It provides a unified framework for policy creation and management across multiple clouds, simplifies policy writing, and supports popular authorization models such as role-based and attribute-based access control. Additionally, AWS has adopted a verification-guided development process to ensure the security and safety of Cedar.

The open-sourcing of the project also includes the Cedar language specification and SDK which offers libraries for authoring and validating policies and authorizing access requests. 

Amazon Verified Permissions uses Cedar to allow you to manage fine-grained permissions in your custom applications. With Amazon Verified Permissions, you can store Cedar policies centrally, have low latency with millisecond processing, and audit permissions across different applications. 

The open-source libraries of Cedar allow users to test and validate policies on their own computers before deploying them with Amazon Verified Permissions. This makes it possible to use Cedar to run applications not connected to the network, allowing users to customize the libraries to meet their needs.

Additional details on the project are available here. 

The post SD Times Open-Source Project of the Week: Cedar appeared first on SD Times.

Amazon Bedrock opens up several FMs from different providers so that AWS customers have the flexibility to choose which model would work best for their specific needs. 

This release helps users speed up the development of generative AI applications using FMs through an API, without the need to manage infrastructure. These FMs can also be privately customized using data from the user’s own organization.

Amazon Bedrock also allows customers to use AWS tools and features that they are already familiar with in order to deploy scalable and secure generative AI applications. 

Additionally, AWS announced the general availability of Amazon EC2 Inf2 instances. This release is powered by AWS Inferentia2 chips, which is intended to lower the overall cost of running generative AI workloads.

According to the company, this release also increases energy efficiency, which helps to make generative AI technology more accessible to a wider range of customers. 

Next, the new Trn1n instances run on AWS’s custom Trainium chips, and provide users with enhanced networking capabilities. This helps organizations as they work to train their generative AI models in a quick and inexpensive way. 

Lastly, AWS is offering individual developers free access to Amazon CodeWhisper in order to provide them with real-time coding assistance. 

Amazon CodeWhisper, uses generative AI under the hood so that it can provide users with code suggestions based on their comments and prior code in real-time. 

To learn more, read the blog post. 

The post Amazon’s new generative AI capabilities work to increase access to AI appeared first on SD Times.

AWS Application Composer allows for building prototypes of serverless applications and collaboratively reviewing them, generating diagrams for documentation or Wikis, and onboarding new team members to a project, according to Amazon. 

“Developers that never used serverless before, how do they know where to start? Which services do they need? How do they work together? We really wanted to make this easier. AWS Application Composer simplifies and accelerates the architecting, configuring, and building of serverless applications,” Dr. Werner Vogels, CTO of Amazon.com said at the re:Invent 2022 keynote, where the application was first previewed. 

Since the initial announcements, AWS Application Composer has received many improvements. 

One such improvement is a new feature that improves how to work with Amazon Simple Queue Service (SQS) queues. By removing the need to route requests through an AWS Lambda function and decreasing the lines of code, Amazon API Gateway resources can now be directly connected to Amazon SQS, which increases reliability.

Also, a new Change Inspector provides a visual breakdown of template changes between two resources when they are connected on the canvas. 

There have been some notable improvements to the UI since the preview. The size of resource cards has been reduced and users can zoom in and out and zoom to fit buttons to show the entire screen or the desired zoom level. 

The post AWS’ low code serverless app builder enables prototyping appeared first on SD Times.

Check here for recaps from the previous days: 

Day 1 

Day 2

Here are the latest updates from the event: 

Amazon previews CodeCatalyst

CodeCatalyst is a platform for software developers to plan, develop, collaborate on, build, and deliver applications on AWS. 

According to Amazon, the goal of this new platform is to cut down on friction throughout the development life cycle by providing a unified set of tools to do the above. 

Key features that will be included in the platform are blueprints to set up project resources, cloud-based development environments, issue management, automated build and release pipelines, dashboards, and unified search. 

AWS Step Functions now offers a distributed map

Step Functions is a visual workflow service for developers, and the new map will extend support for large-scale parallel workloads. The existing map state was limited to 40 parallel iterations, which made it challenging to process workloads with thousands of items. 

Now with the distributed map, users will be able to iterate over millions of objects, like logs, images, or .csv files. It can launch up to 10,000 parallel workflows, which is much higher than the concurrency most other AWS services offer, Amazon explained. 

