Memorystore for Redis Read Replicas to Scale App Read Requests by 6X

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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:

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.

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.
Google Unveils Topaz, the New Subsea Cable Connecting Asia and Canada

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There’s a new subsea cable in town: Topaz, the first-ever fiber cable to connect Canada and Asia.
Once complete, Topaz will run from Vancouver to the small town of Port Alberni on the west coast of Vancouver Island in British Columbia, and across the Pacific Ocean to the prefectures of Mie and Ibaraki in Japan. We expect the cable to be ready for service in 2023, not only delivering low-latency access to Search, Gmail and YouTube, Google Cloud, and other Google services, but also increasing capacity to the region for a variety of network operators in both Japan and Canada.
Google is spearheading construction of the project, joined by a number of local partners in Japan and Canada to deliver the full Topaz subsea cable system. Other networks and internet service providers will be able to benefit from the cable’s additional capacity, whether for their own use or to provide to third parties. And, similar to other cables we’ve built, with Topaz we will exchange fiber pairs with partners who have systems along similar routes. This is a longstanding practice in the industry that strengthens the intercontinental network lattice for network operators, for Google, and for users around the world.

Network infrastructure investments like Topaz bring significant economic activity to the regions where they land. For example, according to a recent Analysys Mason study, Google’s historical and future network infrastructure investments in Japan are forecasted to enable an additional $303 billion (USD) in GDP cumulatively between 2022 and 2026.
The width of a garden hose, the Topaz cable will house 16 fiber pairs, for a total capacity of 240 Terabits per second (not to be confused with TSPs). It includes support for Wavelength Selective Switch (WSS), an efficient and software-defined way to carve up the spectrum on an optical fiber pair for flexibility in routing and advanced resilience. We’re proud to bring WSS to Topaz and to see the technology is being implemented widely across the submarine cable industry.
While Topaz is the first trans-Pacific fiber cable to land on the West Coast of Canada, it’s not the first communication cable to connect to Vancouver Island. In the 1960s, the Commonwealth Pacific Cable System (COMPAC) was a copper undersea cable linking Vancouver with Honolulu (United States), Sydney (Australia), and Auckland (New Zealand), expanding high-quality international phone connectivity. Today, COMPAC is no longer in service but its legacy lives on. The original cable landing station in Vancouver — the facility where COMPAC made landfall on Canadian soil — has been upgraded to fit the needs of modern fiber optics and will house the eastern end of the Topaz cable.
Traditional and treaty rights, and local communities, are deeply important to our infrastructure projects. The Topaz cable is built alongside the traditional territories of the Hupacasath, Maa-nulth, and Tseshaht, and we have consulted with and partnered with these First Nations every step of the way.
“Tseshaht is very proud of this collaboration and our partnership with Google, who has been very respectful and thoughtful in its engagement with our Nation. That’s how we carry ourselves and that’s how we want business to carry themselves in our territory.“ — Tseshaht First Nation – Elected Chief Councillor-Ken Watts
“The five First Nations of the Maa-nulth Treaty Society are pleased that we have concluded an agreement with Google Canada and have consented to the installation of a new, high-speed fiber optic cable through our traditional territories. This agreement, in which both Google Canada and our Nations benefit, is based on respect for our constitutionally protected treaty and aboriginal rights and enhances the process of reconciliation. We would also like to acknowledge the sensitivity that Google Canada expressed during our talks in regard to the pain and trauma experienced by our people as a result of residential school experience. We look forward to a long and mutually beneficial relationship with Google Canada.” —Chief Charlie Cootes, President of the Maa-nulth Treaty Society
“Google’s respect towards our Nation is appreciated and has good energy behind it.” —Hupacasath First Nation – Elected Chief Councilor – Brandy Lauder
With the addition of Topaz today, we have announced investments in 20 subsea cable projects. This includes Curie, Dunant, Equiano, Firmina and Grace Hopper, and consortium cables like Blue, Echo, Havfrue and Raman — all connecting 29 cloud regions, 88 zones, 146 network edge locations across more than 200 countries and territories. Learn about Google Cloud’s network and infrastructure on our website and in the below video.

