Memorystore for Redis Read Replicas to Scale App Read Requests by 6X - Build What's Next
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Memorystore for Redis Read Replicas to Scale App Read Requests by 6X

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Google Cloud announces public preview of Memorystore for Redis Read Replicas which helps scale application read requests by 6x in just a click of a button. Read the blog to understand how this impacts organizations' performance at no cost!

Modern applications need to process large-scale data at millisecond latency to provide experiences like instant gaming leaderboards, fast analysis of streaming data from millions of IoT sensors, or real-time threat detection of malicious websites. In-memory datastores are a critical component to deliver the scale, performance, and availability required by these modern applications. 

Memorystore makes it easy for developers building applications on Google Cloud to leverage the speed and powerful capabilities of the most loved in-memory store: Redis. Memorystore for Redis standard tier instances are a popular choice for applications requiring a highly available Redis instance. Standard tier provides a failover replica across zones for redundancy and provides fast failover with a 99.9% SLA. However, in some cases, your applications will require more read throughput from a standard tier instance. One of the common patterns customers use to scale read queries in Redis is leveraging read replicas.

Introducing Memorystore for Redis Read Replicas

Today we are excited to announce the public preview of Memorystore for Redis Read Replicas, which allows you to seamlessly scale your application’s read requests by 6X with the click of a button.

With read replicas, you can easily add up to five replicas and leverage the read endpoint to automatically load balance read queries across all the available replicas, increasing read performance linearly with each replica added. Additionally, Memorystore’s support for Redis 6 introduced multi-thread I/O, increasing performance significantly for M3 and higher configurations. Combined, you can achieve read requests of more than a million requests per second. 

You will benefit from this new functionality in several ways. You will be able to scale on demand with up to five read replicas and use read endpoint with any redis client to easily load balance read queries across multiple replicas. This new functionality will also improve availability with automatic distribution of replicas across multiple zones. With read replicas, you will also be able to minimize application downtime with fast failover to the replica with the least replication lag. In the future, Memorystore will also easily enable read replicas on existing standard tier instances to increase read throughput. 

You can learn more about how to configure and use read replicas in the Read Replicas Overview

Improving performance with Read Replicas and Redis 6

With the launch of read replicas, you can easily increase the read throughput of a Memorystore instance. You can further enhance the read performance by leveraging Redis version 6 along with read replicas.

To understand why combining read replicas and Redis 6 can significantly improve your application’s read performance, let’s look at the various Memorystore configurations that you can use with your applications today. Memorystore Basic and Standard offerings  provide different capacity tiers. The capacity tier determines the single node performance of a basic and standard tier instance. 

The table below outlines the configuration of the various capacity tiers:

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Up until version 5, Redis processed commands using a single thread. The processing involved reading the request, parsing the request, processing the request, and writing the response back to the socket. This approach means that all of the processing, which includes writing the response, was sequentially processed by a single vCPU regardless of the number of vCPUs available in the instance.

Redis 6 introduced I\O threading which allows writing the response using parallel threads. This functionality enables Redis 6 to more effectively leverage available vCPUs, thereby increasing the overall throughput compared to lower versions. Memorystore for Redis version 6 leverages I\O threading and automatically configures the optimal number of I\O threads to achieve the best possible performance for the various capacity tiers. We have also improved the overall network throughput for all redis versions by leveraging improvements in the Google Cloud infrastructure. Together these improvements deliver significant performance improvements and come at no additional cost to you. 

So what can you expect from using Redis 6? As outlined in the table, Redis version 5 and lower uses a single thread to process the write requests for all tiers while Redis 6 uses a larger number of I\O threads at higher capacity tiers which provides substantially incremental throughput for higher capacity tiers.

For example, using a Redis 6 standard tier instance with a capacity of 101 GB (M5), we have observed up to a 200% improvement in read/write performance compared to version 5, though the actual value you’ll see is dependent on your workload. You can get the benefits of Redis 6 by upgrading an existing instance or by deploying a new instance.

