AWS Week in Review – October 31, 2022

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No tricks, just treats in this weekly roundup of news and announcements. Let’s switch our AWS Management Console into dark mode and dive right into it.

Last Week’s Launches
Here are some launches that got my attention during the previous week:

AWS Local Zones in Hamburg and Warsaw now generally available – AWS Local Zones help you run latency-sensitive applications closer to end users. The AWS Local Zones in Hamburg, Germany, and Warsaw, Poland, are the first Local Zones in Europe. AWS Local Zones are now generally available in 20 metro areas globally, with announced plans to launch 33 additional Local Zones in metro areas around the world. See the full list of available and announced AWS Local Zones, and learn how to get started.

Amazon SageMaker multi-model endpoint (MME) now supports GPU instances – MME is a managed capability of SageMaker Inference that lets you deploy thousands of models on a single endpoint. MMEs can now run multiple models on a GPU core, share GPU instances behind an endpoint across multiple models, and dynamically load and unload models based on the incoming traffic. This can help you reduce costs and achieve better price performance. Learn how to run multiple deep learning models on GPU with Amazon SageMaker multi-model endpoints.

Amazon EC2 now lets you replace the root Amazon EBS volume for a running instance – You can now use the Replace Root Volume for patching features in Amazon EC2 to replace your instance root volume using an updated AMI without needing to stop the instance. This makes patching of the guest operating system and applications easier, while retraining the instance store data, networking, and IAM configuration. Check out the documentation to learn more.

AWS Fault Injection Simulator now supports network connectivity disruption – AWS Fault Injection Simulator (FIS) is a managed service for running controlled fault injection experiments on AWS. AWS FIS now has a new action type to disrupt network connectivity and validate that your applications are resilient to a total or partial loss of connectivity. To learn more, visit Network Actions in the AWS FIS user guide.

Amazon SageMaker Automatic Model Tuning now supports Grid Search – SageMaker Automatic Model Tuning helps you find the hyperparameter values that result in the best-performing model for a chosen metric. Until now, you could choose between random, Bayesian, and hyperband search strategies. Grid search now lets you cover every combination of the specified hyperparameter values for use cases in which you need reproducible tuning results. Learn how Amazon SageMaker Automatic Model Tuning now supports grid search.

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

Other AWS News
Here are some additional news items that you may find interesting:

Celebrating over 20 years of AI/ML innovation – On October 25, we hosted the AWS AI/ML Innovation Day. Bratin Saha and other leaders in the field shared the great strides we have made in the past and discussed what’s next in the world of ML. You can watch the recording here.

AWS open-source news and updates – My colleague Ricardo Sueiras writes this weekly open-source newsletter in which he highlights new open-source projects, tools, and demos from the AWS Community. Read edition #133 here.

Upcoming AWS Events
Check your calendars and sign up for these AWS events:

AWS re:Invent is only 4 weeks away! Join us live in Las Vegas from November 28–December 2 for keynote announcements, training and certification opportunities, access to 1,500+ technical sessions, and much more. Seats are still available to reserve, and walk-ups are available onsite. You can also join us online to watch live keynotes and leadership sessions.

If you are into machine learning like me, check out the ML attendee guide. AWS Machine Learning Hero Vinicius Caridá put together recommended sessions and tips and tricks for building your agenda. We also have attendee guides on additional topics and industries.

On November 2, there is a virtual event for building modern .NET applications on AWS. You can register for free.

On November 11–12, AWS User Groups in India are hosting the AWS Community Day India 2022, with success stories, use cases, and much more from industry leaders. Sign up for free to join this virtual event.

That’s all for this week. Check back next Monday for another Week in Review!

— Antje

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Sysinternals Updates: Process Explorer v17.0, Handle v5.0, Process Monitor v3.92 and Sysmon v14.11, (Sun, Oct 30th)

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Sysinternals tools updates have been released for

Make sure to update sysmon, as it includes a bug fix.

I like the update to the Handles and DLLs view: it's multitab now, making it easier to switch (unless you are used to the control keys to switch).

Didier Stevens
Senior handler
Microsoft MVP
blog.DidierStevens.com

(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.

Quickie: CyberChef & Microsoft Script Decoding, (Sat, Oct 29th)

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This week I discovered a CyberChef operation I didn't know existed, but I'm quite familiar with the algorythm: "Microsoft Script Decoder" (it's been there at least since 2017).

JScript and VBScript scripts can be encoded, and are usually given the extensions .jse or .vbe respectively.

CyberChef can decode these scripts:

 

Didier Stevens
Senior handler
Microsoft MVP
blog.DidierStevens.com

(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.

AWS Named as a Leader in the 2022 Gartner Cloud Infrastructure & Platform Services (CIPS) Magic Quadrant for the 12th Consecutive Year

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This year, and for the twelfth consecutive year, AWS has been named as a Leader in the 2022 Magic Quadrant for Cloud Infrastructure and Platform Services (CIPS). Per Gartner, AWS is the longest-running CIPS Magic Quadrant Leader.