AWS Application Composer available as a preview

The new tool is intended to enable easy creation of serverless applications. It will allow developers to drag and drop AWS services into an application architecture. 

It handles the infrastructure as code definitions and provides integration configuration for the services, enabling developers to focus more of their attention on developing. 

It is currently in preview, and available for free in a number of AWS regions, such as US East (both Ohio and North Virginia), US West (Oregon), Asia Pacific (Tokyo), Europe (Frankfurt and Ireland). 

Amazon EventBridge Pipes 

This new offering will allow developers to create point-to-point integrations between event producers and consumers when building event-driven applications. This removes the need to write glue code. 

While the simplest pipe option is just a source and target, there is also an optional filtering step, which will allow you to restrict the events that flow in, and an optional enrichment step to transform events before they reach the target.

The post AWS re:Invent: Amazon CodeCatalyst, AWS Step Functions distributed map, and more appeared first on SD Times.

The latest highlights from the event include: 

Amazon previews OpenSearch Serverless

This new offering will enable customers to do analytics on their data without having to manage any of the underlying infrastructure. The platform will automatically provision and scale underlying resources for the user. 

A benefit of the platform is that users don’t even have to take into account factors like frequency and complexity of queries, or the volume of data, as these can be difficult to predict in advance. 

AWS DataZone announced

The new solution will make it easy to catalog, discover, share, and govern data that is stored across AWS, on-premises, or third-party sources. 

It uses machine learning to suggest metadata for datasets and improve over time by training on the customer’s data taxonomy and preferences. 

It also enables administrators to set the appropriate privilege levels for users to ensure that engineers, data scientists, product managers, analysts, and business users can access the data they need. 

Integrations in Amazon Aurora with Amazon Redshift and Apache Spark

These two new integrations make it easier for customers to analyze their data across different storage locations, without having to move that data to do so. Typically, a user would need to perform extract, transform, and load (ETL) on that data. 

Amazon is trying to move its customers toward a zero-ETL future, and these new capabilities help bring them a step closer to that. 

“The vastness and complexity of data that customers manage today means they cannot analyze and explore it with a single technology or even a small set of tools. Many of our customers rely on multiple AWS database and analytics services to extract value from their data, and ensuring they have access to the right tool for the job is important to their success,” said Swami Sivasubramanian, vice president of Databases, Analytics, and Machine Learning at AWS. “The new capabilities announced today help us move customers toward a zero-ETL future on AWS, reducing the need to manually move or transform data between services. By eliminating ETL and other data movement tasks for our customers, we are freeing them to focus on analyzing data and driving new insights for their business—regardless of the size and complexity of their organization and data.”

Five new capabilities added to Amazon QuickSight

Amazon QuickSight is another business intelligence tool that can be used for analytics at scale. Amazon QuickSight Q, which is a natural language querying capability, now offers support for asking “why” questions, such as “why did sales increase last month?” Amazon QuickSight Q also now automatically infers and adds semantic information to data. This significantly reduces the amount of time that is spent on data preparation. 

Reporting capabilities have also been updated with the addition of paginated reports. These reports offer a formatted summary of data to share critical information. According to Amazon, with other solutions companies need to maintain multiple systems to produce paginated reports: one for analyzing the data and another for producing reports. 

 Billion-row support has been added to the calculation engine SPICE, which will allow teams to analyze larger datasets. 

And finally, QuickSight now enables customers to create, manage, and edit business intelligence assets through an API. This will allow them to accelerate migrations from legacy systems. 

Amazon Security Lake available in preview

This new service provides a centralized location for storing security data to enable customers to act on insights from that data faster.

It includes customizable data retention settings for data throughout its life cycle. It converts incoming data into the Apache Parquet format, then conforms it to the Open Cybersecurity Schema Framework standard. 

According to Amazon, most companies rely on log and event data from multiple sources, which must then be converted to a consistent format before it can be analyzed. Customers often rely on various solutions to do these analyses, which leads to duplicate data, which is time consuming and costly. 

“Amazon Security Lake lets customers of all sizes securely set up a security data lake with just a few clicks to aggregate logs and event data from dozens of sources, normalize it to conform with the OCSF standard, and make it more broadly usable so customers can take action quickly using their security tools of choice. With Amazon Security Lake, customers get superior visibility and control, with help from the largest ecosystem of security partners and solutions,” said Jon Ramsey, vice president for Security Services at AWS.

