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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.

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For most established businesses today, the disruptive start-up has emerged as the biggest and most intimidating competition. A start-up’s digital prowess and astounding ability to innovate and scale massively in weeks, for what takes conventional businesses quarters, is daunting. How does one compete with that?
To play in today’s digitally-connected world, companies need to be equipped to deliver apps and digital experiences at lightning speed. How do you leverage insights from your environment of customers, partners, suppliers, and, in many cases, stores, warehouses, and inventory and use all that data to deliver relevant products and services? How do you unlock the data from your slow-moving systems of record to build those apps and experiences at the speed and agility of the App Store?
Gartner calls it bi-modal IT: an approach that enables an organization to protect the back-end systems and also drive rapid innovation. Think of it as an enterprise gearbox that enables you to scale your interactions a million times . In this eBook we explore how businesses can implement an API tier to keep backend transaction systems humming as front-end digital interactions scale to billions of requests and interactions , way beyond what your systems were designed to do.
Report on API-led Digital Transformations in 2020 and the Future

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In 2020, many businesses across industries turned their focus and investments towards digital strategies. APIs being an integral part of every organization’s digital disruption, will grow in relevance throughout 2021. Read the report to gain more insights on driving API-led digital transformations and in-depth analysis of Google Cloud’s Apigee API Management Platform usage data, case studies and third-party surveys conducted with tech leaders.
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Unburden Your Operations and Development Teams with Anthos
VMs are used to run the majority of services in enterprises. Whether due to specific technical requirements, developer preferences, or simply time and budget constraints, many applications are not moving to containers and Kubernetes yet.
Think services first
Microservices architectures present numerous benefits but also introduce challenges like added complexity and fragmentation for different workloads. The Anthos platform unburdens your operations and development teams by simplifying service delivery across the board, from traffic management and mesh telemetry to securing communications between services. Anthos Service Mesh, Google’s fully managed service mesh, lets you easily manage these complex environments and enjoy the benefits they promise.
Learn how to incorporate these existing VM workloads into Anthos Service Mesh. Also, see how to use Compute Engine to simplify the installation and management of the Envoy proxy and how to add VMs to the mesh. Lastly, explore how you can modernize your VMs in place or develop a strategy to migrate your VMs to containers. Regardless of the path chosen, we show how the VMs can participate in the mesh and get all the same benefits of security, policy, and telemetry that Anthos Service Mesh provides to Kubernetes workloads.
Scaling with Breaking News: BBC’s Serverless Infrastructure on Google Cloud

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Editors note: Today’s post is from Neil Craig at the British Broadcasting Corporation (BBC), the national broadcaster of the United Kingdom. Neil is part of the BBC’s Digital Distribution team which is responsible for building the services such as the public-facing www bbc.co.uk and .com websites and ensuring they are able to scale and operate reliably.
The BBC’s public-facing websites inform, educate, and entertain over 498 million adults per week across the world. Because breaking news is so unpredictable, we need a core content delivery platform that can easily scale in response to surges in traffic, which can be quite unpredictable.
To this end, we recently rebuilt our log-processing infrastructure on a Google Cloud serverless platform. We’ve found that the new system, based on Cloud Storage, Eventarc, Cloud Run and BigQuery, enables us to provide a reliable and stable service without us having to worry about scaling up during busy times. We’re also able to save license fee payers money by operating the service more cost effectively than our previous architecture. Not having to manually manage the scale of major components of the stack has freed up our time, allowing us to spend it on using, rather than creating the data.
A log in time
To operate the site and ensure our services run smoothly we continually monitor Traffic Manager and CDN access logs. Our websites generate more than 3B log lines per day, and handle large data bursts during major news events; on a busy day our system supports over 26B log lines in a single day.
As initially designed, we stored log data in a Cloud Storage bucket. But every time we needed to access that data, we had to download terabytes of logs down to a virtual machine (VM) with a large amount of attached storage, and use the ‘grep’ tool to search and analyze them. From beginning to end, this took us several hours. On heavy news days, the time lag made it difficult for the engineering team to do their jobs.
We needed a more efficient way to make this log data available, so we designed and deployed a new system that deals with logs and reacts to spikes more efficiently as they arrive, improving the timeliness of critical information significantly.
In this new system, we still leverage Cloud Storage buckets, but on arrival, each log generates an event using EventArc. That event triggers Cloud Run to validate, transform and enrich various pieces of information about the log file such as filename, prefix, and type, then processes it and outputs the processed data as a stream into BigQuery. This event-driven design allows us to process files quickly and frequently — processing a single log file typically takes less than a second. Most of the files that we feed into the system are small, fewer than 100 Megabytes, but for larger files, we automatically split those into multiple files and Cloud Run automatically creates additional parallel instances very quickly, helping the system scale almost instantly.
The nature of running a global website which provides news coverage means we see frequent, unpredictable large spikes of traffic. We learn from these and optimize our systems where necessary so we’re confident in the system’s ability to handle significant traffic. For example, around the time of the announcement of the Queen’s passing in September, we saw some huge traffic spikes. During the largest, within one minute, we went from running 150 – 200 container instances to over 1000…. and the infrastructure just worked. Because we engineered the log processing system to rely on the elasticity of a serverless architecture, we knew from the get-go that it would be able to handle this type of scaling.
Around the time of the announcement of the Queen’s passing in September, we saw some huge traffic spikes. During the largest, within one minute, we went from running 150 – 200 container instances to over 1000…. and the infrastructure just worked

Our initial concern about choosing serverless was cost. It turns out that using Cloud Run is significantly more cost-effective than running the number of VMs we would need for a system that could survive reasonable traffic spikes with a similar level of confidence.
Switching to Cloud Run also allows us to use our time more efficiently, as we no longer need to spend time managing and monitoring VM scaling or resource usage. We picked Cloud Run intentionally because we wanted a system that could scale well without manual intervention. As the digital distribution team, our job is not to do ops work on the underlying components of this system — we leave that to the specialist ops teams at Google.
Another conscious choice we made whilst rebuilding the system was to use the built-in service-to-service authentication in Google Cloud. Rather than implementing and maintaining the authentication mechanism ourselves, we add some simple configuration which instructs the client side to create and send a OIDC token for a service account we define and the server side to authenticate and authorize the client. Another example is pushing events into Cloud Run, where we can configure Cloud Run authorization to only accept events from specific EventArc triggers, so it is fully private.

Going forward, the new system has allowed us to make better use of our data safely. For example, BigQuery’s per-column permissions allow us to open up access to our logs to other engineering teams around the organization, without having to worry about sharing PII that’s restricted to approved users.
The goal of our team is to empower all teams within the BBC to get the content they want on the web when they want it, make it reliable, secure, and make sure it can scale. Google Cloud serverless products helped us to achieve these goals with relatively little effort and require significantly less management than previous generations of technology.
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