opt for a microservices architecture that enables individual services to scale independently while running in a containerized environment, demanded high-quality container orchestration. To optimize cost, scalability and performance, Autonom8 began evaluating Google Kubernetes Engine (GKE).
The business then completed a side-by-side comparison between Google Cloud and its incumbent provider of compute, storage and other services. Google Cloud fared favorably, with Vision AI in particular providing powerful machine learning and optical character recognition (OCR) functionality, supporting a key use case for Autonom8.
In addition, many of Autonom8’s clients at the time are financial institutions in India, and legally required to retain data within the country’s borders. Google Cloud’s global network and local presence means the business could fulfill this requirement easily.
“We decided to evaluate Google Cloud, particularly GKE, from two perspectives. One, from a security perspective, as we sell to banks that audit our platform, and two, as a failover between regions because downtime costs money. We found it a compelling solution.”
— Ranjit Padmanabhan, Co-founder and Chief Technology Officer (CTO), Autonom8
A seamless move to Google Cloud
Autonom8 began deploying on Google Cloud in 2018, with its architecture comprising storage, compute, serverless, container management and orchestration, and Vision AI. “We looked at our scripting with the previous provider, and using the Google Cloud documentation available online, educated ourselves over a few weeks before moving pieces of our architecture step by step to Google Cloud,” says Padmanabhan. “We did not run into any major issues. It was pretty simple, with our experienced engineers training others in the product.”
According to the CTO, the business had two options when moving to Google Cloud. Autonom8 could either install raw virtual machines and effectively create its own virtualized data center, or rely on managed services for functions such as memory store, registration and authentication to save time and resources over the long term. Autonom8 opted for the latter and has transitioned fully to Google Cloud, with the number of cloud products and services in its architecture rising from five to about 15. While each product and service performs a key role in the delivery of Autonom8’s products and services, Padmanabhan nominates GKE, Vision AI and Cloud SQL as providing the greatest value to the business.
Scalability, real-time monitoring and intelligent document processing at low cost
With GKE, the business can now scale the nodes or containers specific to each microservice in the event traffic to a particular client surges, due to a rebate or promotion. “Through the combination of the architecture and localized scalability we achieve with GKE, we are reducing our operating costs by up to 20%,” says Padmanabhan.
Running an open source TimescaleDB on Postgres in Cloud SQL enables Autonom8 to give its clients the ability to monitor customer journey information in real time. An example of a journey is applying for a bank loan. The customer must take steps including providing income, tax and other financial details that the bank then appraises to help make a decision on the application. “The moment someone applies for a loan, for example, a bank knows about it and can monitor for fraud, bottlenecks, or other abnormalities, and immediately route to a remediation workflow,” explains Padmanabhan. “Cloud SQL enables us to maintain transactional logging and provide real-time data to our dashboards.”
After evaluating alternative services, including developing a home-grown OCR engine, the business turned to Cloud Vision AI to manage the intelligent document processing that comprises much of its transactional volume. “Vision AI is significantly better than the alternatives and the cost of maintaining our version did not make sense, because Google Cloud continues to make improvements over time that enable us to deliver more and more accurate results to our customers,” says Padmanabhan. “Switching from our home-grown service to Vision AI has enabled us to increase our profit margins by up to 30%.”
“Through the combination of the architecture and localized scalability we achieve with Google Kubernetes Engine, we are reducing our operating costs by up to 20%.”
—Ranjit Padmanabhan, Co-founder and Chief Technology Officer (CTO), Autonom8
Supporting client demands and improving developer efficiency
Google Cloud also enables Autonom8 to meet the demands of businesses that want to run its platform within their own private data centers. “We can undertake the build within Google Cloud and ship our containers to compatible hosts within those clients’ data centers,” explains Padmanabhan. “With our previous provider, we could create containers, but these would not run properly within those data centers.”
Furthermore, Google Cloud documentation and online resources help Autonom8 reduce the training needed for new developers to become productive, with the Google Cloud learning curve taking up just 10% of the overall onboarding cycle.
The organization spends the equivalent of just 3% of its overall annual revenue on DevOps, measured as DevOps Utility Ratio, while the cloud cost of revenue is about USD 1 for every USD 6 in annual recurring revenue, measured as Cloud Utility Ratio. “These two metrics are about what we can do with the people we have,” explains Padmanabhan. “Our current ratio implies that one DevOps person can handle approximately 30 customers. This is made possible by the tools we have, and the comprehensive support from Google Cloud in terms of security patches, intelligent alerts, resource overloading, and more.”
Google Cloud also provides the flexibility for Autonom8 to accommodate the varying service levels required by individual customers based on factors, such as the impact of downtime, as the business can failover seamlessly between regions to mitigate the impact of any issues that may occur.
“Our current ratio implies that one DevOps person can handle approximately 30 customers. This is made possible by the tools we have, and the comprehensive support from Google Cloud in terms of security patches, intelligent alerts, resource overloading, and more.”
