The 12 Coolest AWS Tools Of 2020 (So Far)

Here’s a look at 12 new product/service releases and updates announced so far this year, including Amazon AppFlow, Amazon CodeGuru, AWS Fargate Platform Version 1.4.0, Amazon Kendra and new features for Amazon Macie.

Amazon Web Services has been known for its rapid pace of innovation in cloud computing, and this year is no different.

It’s added new AWS tools and services ranging from 6th-generation Elastic Compute Cloud (EC2) instances, to Amazon Honeycode, which allows customers to build mobile and web applications without writing programming code, to new capabilities for its Amazon Connect customer contact solution.

Other releases bolstering its cloud portfolio so far in 2020 are the AWS Snowcone portable edge device, the Amazon Interactive Video Service (IVS) live streaming solution, AWS IoT SiteWise and Amazon Relational Database Service (RDS) on its hybrid AWS Outposts cloud offering.

As AWS CEO Andy Jassy told CRN last year, “We just have a lot more capability than anybody else, in part, because we started six years earlier, but also in part just because we‘re iterating at a faster clip than anybody.”

AWS offers more than 175 fully featured services for compute, storage, databases, networking, analytics, robotics, machine learning (ML) and artificial intelligence, internet of things (IoT), mobile, security, hybrid cloud, virtual and augmented reality, media, and application development, deployment and management.

Here’s a look at 12 new product/service releases and updates announced so far this year, including Amazon AppFlow, Amazon CodeGuru , AWS Fargate Platform Version 1.4.0, Amazon Kendra and new features for Amazon Macie.

See the newest entry: The 10 Coolest New AWS Tools Of 2022 (So Far)

AWS Snowcone

AWS last month launched the latest and smallest member of its Snow line of portable edge devices with the general availability of AWS Snowcone.

AWS Snowcone is a portable and rugged edge computing device for collecting, processing and transferring data to the AWS cloud from disconnected environments outside traditional data centers. It weighs about 4.5 pounds and is the size of a tissue box, allowing it to fit in a conventional mailbox or small backpack, or attach to a drone.

AWS Snowcone is an AWS-managed service, with AWS providing direct support to customers. It’s designed for remote or extreme conditions without consistent network connectivity or environments that require portability, including hospitals and first-responder vehicles, military operations, factory floors, oil rigs, remote offices and movie theaters. Industrial IoT, drones, tactical edge computing, content distribution, data migration, video content creation and transportation are among its use cases.

Snowcone includes support for AWS IoT Greengrass, the ability to run Amazon EC2 instances and local storage. It can be used as an IoT hub, data aggregation point, application monitor or lightweight analytics engine. Users can collect and process data and then move it from AWS Snowcone to the AWS cloud, either offline by shipping the device to AWS using its E Ink shipping label or online using Ethernet or Wi-Fi with AWS DataSync, which are preinstalled on the device.

Since AWS rolled out its Snow line in October 2015 with the introduction of Snowball, customer use has greatly increased along with the need for a smaller device with more portability, according to the cloud provider.

“This year we see growing interest around Edge computing and helping customers get their applications closer to their end-users, reducing latency, lowering data transfer costs to the cloud and providing near-real-time output,” said Dave Sellers, general manager of multi-cloud at World Wide Technology, an Advanced AWS Consulting Partner based in Maryland Heights, Mo. “AWS continues to innovate and release solutions across many edge computing categories. AWS Outposts, LocalZones and Wavelength offer infrastructure services to support applications closer to the end user. The AWS Snow family solves for data transfer and remote and disconnected situations, with the recent release of AWS Snowcone providing even more flexibility and choice.”

Amazon Honeycode

AWS launched Amazon Honeycode, which allows customers to build mobile and web applications without writing programming code, in beta last month.

Amazon Honeycode allows customers to bypass hiring developers – or resorting to emailing spreadsheets or documents -- to build often-costly custom applications for tasks ranging from approving purchase orders, inventory management and conducting simply surveys, to managing complex project workflows for multiple teams or departments, according to AWS.

Designed for non-professional “citizen” developers who are end users inside enterprises, the fully managed service combines the familiar interface of a spreadsheet with the data management capability of an AWS-built database. Customers can use Amazon Honeycode’s visual application builder to create interactive web and mobile apps to perform tasks including tracking data over time, notifying users of changes, routing approvals and facilitating interactive business processes.