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Giving Customers More Choice: Google Cloud’s New Product and Pricing Options

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Over the past several years, Google Cloud has made significant investments in our infrastructure product portfolio. We launched new Tau T2D VMs, which deliver 42% better price-performance vs. other leading cloud providers. We upgraded Cloud Storage to offer more flexibility to support customers’ enterprise and analytics workloads, with dual-region buckets and upcoming Turbo Replication. And we’ve delivered numerous improvements to our global network, including expansion to 29 cloud regions.
However, from conversations with customers, we’ve also learned we can do more to align our capabilities and pricing with their varied workloads. So, today, we are announcing we will adjust our infrastructure product and pricing structure to give customers more choice in how they pay for what they use alongside new, flexible SKUs with new product options and capabilities. These changes are designed to help ensure better product fit for our customers’ use cases across a wider array of workloads. They are also designed to better align with how other leading cloud providers charge for similar products, so customers can more easily compare services between leading cloud providers.
Some of these changes will provide new, lower-cost options and features for Google Cloud products. Other changes will raise prices on certain products. Ultimately, our goal is to provide more flexible pricing models and options for how customers are using our cloud services. Here’s an overview of what customers can expect:
Which services are changing? What new services are being introduced?
We are changing prices for some storage, compute, and networking products. The changes provide customers with new ways to optimize their spending based on workload type and size, or data portability needs, as well as reducing costs on some services. Specific changes include:
- Cloud Storage pricing changes for data mobility, including replication of data written to a dual- or multi-region storage bucket, and inter-region data access
- Introduction of a new lower-cost archive snapshot option for Persistent Disk (PD), so that compliance/archiving use cases are charged less than compute-intensive DevOps workloads
- New outbound data processing pricing for Cloud Load Balancing, in line with other leading cloud providers
- New pricing for Network Topology, which will include Performance Dashboard within Network Intelligence Center at no additional charge
Will customers’ bills increase? Decrease?
The impact of the pricing changes depends on customers’ use cases and usage. While some customers may see an increase in their bills, we’re also introducing new options for some services to better align with usage, which could lower some customers’ bills. In fact, many customers will be able to adapt their portfolios and usage to decrease costs. We’re working directly with customers to help them understand which changes may impact them.
When will the new prices go into effect?
Today, we sent customers a six-month notice on the price changes, which go into effect on October 1, 2022. Customers under existing commit contracts with a floating or fixed discount will not face any changes until renewal. Our goal is to help our customers manage any impact of these changes and allow time for them to adjust or modify their implementations.
What should customers do next?
There are a number of things customers can do to prepare for the changes:
- Read through the Mandatory Service Announcement (MSA) sent on March 14.
- Consider what actions, if any, they may want to take based on current storage, networking, and compute needs. Many of these changes may have simple choices associated with them.
- Consider using the Storage Transfer Service to select the right Cloud Storage bucket locations. Storage Transfer Service will be available free-of-cost for transfers within Cloud Storage, starting April 2 until the end of the year.
For those customers under contract, Google Cloud account representatives are available to discuss these changes. Please visit our pricing page and the links below for more details on our updates to storage, networking, and PD pricing, including information on how to modify your implementations if needed. If you do not have an account manager and still have questions please review our public FAQ, which will be updated regularly, as well as the resource links below.
Note: This pricing analysis is valid as of February 2022.
Resources:
S4 Agtech Transforms Agriculture with Google Cloud