—Ranjit Padmanabhan, Co-founder and Chief Technology Officer (CTO), Autonom8
Integrating Google Workspace with Autonom8 to deliver new capabilities
Autonom8 relies on Google Workspace for communication, collaboration and other workplace productivity requirements, growing its footprint from Gmail when the employee population was four or five, to a range of products including Sheets and Drive as the business grew. “It became natural to use the capabilities in Google Workspace as we matured,” says Padmanabhan. “One of the most interesting capabilities was our ability to integrate Google Workspace into our platform. For example, when someone is running a workflow, they can add data from a Sheet. We’ve added Google Workspace authentication capabilities into our products as well.”
“Everyone is using shared links to Drive and I really like the granular permissions structure,” he adds. “I can open up folders to clients while keeping an internal space within the business to ensure security and privacy.”
With Google Cloud, Autonom8 is now poised to continue growing its business and adding new features and capabilities for clients. “We are extremely excited at the opportunity to step up our offering to clients with Google Cloud,” concludes Padmanabhan.
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How McKesson Gains Insights by Running SAP on Google Cloud
McKesson, a 185-yeal old, $200 billion, Fortune 6 pharmaceuticals and health information technology company, with over 80,000 employees migrated their SAP solution to Google Cloud for advanced healthcare analytics.
With changing consumer expectations, the company needed to change its architecture to be able to better serve its customers. And the old on-premise infrastructure was hindering the company from being able to meet those expectations.
Watch this video as Andrew Zitney, SVP and CTO at McKesson, explains how SAP on GCP helps the 180-year old company modernize and meet the changing expectations.
YoungCapital CIO: Why I Moved to Google Cloud and G Suite to Grow Our Business
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When your business is rapidly adding new employees, expanding to new countries, and always focused on staying ahead of the competition, you have to take a hard look at the tools that are slowing you down—and swap them out for better ones that can keep pace with the company. We’re expanding YoungCapital in Germany, which means more offices, more people, and more technology to make the business run smoothly.
As we scale, Google Cloud tools like Chromebooks and G Suite help us grow our business efficiently. They free us up from sluggish, time-intensive technology that’s hard to maintain and repair, and give us the freedom to work together in faster, smarter ways.
Free from hours of device setup. Some months, there are as many as 40 new employees starting at YoungCapital—and as we continue to expand that number will continue to rise, especially now that we’ve opened three new offices in Germany. With our old Windows desktops, setting up new computers could take up to an hour per employee (which can add up to about 40 hours a month for IT). Today, using Chrome Enterprise tools, it takes about five minutes to get an Acer Spin or Pixelbook ready to hand off to a new hire—saving us more than three months per year of device setup time.
Free from VPNs. Our previous Windows machines required a complicated virtual private network (VPN) for accessing corporate files outside of the office. Using a VPN was complicated for our employees because the software wasn’t intuitive; if an employee had trouble signing into the VPN while at home or traveling, they could not log in and work as quickly as they needed to. With Chromebooks, all you need is an online connection to sign into G Suite to access files and work from anywhere.
From our perspective, Chromebooks are resistant to threats like ransomware and phishing attacks, giving us confidence that our data can stay secure. With Chrome Enterprise Upgrade, our IT admins can strengthen security even further: for example, by enabling advanced security features that help block vulnerabilities, locking down lost or stolen devices right away, and setting device security policies in the cloud so devices everywhere are safer.
Free from infrastructure. We used to have to invest in servers, and then add more time and money to keep them running. Now we don’t have to run the business on infrastructure or hire people to maintain it—we can just use Google’s cloud. NextNovate is helping us make the most of Google Cloud Platform, like integrating some of our proprietary applications with G Suite and building our own add-ons. For example, we created a button for Gmail that connects to our job candidate database; when candidates email us, we can click on the button and see their profiles and work experience.
Free from multiple passwords and logins. Chrome Browser and G Suite with single sign-provider SAML are the portal to all the productivity apps our employees need. Once people log in to G Suite, they don’t have to remember a bunch of other user names and passwords. The IT team loves it too, because we don’t have to spend hours zeroing out passwords and creating new ones.
Free to manage cross-country devices easily in the cloud. Our four-person IT support team, which keeps our systems humming, hasn’t grown, even though we’ve doubled the number of employees. When we were on Windows devices, we fielded roughly 1,800 IT support requests every month. Now we get about 1,300 requests a month, from a much bigger employee base. This translates to nearly 30% fewer requests for our lean support team, which reduces their workload significantly even though we have roughly 20% more employees—all made possible with Chrome Enterprise.
Being free of slow, high-maintenance technology doesn’t just make the IT department happy—people are actually changing how they work. They no longer send files to each other by email or struggle to keep track of versions; they store everything in Google Drive and work together in Google Docs on a single document at the same time. And instead of traveling to other offices, connecting with each other in video conferences on Hangouts Meet has become a completely natural way to do business.
With Chromebooks and G Suite, we’re ready for anything: more new markets, more employees, and more-flexible ways to work together and shake up the staffing industry.
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