New Amazon Aurora capability automatically
scales to millions of write transactions per second and manages
petabytes of data while maintaining the simplicity of operating a
single database
New serverless option for Amazon ElastiCache
makes it faster and easier to create highly available caches and
instantly scales to meet application demand
New Amazon Redshift Serverless capability uses
AI to predict workloads and automatically scale and optimize to
meet price-performance targets
Genesys, MIO Partners, Peloton, Quantiphi, and
Tuya Smart among customers and partners using these new serverless
innovations
At AWS re:Invent, Amazon Web Services, Inc. (AWS), an
Amazon.com, Inc. company (NASDAQ: AMZN), today announced three new
serverless innovations across its database and analytics portfolio
that make it faster and easier for customers to scale their data
infrastructure to support their most demanding use cases. Today’s
announcement introduces Amazon Aurora Limitless Database, a new
capability that automatically scales beyond the write limits of a
single Amazon Aurora database, making it easy for developers to
scale their applications and saving them months compared to
building custom solutions. Additionally, Amazon ElastiCache
Serverless helps customers create highly available caches in under
a minute and instantly scales vertically and horizontally to
support customers’ most demanding applications, without needing to
manage the infrastructure. AWS is also releasing a new Amazon
Redshift Serverless capability that uses artificial intelligence
(AI) to predict workloads and automatically scale and optimize
resources to help customers meet their price-performance targets.
These announcements build on AWS’s pioneering work with serverless
technologies to help customers manage data at any scale and
dramatically simplify their operations, so they can focus on
innovating for their end users—without spending time and effort
provisioning, managing, and scaling their data infrastructure. To
learn more about unlocking the value of data using AWS, visit
aws.amazon.com/data.
“Since its earliest days, AWS has focused on removing
undifferentiated heavy lifting for customers, and we have continued
to build on that legacy through serverless offerings that
dramatically simplify what it takes to build, run, and manage
applications at scale," said Dr. Swami Sivasubramanian, vice
president of Data and Artificial Intelligence at AWS. "Data is the
cornerstone of every organization's digital transformation, and
harnessing data to its full potential requires an end-to-end
strategy that can scale with a customer’s needs while accommodating
all types of use cases. The dynamic nature of data makes it
perfectly suited to serverless technologies, which is why AWS
offers a broad range of serverless database and analytics offerings
that help support our customers' most demanding workloads. The new
serverless innovations announced today build on this foundation to
make it easier for customers to scale to millions of transactions
per second, quickly add capacity at a moment’s notice, and
dynamically adapt workload patterns to optimize for performance and
cost."
Organizations create and store petabytes of data from a growing
number of sources. To get the most value out of this data, these
companies need an end-to-end strategy that can help them analyze
and manage the data at any scale. Many AWS customers are already
using a wide variety of purpose-built data services to support
their most critical applications and make data-driven decisions,
including Amazon Aurora for relational databases, Amazon
ElastiCache for running in-memory caches, and Amazon Redshift for
data warehousing. These services remove much of the heavy lifting
that customers have to go through if they run their own database
and analytics solutions, allowing them to focus on creating
differentiated experiences for their end users. AWS continues to
simplify operations for customers by releasing serverless
technologies across its service portfolio, from some of AWS’s
earliest offerings like Amazon Simple Storage Service (Amazon S3)
to pioneering serverless, event-driven computing with AWS Lambda.
Today, AWS offers the broadest set of serverless data analytics
offerings in the cloud, making it easy for customers to take
advantage of benefits like automatic provisioning, on-demand
scaling, and pay-for-use pricing while using the right tool for the
job. The new innovations announced today further AWS’s commitment
to reimagining its database and analytics portfolio through
serverless technologies, by making it even easier for customers to
optimize costs and maximize their data’s value.
Amazon Aurora Limitless Database powers petabyte-scale
applications with millions of writes per second
Today, hundreds of thousands of customers use Amazon Aurora, a
fully managed MySQL- and PostgreSQL-compatible relational database
that provides the performance and availability of commercial
databases at up to one-tenth the cost. These organizations rely on
Amazon Aurora Serverless v2 to power their applications because it
is capable of scaling to support hundreds of thousands of
transactions in a fraction of a second. As it scales, it adjusts
capacity up and down in fine-grained increments to provide the
right amount of database resources for the application. However,
there are some use cases, such as online gaming and financial
transaction processing, with workloads that need to process and
manage hundreds of millions of global users, handle millions of
transactions, and store petabytes of data. Today, these
organizations must scale horizontally by splitting data into
smaller subsets and distributing them across multiple distinct
database instances in a process known as “sharding,” which requires
months—or even years—of upfront developer effort to build custom
software that routes requests to the correct instance or makes
changes across multiple instances. Organizations also need to
continuously monitor database activity and adjust capacity, which
can be time-consuming and impact availability. The ongoing
maintenance effort for these workloads is high, as organizations
need to coordinate routine maintenance operations—such as adding a
column to a table, taking consistent backups across all compute
instances, or applying upgrades and patches—and constantly tune and
balance the load across multiple instances. As a result,
organizations need ways to automatically scale their applications
beyond the limits of a single database without spending time
building their scaling solutions.