By enabling read replicas on an instance using Redis 6, you can further improve the read performance. Read throughput scales linearly with the number of replicas so you can increase your read queries on an instance by up to 500% using five read replicas. By combining Redis 6 and read replicas, you can see a 10X increase in read performance compared to a version 5 standard tier instance with no read replicas.

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We are excited about the launch of read replicas but this is just one step in our journey to deliver the scale you need at the best price-performance. You can learn more about read replicas pricing on our Memorystore pricing page and get started using the Read Replicas Overview.

How-to

6 Tips for Stress-Free Google Cloud Billing

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In this blog, you will discover 6 simple ways to avoid stress when managing your Google Cloud billing and gain control over your expenses with these easy-to-follow tips. Read now!

If you took one look at the title of this blog and thought, “just show me how, because I already know a million reasons why I’m stressed about billing things” then check out the interactive tutorial right here.

For everyone else, read on, because we’ll walk through some common sense tips, and a few step-by-step tutorials for all things billing related. If you’ve ever wished you could sit down with someone from Google Cloud, and walk through your bill, the console, and your options — you’re in the right place! Consider this Cloud Billing 101 – an intro level course that’ll get you started on the right foot.

6 simple tips to manage your Google Cloud billing accounts:

  1. Get to know your billing statement and console: Knowledge is power, after all. Take a tour of the billing console so you can better understand your options, along with what’s included in your monthly bill and the different components.
  2. Set up authorized users, alerts and budgets: Make sure anyone who needs to have access to payment settings is authorized. Allocate budgets for projects, and get notifications when your usage or spending exceeds a certain amount so you can take action as needed.
  3. Use cost-saving tools: We’ve got  a range of tools and services to help you save money, like Committed Use Discounts, and even Recommenders for actionable, AI-powered intelligent recommendations around your cost trends and product usage.
  4. Optimize your resources: Use the Google Cloud Resource Manager to see how your resources are being used and identify areas for optimization, temporarily suspend, or even shut down unused projects
  5. Review your billing history with reporting and data visualization: Regularly check your billing history with reports to help track your spending, identify any trends or patterns, and even anticipate future costs. You can even export your data to BigQuery for detailed analysis, or use a tool like Google Data Studio to visualize your data.
  6. Use the pricing calculator: Estimate your monthly costs and make informed decisions with the Google Cloud pricing calculator. It can help you get a ballpark figure for your usage, and determine if your use case fits within cost-free parameters.

I hope these common sense pointers and tutorials empower you to effectively manage your Google Cloud billing and stay on top of your spending. Get started right now by managing your billing methods and payment settings in this 5-minute tutorial, and then take a tour of the billing console to get familiar with your setup.

Blog

Start-up Paves Way for More Inclusive Clinical Research: Honoring Black Founders of Acclinate with Google Cloud

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February is Black history month, honoring the contributions by Black Americans. Acclinate, a research start-up uses Google Cloud to grow business and drive inclusion in clinical research. Read their journey of scaling platform on Google Cloud.

Editor’s note: February is Black History Month—a time for us to come together to celebrate the diverse set of experiences, perspectives and identities that make up the Black experience. Over the next few weeks, we will highlight Black-led startups and how they use Google Cloud to grow their businesses. Today’s feature highlights Acclinate and its founders, Del and Tiffany. 

As patients, as caregivers, and as parents taking our own children to the doctor, we want recommended medications to be safe and effective. It’s a right everyone deserves.

It’s known that certain medications don’t work in the same way in all populations. For example, Albuterol, a medication often prescribed for asthma, is less effective in 67% of all Puerto Ricans and 47% of Black Americans. These problems—which can have deadly consequences—result from historically limited diversity in pharmaceutical clinical trials. 