With the release, AWS joins Microsoft and Google Cloud in the no-code application competition. But Gartner research vice president Jason Wong referred to Amazon Honeycode as functionally “very lightweight” in its initial release compared to Microsoft Power Apps, which launched in 2016, and Google Cloud’s AppSheet, gained from the acquisition of the 6-year-old Seattle startup in January.

Excited to bring customers the next gen of Amazon EC2 instances powered by #AWS-designed, Arm-based Graviton2 processors that deliver up to 40% better price/performance than comparable current x86 instances. Should be a game changer! https://t.co/UCmidWcTmP

— Andy Jassy (@ajassy) June 12, 2020

6th-Gen EC2 Instances

AWS CEO Andy Jassy called AWS’ new sixth-generation Amazon EC2 C6g and R6g instances, which are powered by Arm-based AWS Graviton2 processor,s an expected “game changer.”

First unveiled at AWS re:Invent in December, the cloud provider made the new AWS-designed, compute-optimized C6g and memory-optimized R6g instances generally available last month.

“Excited to bring customers the next gen of Amazon EC2 instances powered by #AWS-designed, Arm-based Graviton2 processors that deliver up to 40% better price/performance than comparable current x86 instances,” Jassy tweeted. “Should be a game changer!”

The Amazon EC2 C6g and cR6g instances currently are offered in AWS’ U.S. East (northern Virginia and Ohio), U.S. West (Oregon), Europe (Frankfurt), Europe (Ireland) and Asia Pacific (Tokyo) cloud regions.

AWS designed the C6g instances for compute-intensive workloads, including high-performance computing, batch processing, video encoding, gaming, scientific modeling, distributed analytics, ad-serving and CPU-based ML inference. The R6g instances are designed for workloads that process large data sets in memory, including open-source databases such as MySQL, MariaDB and PostgreSQL, in-memory caches such as Redis, Memcached and KeyDB, and real-time, big data analytics.

The new instances -- and general-purpose EC2 M6g instances rolled out in May – have a 40 percent better price performance over comparable current-generation x86-based Amazon EC2 C5 instances, according to AWS. Built on the AWS Nitro System of AWS-designed hardware and software, they’re each available in nine instance types, including bare metal.

“This is a big step forward over our current instance types, and it‘s why we’re leading with Graviton,” James Hamilton, vice president and distinguished engineer at AWS, said while announcing the launch. “Even I was slightly surprised by the Graviton performance, despite the fact that I was there on day one. We have up to 64 cores, up to 25 gigabits per second of enhanced networking and up to 19 gigabits per second of EBS (Elastic Block Store) storage bandwidth.”

The Arm-based AWS Graviton2 processors allow for up to 7x greater performance, 4x more compute cores and 5x faster memory than the Arm-based EC2 A1 instances powered by AWS’ first-generation Graviton processor introduced a year ago.

“ARM-based EC2 instances such as the new C6g and R6g offerings from AWS will make it much easier for software developers to port their infrastructure to ARM to enable lower power consumption and enable a greater software base for IoT- and maker-based devices like the Raspberry Pi, which, while improving in terms of hardware, still struggle with available software,” said John Best, chief technology officer of xOps, an AWS Consulting Partner with headquarters in Far Hills, N.J. “Hopefully these new EC2 instances will make porting easier for developers.”

Amazon IVS

This month’s AWS rollouts included the general availability of Amazon Interactive Video Service (IVS), a fully managed live streaming solution. It uses the same technology behind the popular Twitch live streaming platform to make it easier to quickly set up live, low-latency interactive video streams -- for web and iOS and Android mobile applications -- that can support millions of viewers at a time globally.

The fully managed service allows customers to post live content with latency that can be under three seconds -- significantly lower than the 20- to 30-second latencies typical of online streaming video -- according to AWS, while removing the complexity, time and high costs of setting up the required infrastructure.

Customers can use the Amazon IVS player software development kit (SDK) and timed metadata APIs to incorporate interactive features into their live streams, including virtual chat spaces, votes and polls to gauge audience opinions, real-time question-and-answer sessions, and synchronized promotional elements to let viewers make purchases or donations related to the content. There are no additional charges or upfront commitments required to use Amazon IVS, and customers pay only for video input to Amazon IVS and video output delivered to viewers.