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Like countless other industries, farming is going digital and undergoing big changes—driven by access to more actionable information. The agriculture business can now gather and analyze georeferenced data from satellites, combined with data from IoT sensors in fields, crop rotation and yield histories, weather patterns, seed genotypes and soil composition to help increase the quantity and quality of crops.
This is essential for businesses in the agriculture industry, but it’s also critical to address growing food shortages around the world.
At S4, we create technology to de-risk crop production. We provide customers seeking agricultural risk management solutions with the tools to make better, data-driven decisions for their crop planning, based on machine learning and proprietary algorithms.
We interpret plant evolution on a global scale with predictive modeling and analytics, and offer super-efficient risk-transferring solutions. Our multi-cloud platform includes a petabyte-scale database, an open source stack, and—after 50 proof-of-concept evaluations—BigQuery for our data warehouse and the Cloud SQL database service to handle OLTP queries to our PostgreSQL database.
These PoCs included, among others, Microsoft Azure Data Lake Analytics, IBM Netezza, Postgres/PostGIS running on IBM bare-metal servers with SATA SSDs and on Google’s Compute Engine with NVMe disks, and on-premises memSQL, CitusData and Yandex ClickHouse.
Weeding out risk in an uncertain market
According to recent research, climate extreme events like drought, heat waves, and heavy precipitation are responsible for 18-43% of global variation in crop yields for maize, spring wheat, rice, and soybeans. This is a clear trend for other crops as well. Such variation poses risks of food shortages as well as large financial risks to farmers, insurers, and regions dependent on successful crop yields. Also, it creates vast humanitarian difficulties.
Our mission at S4 is to help de-risk crop production by matching the right data with analytics tools so farmers and other participants in the agricultural value chain can plan better, resulting in more reliable food supplies.
In a nutshell, we create indices out of biological assets. These indices measure yield losses on crops that are caused by the effects of weather and other factors, which are then used as underlying assets for products, such as swap/derivative contracts and parametric insurance policies, to transfer risk to the financial markets.
We enable insurers and lenders to buy and sell agricultural risks through the futures market. Also, our other products help farmers and seed and fertilizer companies provide customized genotype recommendations and fertilization requirements. This helps to optimize planting by geography, resources, and crop species, monitor phenological, pests and humidity evolution throughout the crop season, and estimate yields.
Local communities benefit from S4’s technology, as the ability to manage weather risks allows farmers to stabilize their cash flows, invest more to produce more with fewer risks, and develop in a more sustainable manner.
Growing data sources, reducing costs, accelerating performance
With the volume of diverse data sources and analytical complexity both growing at a very fast pace, we decided that using a major cloud services provider with a broad roadmap and global partnerships would be beneficial to S4’s future evolution.
At the same time, we wanted to bring our services to users faster and cut costs by consolidating our on-premises technology stack. When we started evaluating providers, our leading criteria included a powerful geospatial database and data analytics tools along with excellent support, all at a competitive price. GCP prevailed in nearly all criteria categories among the 50 companies we measured.
Our previous platform architecture included a hybrid relational database that used Compute Engine for virtual machines and Cloud Storage for database backup. The RDBMS was slow. Maintaining our own data warehouse was complex and expensive.
We wanted to use machine learning and neural networks, but couldn’t do so easily and affordably. The complexity of that system meant that products or services requiring small changes or additions to the data model translated to expensive expansions of infrastructure or project time.
Also, agronomical or product teams couldn’t test these changes by themselves, always requiring the intervention on no small part of the IT team, which led to further delays.
We added GCP services like BigQuery as S4’s cloud data warehouse and use BigQuery GIS for geospatial analysis, Cloud Dataflow for simplified stream and batch data processing, and Cloud SQL for queries to the S4 database platform, which have all made a huge impact on our services and bottom line.
Database and analytics costs have decreased by 40% and customers are receiving our analytical results 25% faster. In addition, we’ve eliminated the time-consuming downloading of images, reducing storage and processing costs by 80%, because we no longer need expensive tools licenses, and have greatly reduced classification processing times.
Our customers working in the agriculture industry are also benefiting from this infrastructure change. They are now able to speed up their data analytics using our GCP-based platform.
“S4 products and technologies unlock the full potential of satellite imagery for crop prescriptions, monitoring and yield estimates,” says Nicolás Loria, Manager of Marketing Services, Southern Cone, Corteva Agriscience.
“We’ve worked with S4 for the last three (and starting year number four) crop seasons as its team capabilities, data integration capacities, and analytics insights have allowed Corteva to perform an entire new solution. Thanks to S4’s customized 360° approach, fast response and delivery times, we have safely outsourced our remote crop analytic technical needs.”
Also, this new architecture has allowed us to scale our models and databases with almost no limits, at a fraction of the cost vs. the previous models.
We’ve saved a lot of time on executing processes and reduced work needed by our internal teams to do certain tasks, like preparing images, converting them, validating results, and more. Using Google Earth Engine has decreased the execution time of daily tasks anywhere from 50% to 90% of the previous time, going from an average time of 30 minutes to between four and 15 minutes, depending on the task.
In addition to saving money and time, we are able to focus on innovation with the GCP performance and features we’re using. We’re able to seamlessly add satellite data to analytics using both public datasets and our own private data, and deliver GIS data management, analytics, crop classification and monitoring in real time.
We can do semi-automatic crop classification and classification using spectral signatures with Google Earth Engine. Later this year, we’ll be using neural networks for pattern recognition and machine learning in new applications to improve crop yields and fine-tune risk models. And using GCP and Google Earth Engine infrastructure means we can run models for customers in South America and around the world, since Google Earth Engine has global satellite imagery available.
We’ve heard from our customer Indigo Argentina that they’re able to bring customers data insights faster.
“We are working with S4 in the development of two different applications for satellite crop monitoring and yield assessment,” says Carlos Becco, CEO, Indigo Argentina. “S4’s technology allowed us to manage and analyze multiple sources and layers of information in real time, letting us uncover valuable insights in Indigo’s own microbiome technologies, and at a very competitive cost.”
Analytical products and app development thrive with GCP
With GCP, we are updating and improving algorithms that we built manually with machine learning processes to develop drought indices for upcoming crop seasons. Algorithms can recognize specific phases of crop phenology (e.g., bud burst, flowering, fruiting, leaf fall) and correlate them with photosynthetic activity, light, water, temperature, radiation, and plant genetics factors. Other analytical products like crop monitoring, pre-planting recommendations, financial scoring, and yield estimation can now do a lot more for users by offering multiple layers and datasets, faster image processing, and real-time access via APIs.
We also replaced our bare-metal S4 app deployment with the App Engine serverless application platform. It provides tighter integration between the S4 platform and our BigQuery data warehouse for integration with marketplaces and third-party solutions.
We get all of these Google Cloud features with all the benefits of managed cloud services, from multiversioning and security to automatic backups and high availability.
At S4, we trust technology to decode plant growth and help protect farmers and their communities from climate change. With growing food shortages due to increasing populations and intensifying weather, data and analytics can have a huge impact in lowering financial risks and improving agricultural yields. It’s one sector where cloud, database, analytics, and other technologies are combining to improve business outcomes and affect the lives of billions of people. Learn more about S4’s work and learn more about data analytics on Google Cloud.
Israeli Government Chooses Google Cloud to Power its Cloud-based ‘Project Nimbus’