We founded our startup Acclinate to integrate culture and technology to achieve more inclusive clinical research. Help pharmaceutical companies and healthcare organizations access and engage communities of color so research is more inclusive.

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Bridging the health equity gap by building trust

It’s important that health research organizations access and engage communities of color so their efforts reflect all the people they serve. Take a disease like diabetes, which affects a significantly higher proportion of Black Americans. When you look at even recent clinical trials for diabetic drugs, the representation of Black Americans among participants is only in the low single digits, despite comprising 13 percent of the U.S. population and more than 40 percent of diabetes patients in this country. Industry leaders have been aware of the lack of diversity issue, but some have chosen to ignore it or brush it aside. The biggest problem, in our opinion, is that there have been no penalties for not achieving higher diversity figures in clinical trials, and only minor financial repercussions to pharma/biotech companies when their treatments either do not work across all groups once approved, or there is a lack of uptake by all groups due to the lack of testing in those groups. The lack of clinical trial diversity has adversely impacted the reputation of the industry and the ability to recruit diverse populations in the future. 

Acclinate integrates culture and technology to promote diverse patient representation in medical research. Our approach is not transactional. We build trust through our  #NOWINCLUDED community, which is an ongoing, ever-expanding digital platform that educates and engages with communities of color on health issues.

#NOWINCLUDED includes a website app, and social media presence where members can learn information about diseases, particularly those with greater negative impacts on people of color, such as cancer, diabetes, and cardiovascular diseases. Members can share stories and ask questions. By providing access to trusted resources about these health issues and the latest clinical research, we empower Black people to take control of their health and consider  participating in research that is shaping the future of healthcare.  

For healthcare-related organizations, we offer the opportunity to better understand the attitudes, aspirations, and unmet needs of underrepresented minority communities. Data from #NOWINCLUDED feeds our HIPAA-compliant SaaS platform, e-DICT™ (Enhanced Diversity in Clinical Trials), which uses predictive analytics and machine learning to identify individuals matching the requirements and most likely to be receptive to participation in a particular clinical trial.

Acclinate scales its platform with Google Cloud

We rely on Google Cloud services, including Vertex AI, to know whom to ask, when to ask, and how to ask for clinical trial participation. With Vertex AI, we enjoy a unified platform for developing our artificial intelligence models, including tools for preparing and storing our datasets. We can easily train and compare models using AutoML, which requires minimal ML expertise or effort with its intuitive graphical interface. This allows us to leverage more than ten ordinal and categorical data points to determine in real time a community member’s likelihood to enroll, which we call our Participation Probability Index (PPI). Our models evolve in an iterative process the more we interact with, and learn about, our community members.

We follow the pay-per-use Google Cloud Platform architecture model using serverless technology, which helps reduce infrastructure management costs and lets us focus on product development and engaging with communities across the U.S.

CloudSQL, a fully managed relational database service, integrates easily with BigQuery so we can glean insights for our clients in real time, all with Google Cloud’s robust security, governance, and reliability controls. Virtual Private Cloud (VPC) gives us scalable and flexible networking for our cloud-based resources and services. We also use Identity and Access Management (IAM) to simplify oversight of Google Cloud resource permissions for different user groups and roles, with appropriate security protections. 

API Gateway manages our APIs using Cloud Functions, which both use consumption-based pricing, plus give our developers consistent and highly secure access to our services through a well-defined REST API. We use Memorystore for Redis to reduce platform latency. This is done with a fully managed service powered by the Redis in-memory data store, which builds application caches for fast data access. All of this comes together to provide an outstanding experience for our platform’s users and contributors.