Amazon Aurora Limitless Database scales to millions of write
transactions per second and manages petabytes of data while
maintaining the simplicity of operating inside a single database.
Amazon Aurora Limitless Database automatically distributes data and
queries across multiple Amazon Aurora Serverless instances based on
a customer’s data model, eliminating the need to build custom
software to route requests across instances. As compute or storage
requirements increase, Amazon Aurora Limitless Database
automatically scales resources vertically within serverless
instances and horizontally across instances to meet workload
demand, providing customers with consistently high performance
while saving them months or years of effort in building custom
software to scale their databases. Maintenance operations and
changes can be made in a single database and automatically applied
across instances, eliminating the need for managing routine tasks
across dozens, or even hundreds, of database instances
manually.
Amazon ElastiCache Serverless makes it faster and easier to
create a cache and instantly scale to meet application
demand—without needing to provision, plan for, or manage
capacity
Organizations building applications store frequently accessed
data in caches to improve application response times and reduce
database costs. These customers use open source, in-memory data
stores like Redis and Memcached for caching because of their high
performance and scalability. To simplify the process of building
and running a cache, AWS offers Amazon ElastiCache, a fully managed
Redis- and Memcached-compatible service that is used by hundreds of
thousands of customers today for real-time, cost-optimized
performance. Today, Amazon ElastiCache scales to hundreds of
terabytes of data and hundreds of millions of operations per second
with microsecond response times, and organizations use it to deploy
highly available, mission-critical applications across multiple
Availability Zones. While many organizations appreciate the
fine-grained configuration options Amazon ElastiCache offers, some
companies building a new application or migrating existing
workloads want to get started quickly without designing and
provisioning cache infrastructure, a process that requires
specialized expertise and deep familiarity with application traffic
patterns. Organizations also need to constantly monitor and scale
their capacity to maintain consistently high performance, or
overprovision for peak capacity, which results in excess costs. As
a result, they need a solution that can help them manage the
underlying infrastructure, making it faster and easier to create
and operate a cache.
With Amazon ElastiCache Serverless, customers can now create a
highly available cache in under a minute without infrastructure
provisioning or configuration. Amazon ElastiCache Serverless
eliminates the complex, time-consuming process of capacity planning
by continuously monitoring a cache’s compute, memory, and network
utilization and instantly scaling vertically and horizontally to
meet demand without downtime or performance degradation. With
Amazon ElastiCache Serverless, customers no longer need to
rightsize or fine-tune their caches. Amazon ElastiCache Serverless
automatically replicates data across multiple Availability Zones
and provides customers with 99.99% availability for all workloads.
Customers only pay for the data they store and the compute their
application uses. Amazon ElastiCache Serverless is generally
available today for both Redis- and Memcached-compatible deployment
options. To get started, visit
aws.amazon.com/elasticache/features/#Serverless.
Next-generation, AI-driven scaling and optimizations in
Amazon Redshift Serverless deliver better price-performance for
variable workloads
Tens of thousands of customers collectively process exabytes of
data with Amazon Redshift every day. Many of these customers rely
on Amazon Redshift Serverless, which automatically provisions and
scales data warehouse capacity to meet demand based on the number
of concurrent queries. While customers enjoy the ease of running
analytics workloads of all sizes on Amazon Redshift Serverless
without needing to manage data warehouse infrastructure, they would
benefit further from the ability to easily adapt to changes in
their workloads along additional dimensions, such as the amount of
data or query complexity, to achieve consistently high performance
while optimizing cost. For example, an organization with normally
predictable dashboarding workloads may find that a new regulatory
reporting requirement means they need to ingest substantially more
data and handle more intensive, complex queries. To address
workload changes along all dimensions, while ensuring consistent
performance and without disrupting existing workloads, an
experienced database administrator would have to spend hours
separating the additional workload to a different data warehouse or
making multiple, complex manual adjustments. This includes
temporarily increasing the resources for data ingestion and new
query workloads, pre-computing results for quick data access,
organizing data for efficient retrieval, and timing data warehouse
management tasks. All of these optimizations need to be done
continuously, while managing each individual organization’s
priorities for balancing performance and cost, regardless of
changes in data volume, query complexity, or more concurrent
queries.
With the new AI-driven scaling and optimizations, Amazon
Redshift Serverless automatically scales resources up and down
across multiple workload dimensions and performs optimizations to
meet price-performance targets. Amazon Redshift Serverless uses AI
to learn customer workload patterns along dimensions such as query
complexity, data size, and frequency and continuously adjusts
capacity based on those dynamic patterns to meet
customer-specified, price-performance targets. Amazon Redshift
Serverless now also proactively adjusts resources based on those
customer workload patterns. For example, Amazon Redshift Serverless
with AI-driven scaling and optimizations automatically lowers
capacity during the day to handle dashboard workloads, but adds
just the right amount of required capacity on demand whenever a
complex query needs to be processed. Then overnight, Amazon
Redshift Serverless proactively increases capacity again to support
large data processing tasks without manual intervention. Building
on existing self-tuning capabilities, Amazon Redshift Serverless
automatically measures and adjusts resources and conducts a
cost-benefit analysis to prioritize the best optimization for a
given workload. Customers can set their own price-performance
targets in the AWS Console, choosing to optimize between cost and
performance. Amazon Redshift Serverless with AI-driven scaling and
optimizations is available in preview. To learn more, visit
aws.amazon.com/redshift/redshift-serverless/.