AWS was among the first cloud providers when we launched Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3) 16 years ago. Our APIs have been adopted by the whole industry and often copied by others.

We believe this report validates AWS’s ability to innovate and deliver the broadest and deepest set of services for cloud computing. I encourage you to read the full report to appreciate the details.

As Jeff Bezos wrote in his first letter to shareholders in 1997 (reprinted at the end of each annual letter since then), Amazon makes decisions and weighs trade-offs differently than some companies. We focus on the long-term value rather than short-term profits, we make bold rather than timid investment decisions, and most importantly, we relentlessly focus on you: our customers. As a matter of fact, 90 percent of AWS’s roadmap for new services and capabilities is directly driven by your feedback and requests.

I work with AWS service teams every day. These teams work hard to innovate on your behalf. They make bold investments to invent, build, and operate services that help you innovate and build amazing experiences for your customers. The entire team is proud to see these efforts recognized by Gartner.

Our teams closely work with the vibrant AWS Partner Network. AWS has the largest and most dynamic community, with millions of active customers every month and more than 100,000 partners from over 150 countries—with almost 70% headquartered outside the United States. There is a real network effect when you use AWS.

The Magic Quadrant for CIPS, showing Amazon Web Services as a leader.

The full Gartner report has details about the features and factors they reviewed. It explains the methodology used and the results. This report can serve as a guide when choosing a cloud provider that helps you innovate on behalf of your customers.

— seb

Gartner, Magic Quadrant for Cloud Infrastructure and Platform Services, 19 October 2022, Raj Bala, et. al.


The Magic Quadrant graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from AWS.

Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

 

Automated Endpoint Discovery

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Tweet VMware Skyline Advisor Pro’s Automated Endpoint Detection feature, which currently supports Aria Operations (formerly vRealize Operations), Aria Automation (Formerly vRealize Automation), and Aria Suite Lifecycle (formerly vRealize Lifecycle Manager) will automatically detect unconnected endpoints and recommend that you connect them. And, if you’re currently a Skyline customer, here’s why this feature is such a … Continued

The post Automated Endpoint Discovery appeared first on VMware Support Insider.

Upcoming Critical OpenSSL Vulnerability: What will be Affected?, (Thu, Oct 27th)

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Some here may still remember Heartbleed. Heartbleed was a critical OpenSSL vulnerability that surprised many organizations, and patching the issue was a major undertaking. Heartbleed caused OpenSSL and other open source projects to rethink how they address security issues and how they communicate with their users. OpenSSL started to pre-announce any security updates about a week ahead of time.

Introducing Amazon Neptune Serverless – A Fully Managed Graph Database that Adjusts Capacity for Your Workloads

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Amazon Neptune is a fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. With Neptune, you can use open and popular graph query languages to execute powerful queries that are easy to write and perform well on connected data. You can use Neptune for graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security.

Neptune has always been fully managed and handles time-consuming tasks such as provisioning, patching, backup, recovery, failure detection and repair. However, managing database capacity for optimal cost and performance requires you to monitor and reconfigure capacity as workload characteristics change. Also, many applications have variable or unpredictable workloads where the volume and complexity of database queries can change significantly. For example, a knowledge graph application for social media may see a sudden spike in queries due to sudden popularity.

Introducing Amazon Neptune Serverless
Today, we’re making that easier with the launch of Amazon Neptune Serverless. Neptune Serverless scales automatically as your queries and your workloads change, adjusting capacity in fine-grained increments to provide just the right amount of database resources that your application needs. In this way, you pay only for the capacity you use. You can use Neptune Serverless for development, test, and production workloads and optimize your database costs compared to provisioning for peak capacity.

With Neptune Serverless you can quickly and cost-effectively deploy graphs for your modern applications. You can start with a small graph, and as your workload grows, Neptune Serverless will automatically and seamlessly scale your graph databases to provide the performance you need. You no longer need to manage database capacity and you can now run graph applications without the risk of higher costs from over-provisioning or insufficient capacity from under-provisioning.

With Neptune Serverless, you can continue to use the same query languages (Apache TinkerPop Gremlin, openCypher, and RDF/SPARQL) and features (such as snapshots, streams, high availability, and database cloning) already available in Neptune.

Let’s see how this works in practice.

Creating an Amazon Neptune Serverless Database
In the Neptune console, I choose Databases in the navigation pane and then Create database. For Engine type, I select Serverless and enter my-database as the DB cluster identifier.

Console screenshot.

I can now configure the range of capacity, expressed in Neptune capacity units (NCUs), that Neptune Serverless can use based on my workload. I can now choose a template that will configure some of the next options for me. I choose the Production template that by default creates a read replica in a different Availability Zone. The Development and Testing template would optimize my costs by not having a read replica and giving access to DB instances that provide burstable capacity.

Console screenshot.