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Expanding influence with the Google for Startups Accelerator for Black Founders

Three months of one-on-one Google support and mentorship as part of the most recent Google for Startups Accelerator : Black Founders cohort not only helped us build our product, but also helped us earn external credibility. People use Google every day, so whether we’re trying to engage in conversations with industry experts or with somebody in a rural community, it is helpful to have the buy-in of a globally-recognized brand as we take on a historically difficult, systemic issue with challenges around trust. Getting access to the products, best practices, and people we need to build and grow through the Accelerator program has been priceless. For example, working with the Google AdWords team helped us generate important traffic from people interested in learning more about #NOWINCLUDED or sharing their story with us. Jason Scott, who leads the Google for Startups Accelerator: Black Founders program, is still connecting us to people in his network and identifying key opportunities for us months after the program wrapped. He continues to demonstrate that he is invested in seeing us succeed. 

Our company has made great progress against our goals, in part thanks to receiving capital from the Google for Startups Black Founders Fund. We received $100K in non-dilutive funding along with Google Cloud credits, Google.org Ads grants, and hands-on support. We used the funds to pay for the transition and development costs associated with moving to Google Cloud. The Google support and accountability has been incredible. After receiving the Google for Startups Black Founders Fund award, we’ve gone on to raise another $1M and moved our cloud from Salesforce to Google Cloud. 

We also had the amazing opportunity to be selected as one of six companies to take part in a face-to-face web conference with Sundar Pichai, Google’s CEO. We were thrilled to hear him explain his vision around health equity and the role Google plays. Ultimately, for us, it’s not just about the funding we get, but we are also gratified to receive support from an entity that truly believes in addressing this issue. We know Google is aligned with our mission of health and racial equity. 

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Championing diversity in clinical trials

Our 2022 looks bright. We expanded our presence to Washington, D.C. as part of the Johnson & Johnson Innovation JLABS ecosystem. We were also selected to take part in the BLUE KNIGHT initiative created between Johnson & Johnson Innovation and the Biomedical Advanced Research and Development Authority (BARDA) under the U.S. Department of Health and Human Services. 

Acclinate is also on track to have contracts with five of the top 25 largest biopharmaceutical companies in the U.S this year. They’ve taken note, as has the Food and Drug Administration (FDA), that the lack of diversity in clinical trials represents a significant health concern—to the extent that the FDA has provided strong guidance for pharmaceutical companies to  diversify their clinical trials. At the same time, the industry is also responding to pressure from communities of people of color to make equitable representation a priority.

Today, we are in the fortunate but challenging position to have significant inbound opportunities coming our way. In response, we continue to recruit and hire talented people to join our team. On the technology side, we are happy to be aligned with Google Cloud to have powerful cloud infrastructure that will scale with us, as well as high-caliber champions united in partnership. With people’s lives at stake, we are passionate in our commitment to helping ensure medications do what they are supposed to do: heal and improve the quality of life for everyone who takes them. 

Hear Acclinate cofounders Del Smith and Tiffany Whitlow chat with Google’s Head of Startup Developer Ecosystem Jason Scott and fellow Black Founders Fund recipient Bobby Bryant about building on Google Cloud in a recent Google for Startups Instagram Live


If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more

Case Study

Manipal Group: Delivering High-Quality Patient Care with Google Cloud

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Manipal Group of Hospitals deployed a mobile application that automates nurse rostering, reducing personnel requirements, costs, and stress on nurses and freeing up senior nurses for more valuable tasks.

One of India’s best-known healthcare brands, Manipal Group prides itself on clinical excellence and a patient-centric approach. From humble beginnings in 1953 as a single teaching hospital—the Kasturba Medical College—in a university town in Karnataka, India, Manipal Group has grown to a presence in seven cities in India and operations in Malaysia and Nigeria. “Our founder, Dr T. M. A. Pai, established Kasturba Medical College just six years after India gained independence,” says C. G. Muthana, Chief Operating Officer, Teaching Hospitals, Manipal Health Enterprises Pvt. Ltd, part of Manipal Group.

Manipal Health Enterprises Pvt. Ltd operates 11 corporate, or for-profit, hospitals and five teaching hospitals. “We have about 7,000 beds India-wide, and on that measure, we are the third-largest private-sector healthcare provider in India today,” says Muthana. The organization now employs about 6,000 people in its corporate hospitals and 5,000 people in its teaching hospitals.