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Google Cloud today announced that it has been selected by the Israeli government to provide public cloud services to help address the country’s challenges within the public sector, including in healthcare, transportation, and education.
Following a thorough public tender process, Google Cloud was selected for this four-phase project known as “Project Nimbus.” The agreement will deliver cloud services to all government entities from across the state, including ministries, authorities, and government-owned companies. The agreement is also available for higher education, health maintenance organizations and municipalities. The project will run for an initial period of 7 years, and the Israeli government may extend the engagement for up to 23 years in total.
As part of the agreement, Google Cloud will work with the public sector on the formulation of best practices for cloud migration, integration and migration to the cloud, and optimisation of cloud services. Google Cloud will also provide training to the country’s technical government employees and senior leaders to enhance digital skills. Google Cloud announced last month that it will open a Google Cloud region in Israel to make it easier for customers to serve their own users faster, more reliably and securely. The region in Israel will be available to serve not only the government and related entities but also private commercial companies, just like any other Google Cloud region.
The Accountant General of Israel, Mr. Yali Rothenberg, congratulates Google on their winning bid in the first tender of “Project Nimbus”, a multi-year flagship project led by the Israeli Government Procurement Administration, that is intended to provide a comprehensive framework for the provision of cloud services to the Government of Israel.
We are delighted to have been chosen to help digitally transform Israel. This builds on the continued success we are seeing with the public sector globally.
Google Cloud region in Israel
In April, we announced that a new Google Cloud region is coming to Israel to make it easier for customers to serve their own users faster, more reliably and securely. Our global network of Google Cloud regions are the foundation of the cloud infrastructure we’re building to support our customers in the Middle East and around the world. With cloud’s 25 regions (and forthcoming Middle East regions in Qatar and Saudi Arabia) and 76 zones around the world, we deliver high-performance, low-latency services and products for Google Cloud’s enterprise and public sector customers.
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