“Online audiences are increasingly turning to mobile and web applications for live video across sports, entertainment, education and work,” AWS said in announcing Amazon IVS. “Today’s viewers require higher-resolution content and smooth video playback without buffering or delays, no matter where they are or what device or application they are using. Viewers have also come to expect more interactivity in live streaming, so they can engage with those experiences -- and others watching -- as events unfold, not moments after they happen.”

Customers can send their live videos to the Amazon IVS ingest endpoint using standard streaming software such as the free Open Broadcaster Software. Amazon IVS ingests the video and transcodes and optimizes it before making it available for live delivery across AWS-managed global infrastructure, using the same video transfer technology that Twitch uses.

The Amazon IVS Management Console and APIs for control and creation of video streams are available in AWS’ U.S. East (N. Virginia), U.S. West (Oregon), and Europe (Ireland) cloud regions, while video ingestion and delivery is available globally via a separate managed network of infrastructure optimized for live video.

AWS IoT SiteWise

Now generally available, AWS IoT SiteWise is a managed service that collects data from sensors and industrial equipment, structures and labels it, and generates real-time performance metrics to help customers make better data-driven decisions.

Customers can use AWS IoT SiteWise to monitor operations across their facilities, help prevent costly equipment issues and reduce production gaps.

Obtaining performance metrics from sensors and industrial equipment in multiple locations can be challenging because the needed data often is confined to proprietary on-premises data stores and typically requires specialized expertise to retrieve and convert it to a format that enables analysis, according to AWS. Its solution, meanwhile, simplifies the process by providing AWS IoT SiteWise Connector gateway software that sits in customers’ facilities, runs on common industrial gateway devices running AWS IoT Greengrass and automates data collection and organization, the company said. The gateway connects to customers’ on-premises data servers and sends the data to the AWS cloud.

AWS IoT SiteWise is available in AWS’ U.S. East (N. Virginia), U.S. West (Oregon), Europe (Frankfurt) and Europe (Ireland) cloud regions.

Volkswagen, Bayer Crop Science, water filtration system provider Pentair and Genie, a lifting and material processing products manufacturer, are among AWS customers using AWS IoT SiteWise.

The IoT SiteWise launch is important, because IoT is not just a buzzword anymore – “everything‘s IoT,” according to Taylor Bird, senior vice president at Onica, a Rackspace Technology company and AWS Premier Consulting Partner.

“SiteWise shows how Amazon is…going to look for opportunities to get into new industries,” he said. “That‘s really going to push IoT manufacturing forward.”

AWS Outposts And Amazon RDS

AWS launched Amazon Relational Database Service (RDS) on AWS Outposts, its hybrid cloud offering, last month.

The new support allows customers to create fully managed relational database instances in their on-premises environments for low-latency workloads that must be in close proximity to on-premises data and applications. It also enables backup to an AWS cloud region and management of RDS databases in the cloud or om premises using the same AWS Management Console, APIs and command line interface.

AWS Outposts, which launched in December, extends AWS’ cloud infrastructure, services, APIs and tools into customers’ on-premises data centers or colocation sites with compute-and-storage server racks outfitted with AWS-designed hardware. The 11-year-old Amazon RDS makes it easier to set up, operate and scale a relational database in the cloud.

Amazon RDS on Outposts provides resizable capacity for on-premises databases and automates administration tasks including infrastructure provisioning, database setup, patching and backups. It launched with support for MySQL and PostgreSQL, and support for other database engines is “coming soon,” according to AWS.

“The late 2019 GA (general availability) of Outposts has been a huge thing for our customer base and our business,” said Onica’s Bird. “We think it‘s really big -- sort of Amazon redefining what hybrid computing is. But some of the problems with its initial sort of preview is it only did one or two things. RDS is…a huge use case for Outposts.”

Amazon AppFlow

AWS debuted Amazon AppFlow debuted in April to help customers more easily create and automate private data flows between AWS and third-party, software-as-a-service (SaaS) applications -- without writing custom integration code.

The fully managed integration service enables customers with diverse technical skills to manage petabytes or exabytes of data spread across applications with a “few clicks” and without developing custom connectors or managing application programming interface and network connectivity.

Customers can build and execute secure data flows between AWS services such as Amazon S3 and Amazon Redshift and SaaS applications in minutes, including those of Salesforce, Infor Nexus, Marketo, ServiceNow, Slack, Trend Micro and Zendesk, according to AWS.