Manipal Health Enterprises Pvt. Ltd acquires and operates world-class medical technologies in its teaching and corporate hospitals. However, with 75% of corporate hospital wards allocated to fee-paying private patients—compared to just 25% of the wards in teaching hospitals—the differences in information technology budgets are significant. “In the general wards that comprise most of the wards in teaching hospitals, patients are typically treated for free or at heavily subsidized rates,” explains Muthana. “So revenues and costs of delivery vary between hospitals, while employee costs remain similar.”

Rostering nurses a critical task

Rostering nurses to work shifts is one of the most important tasks at Manipal Group corporate and teaching hospitals. As at all hospitals, nurses administer medications, monitor patients, maintain records, manage intravenous lines, and work with doctors to heal patients. They can also provide advice and support to patients and loved ones, including teaching them how to administer medication outside a hospital setting. If too few nurses are rostered for a particular shift, the quality of patient care may suffer.

Google Cloud results

  • Enabled the hospital to correctly size its nursing workforce
  • Lowers stress on nurses by delivering more equitable rostering
  • Presents opportunity to better manage nurses’ leave and other administration tasks

However, rostering at the group’s hospitals was a time-consuming exercise. Senior nurses on each ward would have to spend up to 45 minutes per day manually amending paper-based rosters to accommodate requested changes to duty shifts for personal or other circumstances. The organization began receiving complaints from patients, doctors, and other hospital staff that, on occasion, too few nurses were rostered on for certain shifts—particularly at its flagship hospital in Bangalore. “We had based our rostering calculations on the number of beds occupied by patients and, when we investigated, we found at a macro level, we were rostering on the correct number of nurses,” says Muthana. “However, on some days, on wards optimally staffed by, say, 10 nurses per shift, we might have 14 nurses rostered on for one shift and seven rostered on for another shift. Those times we had seven, we had a clear shortage.”

In 2012, Muthana asked a consultant to develop algorithms to help automate the rostering. “Unfortunately, there were so many variables, the consultant failed to solve the problem,” he says. The Chief Operating Officer’s next step was to ask the founder and Chief Executive Officer of predictive analytics business Retigence Technologies—already working with the business on a materials management project—to develop an application to manage rostering.

Removing the daily drudgery

“Our plan with the automation project was to relieve our senior nurses of the daily drudgery of amending the rosters and to deliver rosters that were as fair as possible to all our staff,” says Muthana. “We also saw an opportunity to reduce our costs by reducing the overall number of nurses needed to look after our patients.”

Retigence Technologies’ team members then worked with the group’s nurses to capture the variables and requirements for the project. For example, a minimum number of nurses with one year experience or more needs to be rostered on for each shift. Retigence Technologies then started building an application using compute resources available through Compute Engine, a Google Cloud product. “We selected Google primarily because of its pioneering work in artificial intelligence (AI) and machine learning,” says Srinibas Behera, founder and Chief Executive Officer of Retigence Technologies.

With the nurses rostering application developed, Manipal Health Enterprises Pvt. Ltd undertook several pilots to build user acceptance. “Some of our senior nurses took time to accept the fact automation removed their control over rostering assignments, but were finally convinced by the better transparency the product offered,” says Muthana. The organization deployed the application to a smaller hospital and secured user support before rolling out the application to its Bangalore flagship.

Eliminating stress

Deploying the application has enabled Manipal Health Enterprises Pvt. Ltd to remove a buffer of about 100 nurses retained to accommodate the variations in number of nurses rostered for individual shifts. “The savings on those salaries more than paid for the cost of developing the application,” says Muthana.