Genesys is a leader in AI-powered experience orchestration that
helps organizations engage with customers across any channel and
empowers employees in the contact center and beyond. “At Genesys,
we use Amazon ElastiCache to power high-throughput, low-latency
storage for our all-in-one cloud platform, enabling millions of
customer interactions per day,” said Rob Gevers, chief architect at
Genesys. “We expect Amazon ElastiCache Serverless to help us
improve performance and efficiency by eliminating the need to
provision instances and choose specific configuration settings and
scaling. With Amazon ElastiCache Serverless, we can remove
administrative overhead and offer a significant leap in stability
while providing the scalability we need to handle our growing usage
and variable workloads.”
MIO Partners, Inc. is a global investment and advisory
institution. “Our developers spend significant time evaluating
usage, configuring node types, and designing cluster topologies to
set up and configure cache capacity,” said Anand Mishra, chief
technology officer at MIO Partners. “With Amazon ElastiCache
Serverless, we can create a cache in less than a minute without any
infrastructure provisioning, configuration, or capacity planning.
Amazon ElastiCache Serverless eliminates the need for
time-consuming capacity planning, improving our cost efficiencies
and providing us with better operational reliability. Now, we can
redeploy the team of engineers who were previously engaged in
managing Redis to projects that deliver higher value for our
clients.”
Peloton aims to help people around the world reach their fitness
goals through its connected fitness equipment and
subscription-based classes. "At Peloton, we collect and process a
variety of data, ranging from hardware sales to instructor trends
and user workout data, to create and refine our business decisions
for better customer experiences,” said Jerry Wang, director of Data
Engineering at Peloton. “However, analytics workloads are becoming
more complex, causing our database administrators to spend a lot
more time changing capacity thresholds and performing manual
database optimizations. Leveraging the new optimizations
capabilities in Amazon Redshift Serverless, we can eliminate even
more of the data warehouse management tasks, making it more cost
efficient while delivering better performance.”
Quantiphi is a digital engineering company driven by the desire
to solve transformational problems. "At Quantiphi, we deliver
tailored data analytics and machine learning solutions for our
customers, and Amazon Redshift remains the cornerstone of our data
warehouse services," said Sanchit Jain, data and application
practice lead at Quantiphi. "We have been hearing from our
customers that they want a solution that can also help them meet
price-performance within their budget constraints. The newly
introduced AI-driven scaling and optimizations in Amazon Redshift
Serverless will help improve our offering, bringing flexibility and
intelligence to data management and ensuring automatic,
cost-effective scaling based on historical query data. With this
new capability, we can provide tailored solutions for our customers
who seek optimal price-performance while adapting to ever-growing
data volumes."
Tuya Smart offers a cloud platform that connects devices via the
Internet of Things (IoT) and empowers partners and customers by
improving product value and making consumer lives more convenient
through technology application. “Tuya's IoT Developer Platform has
over 846,000 registered developers from over 200 countries, serving
more than 7,600 enterprises with Tuya IoT solutions,” said Chong
Chen, head of Data Infrastructure at Tuya Smart. “We have been
using Amazon Aurora, along with other AWS purpose-built databases,
for more than five years, but we had to build our own in-house
sharding and proxy solution for databases due to high write
requests. We are excited that Amazon Aurora Limitless Database can
help us bring our IoT platform performance and management to the
next level by managing and scaling the write throughput we need to
serve our increasing customers base while providing a consistent,
smooth, and efficient response experience for our customers, all
without us having to use a self-managed solution.”
About Amazon Web Services
Since 2006, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud. AWS has been continually
expanding its services to support virtually any workload, and it
now has more than 240 fully featured services for compute, storage,
databases, networking, analytics, machine learning and artificial
intelligence (AI), Internet of Things (IoT), mobile, security,
hybrid, virtual and augmented reality (VR and AR), media, and
application development, deployment, and management from 102
Availability Zones within 32 geographic regions, with announced
plans for 15 more Availability Zones and five more AWS Regions in
Canada, Germany, Malaysia, New Zealand, and Thailand. Millions of
customers—including the fastest-growing startups, largest
enterprises, and leading government agencies—trust AWS to power
their infrastructure, become more agile, and lower costs. To learn
more about AWS, visit aws.amazon.com.
About Amazon
Amazon is guided by four principles: customer obsession rather
than competitor focus, passion for invention, commitment to
operational excellence, and long-term thinking. Amazon strives to
be Earth’s Most Customer-Centric Company, Earth’s Best Employer,
and Earth’s Safest Place to Work. Customer reviews, 1-Click
shopping, personalized recommendations, Prime, Fulfillment by
Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire
tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology,
Amazon Studios, and The Climate Pledge are some of the things
pioneered by Amazon. For more information, visit
www.amazon.com/about and follow @AmazonNews.
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