For Connectivity, I use my default VPC and its default security group.

Console screenshot.

Finally, I choose Create database. After a few minutes, the database is ready to use. In the list of databases, I choose the DB identifier to get the Writer and Reader endpoints that I am going to use later to access the database.

Using Amazon Neptune Serverless
There is no difference in the way you use Neptune Serverless compared to a provisioned Neptune database. I can use any of the query languages supported by Neptune. For this walkthrough, I choose to use openCypher, a declarative query language for property graphs originally developed by Neo4j that was open-sourced in 2015 and contributed to the openCypher project.

To connect to the database, I start an Amazon Linux Amazon Elastic Compute Cloud (Amazon EC2) instance in the same AWS Region and associate the default security group and a second security group that gives me SSH access.

With a property graph I can represent connected data. In this case, I want to create a simple graph that shows how some AWS services are part of a service category and implement common enterprise integration patterns.

I use curl to access the Writer openCypher HTTPS endpoint and create a few nodes that represent patterns, services, and service categories. The following commands are split into multiple lines in order to improve readability.

curl https://<my-writer-endpoint>:8182/openCypher 
-d "query=CREATE (mq:Pattern {name: 'Message Queue'}),
(pubSub:Pattern {name: 'Pub/Sub'}),
(eventBus:Pattern {name: 'Event Bus'}),
(workflow:Pattern {name: 'WorkFlow'}),
(applicationIntegration:ServiceCategory {name: 'Application Integration'}),
(sqs:Service {name: 'Amazon SQS'}), (sns:Service {name: 'Amazon SNS'}),
(eventBridge:Service {name: 'Amazon EventBridge'}), (stepFunctions:Service {name: 'AWS StepFunctions'}),
(sqs)-[:IMPLEMENT]->(mq), (sns)-[:IMPLEMENT]->(pubSub),
(eventBridge)-[:IMPLEMENT]->(eventBus),
(stepFunctions)-[:IMPLEMENT]->(workflow),
(applicationIntegration)-[:CONTAIN]->(sqs),
(applicationIntegration)-[:CONTAIN]->(sns),
(applicationIntegration)-[:CONTAIN]->(eventBridge),
(applicationIntegration)-[:CONTAIN]->(stepFunctions);"

This is a visual representation of the nodes and their relationships for the graph created by the previous command. The type (such as Service or Pattern) and properties (such as name) are shown inside each node. The arrows represent the relationships (such as CONTAIN or IMPLEMENT) between the nodes.

Visualization of graph data.

Now, I query the database to get some insights. To query the database, I can use either a Writer or a Reader endpoint. First, I want to know the name of the service implementing the “Message Queue” pattern. Note how the syntax of openCypher resembles that of SQL with MATCH instead of SELECT.

curl https://<my-endpoint>:8182/openCypher 
-d "query=MATCH (s:Service)-[:IMPLEMENT]->(p:Pattern {name: 'Message Queue'}) RETURN s.name;"
{
  "results" : [ {
    "s.name" : "Amazon SQS"
  } ]
}

I use the following query to see how many services are in the “Application Integration” category. This time, I use the WHERE clause to filter results.

curl https://<my-endpoint>:8182/openCypher 
-d "query=MATCH (c:ServiceCategory)-[:CONTAIN]->(s:Service) WHERE c.name='Application Integration' RETURN count(s);"
{
  "results" : [ {
    "count(s)" : 4
  } ]
}

There are many options now that I have this graph database up and running. I can add more data (services, categories, patterns) and more relationships between the nodes. I can focus on my application and let Neptune Serverless manage capacity and infrastructure for me.

Availability and Pricing
Amazon Neptune Serverless is available today in the following AWS Regions: US East (Ohio, N. Virginia), US West (N. California, Oregon), Asia Pacific (Tokyo), and Europe (Ireland, London).

With Neptune Serverless, you only pay for what you use. The database capacity is adjusted to provide the right amount of resources you need in terms of Neptune capacity units (NCUs). Each NCU is a combination of approximately 2 gibibytes (GiB) of memory with corresponding CPU and networking. The use of NCUs is billed per second. For more information, see the Neptune pricing page.

Having a serverless graph database opens many new possibilities. To learn more, see the Neptune Serverless documentation. Let us know what you build with this new capability!

Simplify the way you work with highly connected data using Neptune Serverless.

Danilo

Why is My Cat Using Baidu? And Other IoT DNS Oddities, (Wed, Oct 26th)

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My cat, Gluon, is having a problem. Last year, a new cat, Einstein, invaded her property, and since then, she has no longer ventured outside after some unfortunate encounters with Einstein. Gluon now spends most of her time inside doing cat stuff like grooming and sleeping; unfortunately, she has gained an unhealthy amount of weight. To help, we got her an automated cat feeder to better control her food intake. The cat feeder is sporting not just the obligatory WiFi and Cloud/App connectivity but also a camera, so it was immediately moved to our "IoT" network.