The no-code service also works with AWS PrivateLink to route data flows through AWS rather than the exposing them to the public internet. PrivateLink provides private, secure connectivity between virtual private clouds, AWS services and on-premises applications on the AWS network.

David Brown, AWS‘ vice president of Amazon EC2, said AWS recognized the need for a high-level service that “took away a lot of the complexity of having to transfer that data between the service that you might be doing or the application you might be using to an AWS service.”

Organizations previously would need skilled developers to build often time-consuming connectors and had to worry about how the data would be transformed, how often they wanted to run the process to move data over and how to keep it up current, Brown said.

“Very often, the solution that works is very small-scale -- it doesn‘t work at very large scale unless you have really strong engineers -- and so this was something that companies weren’t doing,” Brown said.

Amazon AppFlow so far is available in the following AWS regions: U.S. East region (Northern Virginia), U.S. East (Ohio), U.S. West (Northern California), U.S. West (Oregon), Canada (Central), Asia Pacific (Singapore), Asia Pacific (Toyko), Asia Pacific (Sydney), Asia Pacific (Seoul), Asia Pacific (Mumbai), Europe (Paris), Europe (Ireland), Europe (Frankfurt), Europe (London) and South America (São Paulo).
“AppFlow is a wonderful data-transfer option for those organizations worried about managing large amounts of SaaS-related data, and it‘s good to see AWS allowing flexibility when it comes to giving organizations choice in how to use and manage this data,” said xOps’ Best.

Amazon CodeGuru

The ML-powered Amazon CodeGuru helps developers create better applications by providing automated recommendations for improving Java code quality and by identifying apps’ most expensive lines of code.

The new tool helps proactively identify issues throughout the app development cycle to reduce CPU usage and costs. It has two components: CodeGuru Reviewer identifies critical issues and elusive bugs during the application development process, while CodeGuru Profiler is designed to optimize performance for applications running in production and identify the most expensive code lines of code to cut operational costs by up to 50 percent, according to AWS. The latter supports applications written in Java virtual machine languages including Java, Sacala, Kotlin, Apache Groovy, Jython, JRuby and Clojure.

Launched in preview at AWS re:Invent in December, Amazon CodeGuru went generally available in late June in 10 AWS cloud regions.

During the preview, AWS implemented a new pricing model for Amazon CodeGuru Reviewer, charging for revisions to a pull request only for changed or newly added lines of code. It also added support for Atlassian Bitbucket repositories and added a -javaagent switch to Amazon CodeGuru Profiler that allows customers to start the profiling agent using a command line.

Other new features include CodeGuru Reviewer support for Github Enterprise, in addition to anomaly detection, Lambda function support and Amazon CloudWatch metrics and alerts for CodeGuru Profiler.

AWS CloudFormation support is expected to be added soon.

AWS Fargate Platform Version 1.4.0

In April, AWS launched a new platform version 1.4.0 of AWS Fargate, its compute engine for Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS) that allows users to run containers without managing servers or clusters.

There‘s no question that containers have reached mainstream adoption due to their efficient use of infrastructure and ease of deployment and automation, said Karl Robinson, director at Logicata, an AWS Managed Services provider based in London.

“AWS is the market leader for Kubernetes deployments, despite being a late comer compared to the other leading CSPs (cloud service providers),” Robinson said. “This is no surprise with the pace of development of AWS container services, which is likely to cement their position as the go-to platform to run containerized workloads.”

Fargate, a managed service, is AWS’ primary competitive advantage, according to Robinson.

“With this launch (of platform version 1.4.0), a host of new features were announced, including support for EFS (Elastic File System) endpoints, enabling containers to access shared storage in AWS, and other new features giving greater visibility into and management of the container estate,” he said. “To improve container security, all Fargate managed ephemeral storage is now encrypted by default.”

AWS first introduced AWS Fargate to run containers without managing infrastructure in late 2017. Features of the latest iteration – which are for the native Fargate platform and directly consumable by the ECS orchestrator – include support for Amazon EFS endpoints, and network performance metrics that are available in Amazon CloudWatch Container Insights.

Network stats are available in Fargate through the new task metadata endpoint version 4, according to a blog post by Massimo Re Ferre, principal developer advocate at AWS. In addition, the availability zone attribute is available in the task metadata, the Fargate agent is replacing the ECS Agent, and task elastic network interfaces also support jumbo frames for improved networking efficiency. Containerd also has replaced Docker as the container runtime.