The application also enabled the organization to reduce the stress on nurses—both the nurses in charge of the rosters and the nurses subject to the rosters. “Night shifts were more equitably distributed among the nurses, while we have been able to reduce the 45 minutes per day required to amend rosters to just 10 minutes,” says Muthana. “In Bangalore alone, we have 51 nurses in charge of rostering—so the combined saving there equates to nearly 30 hours per day.” This is freeing up these senior nurses to complete more important tasks.

The application was subsequently implemented at Kasturba Hospital, Manipal, again reducing the time needed to generate complete nursing rosters to less than 10 minutes.

Managing leave and training

The organization now plans to extend the application to manage leave and training for its nurses and other employees. “I would like to see every employee given an annual leave plan that is added to the roster at the start of the year,” says Muthana. “The flexibility and control afforded by the application would enable us to address challenges such as managing leave across a workforce with high attrition rates.” The organization would also be able to create a calendar to ensure nurses receive all their required training.

“We also plan to keep fine-tuning the application to deploy nurses more efficiently and continue to reduce their stress levels,” adds Muthana. “We also want to create a nursing load indicator tailored to patients’ specific circumstances. For example, a sedated patient may not require much nursing care, whereas a patient who comes in with a broken leg and may be on a ventilator may require assistance from three nurses at once.” The business plans to use Google’s AI and machine learning APIs in the future to improve the value and user experience of the product.

Whitepaper

Unlocking Business Acceleration in a Hybrid Cloud World

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Across industries, CEOs share a top priority—harness technology to jump-start growth, accelerate time to market, and foster innovation. CIOs and other technology leaders recognize that the C-suite depends on them to achieve growth and meet rising expectations for agility.

They increasingly view IT modernization—including migrating to the cloud, adopting new application architectures, and building on cloud-native services—as a way to sustain these goals. To date, however, most companies have not captured the anticipated agility benefits because a number of challenges hinder technology leaders as they push ahead with modernization initiatives.

While many of these challenges are valid, there are some false tradeoffs that can be avoided. New McKinsey research highlights that cloud migration needs to be combined with a comprehensive organizational approach to allow for a much more effective agile transformation. CIOs need to promote the transformation mind-set of focusing on differentiated business value by adopting agile processes, automating policies, and upskilling talent across the entire organization. They need to look beyond technology to change the way their IT organization operates across three foundational elements—people, processes, and policies.

Priorities include upskilling existing talent and creating new roles (such as site reliability engineers, full-stack engineers, and data scientists), revamping procedures by adopting agile
development processes with security integrated into every step, and enforcing policies through automation.

Download this McKinsey research report to understand the practices of leaders versus that of laggards and get the key “unlocks” that can help organizations move to higher levels of business agility as they pursue increased cloud adoption.

Case Study

How 20th Century Fox Uses Machine Learning to Gauge the Financial Performance of a Movie

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Success in the movie industry relies on a studio’s ability to attract moviegoers—but that’s sometimes easier said than done.

Moviegoers are a diverse group, with a wide variety of interests and preferences. Historically, movie studios have relied heavily on experience when deciding to invest in a particular script—but this can lead to huge risks, particularly when investing in new, original stories.

The iterative and complex process of matching stories and audiences is something that Julie Rieger, President, Chief Data Strategist and Head of Media, and Miguel Campo-Rembado, SVP of Data Science, together with their team of data scientists at 20th Century Fox, decided to clarify with data.

Together, Google Cloud and 20th Century Fox have built privacy-robust data partnerships to better understand moviegoers, and have developed in-house deep learning models that train on granular customer data and movie scripts to identify the basic patterns in audiences’ preferences for different types of films.

In 18 months, these models have become routine considerations for important business decisions, and provide one of their most objective, data-driven, and effective barometers to evaluate the tone of a movie, its affinity with core and stretch audiences, and its potential financial performance.

Find how machine learning helped achieve this (clue: it used movie trailers). Download the case study.

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DB Corp Opts For Google Cloud to Drive Transformation to Real-Time Operation

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