Fargate tasks now have a single 20-GB ephemeral volume, a change that applies both to ECS tasks and Amazon EKS pods running on Fargate, and Fargate tasks now support the CAP_SYS_PTRACE Linux capability across all available Fargate platform versions.

Robinson also noted AWS’ March launch of Bottlerocket to further simplify container deployment and improve uptime. Bottlerocket isa new open-source, Linux-based operating system purpose-built to run containers.

“AWS also simplified EKS cluster creation and management via the AWS Console, while slashing EKS pricing by 50 percent,” Robinson said.

Amazon Kendra

Amazon Kendra is an enterprise search service powered by ML that uses natural language processing to perform more efficient and useful queries across an organization’s data silos and get precise answers.

AWS announced the GA of Amazon Kendra in May after launching the preview version at AWS re:Invent in December. The new service requires no ML expertise and can be set up within the AWS Management Console.

Data is encrypted in transit and at rest, and organizations can index structured and unstructured data stored in different backends including file systems, applications, intranets and relational databases. The new service provides native cloud and on-premises connectors to data sources such as SharePoint, OneDrive, Salesforce, ServiceNow, Amazon Simple and Storage Service.

Amazon Kendra is optimized to understand industry-specific language from multiple sectors: information technology, healthcare and life sciences, insurance, energy, industrial, financial services, legal, media and entertainment, travel and hospitality, human resources, news, telecommunications, mining, food and beverage, and the automotive industry.

“We have a lot of hopes for that service,” Bird, of Onica, said. “We‘re implementing it at a number of customers, and I think that should be a big one. This is changing how enterprises approach the idea of search. There‘s a lot of products out there that do enterprise search, but they’re products that run on top of products that run on top of data products. Kendra kind of wraps that up. It’s that AWS promise of here’s a service that just works.”

New Amazon Macie Features

Updated ML models for more accurate detection of personally identifiable information, support for customer-defined data types, and native multi-account management with AWS Organizations are among new improvements rolled out in May for AmazonMacie.

First launched in 2017, Amazon Macie is AWS’ fully managed data security and privacy service that helps customers discover and protect their sensitive data in its cloud.

Jassy tweeted that customers have loved Amazon Macie as a simple and thorough way to discover and protect their sensitive data, but requested it be less expensive to use at scale.

“How’s 80-90% less expensive?” Jassy tweeted in May. “That’s what we delivered today after months of hard work + invention.”

Along with the new enhancements, AWS expanded Amazon Macie’s availability to 17 AWS cloud regions.

Contact Lens

Now generally available, Contact Lens provides ML-powered contact center analytics for Amazon Connect, AWS’ cloud-based contact center service that’s designed to make it easier for organizations to deliver better customer service at lower costs.

AWS introduced Amazon Connect in 2017, and parent company Amazon.com uses it for its own customer service.

“Amazon Connect continues growing quickly b/c people love getting scale/perf/cost structure http://Amazon.com has for its call center tech, and b/c Connect keeps innovating fast. Next up for Connect: Contact Lens (ML-powered analysis of CS calls) #AWS,” Jassy tweeted Thursday.

Contact Lens automatically transcribes voice conversations between customers and customer service agents. It allows contact centers to search those transcripts and easily understand the reasons for customer calls and the sentiments, trends and compliance risks of those conversations. It helps identify important customer feedback and issues, and train agents so that successful customer interactions can be repeated, according to AWS. The new analytics features are accessible with a few clicks and don’t require coding experience.

Contact Lens also allows for the redaction of sensitive customer data – such as customers’ names, addresses, credit card details and social security numbers -- from the call audio recordings and transcripts to help keep that data secure.

An AWS blog post last week gave an example of a recent use case of Contact Lens, citing an organization that realized its customers were having trouble completing payments on its website. It used Contact Lens to search for calls in which customers mentioned the issue, allowing it to quantify the issue’s severity and complete an analysis.

Contact Lens is available in AWS’ U.S. West (Oregon), U.S. East (N. Virginia), Europe (London), Europe (Frankfurt), Asia Pacific (Singapore), Asia Pacific (Tokyo) and Asia Pacific (Sydney) cloud regions.