The post AWS re:Invent: OpenSearch Serverless, AWS DataZone, and more appeared first on SD Times.

According to Amazon, this service can be used for development, test, and production workloads as well as to improve database costs compared to provisioning for optimal capacity.

Neptune Serverless also allows users to accelerate the deployment of graphs for modern applications. 

Amazon stated that users can start with a small graph, and as the workload grows, Neptune Serverless will work to scale the graph databases in order to provide the necessary performance.

The service is intended to rid users of the need to manage database capacity and allow them to run graph applications without the added risk of higher costs from over-provisioning or lack of capacity from under-provisioning. 

Additionally, Neptune Serverless allows users to continue utilizing the same query languages and features that are currently available in Neptune. These include Apache, TinkerPop, Gremlin, OpenCypher, and RDF/SPARQL.

Neptune Serverless is currently available in the US East, US West, Asian Pacific, and Europe. For more information, visit the website.  

The post Amazon announces Neptune Serverless appeared first on SD Times.

Users are also enabled to provide rich insights for their own end-users where they are most needed, without server or software setup or any infrastructure management. 

Fine-Grained Visual Embedding allows developers and ISVs to embed any visuals from dashboards into their own applications using APIs. Enterprises can embed visuals into their sites using 1-Click Embedding. Finally, it offers end-users an integrated experience to access several key data visuals in order to access insights. 

The embedded visuals are updated automatically when the source data changes or whenever the visual is updated. Additionally, embedded visuals scale automatically without needing to manage servers and are optimized for high performance even on crowded pages.

Users can use Fine-Grained Visual Embedding either with 1-Click Embedding or QuickSight APIs in order to generate the embedded URL.

The 1-Click embedding feature simplifies the process for nontechnical users to generate embed code that can then be inserted directly into internal portals or public sites.

By utilizing APIs, ISVs and developers can embed visuals into their applications with secure data access from row-level security. This allows users the ability to access only their own data. 

For more detailed information, visit the documentation page.

The post AWS announces visual embedding powered by QuickSight appeared first on SD Times.

According to Amazon, there are hundreds of millions of Alexa-enabled devices in use, and building skills for Alexa provides developers with a good opportunity to engage with those customers in new ways.

“Last year, customers engaged with Alexa skills 10s of billions of times, and this is just the skill side of things, this isn’t asking for the weather or the time or things like that, but it’s the actual third party experiences that developers have built. Twenty percent of all Alexa interactions involve customers engaging with a skill,” Jeff Blankenburg, chief technology evangelist for Alexa at Amazon, told SD Times.

The company made a number of announcements at the event to help developers create better Alexa skills, including the new Alexa Learning Lab and the Skill Quality Coach.

The Alexa Learning Lab is a resource that can be accessed through the developer portal. It enables developers to try new features out and get real-time guidance on them. They can modify code, submit it, and then see the results. 

It is focused on multimodal experiences, such as things that combine voice and visuals and touch, and Blankenburg says these experiences resonate most with customers.

According to Blankenburg, early assessments showed that developers who utilized the Learning Lab were able to pass Amazon’s assessments faster and also scored higher on measurements for growth and the ability to develop skills. 

Another update, the Skill Quality Coach provides developers with a score and recommendations for improving. It learns the common attributes of successful skills from existing Alexa skills, then compares that to your skill. It then uses this information to provide you with a plan for making improvements. 

Developers are provided with a Skill Quality Score, ranging from 0 to 5, which is based on different components, such as customer experience and skill design attributes like rich multimodal and voice responses, voice model coverage, content richness and personalization, and endpoint health.  

“Developers have a lot of really great ideas about what they want to build, but when it comes to building it in a way that makes it very engaging for their customer, in a way that gets users to come back, that’s where sometimes they can just use a little tip or a hint here or there that the developer may not have been aware that that would have been a useful thing to add,” said Blankenburg.

More information about these updates can be found in Amazon’s blog post about the news. 

The post Amazon provides developers with new resources for building Alexa skills appeared first on SD Times.

This comes as a long awaited conclusion to the license battle between the two companies due to the change to the license of ElasticSearch and Kibana back in 2021. The open-source license was changed to SSPL as a result of Elastic believing customers were being misled by Amazon offering Amazon Elasticsearch Service, and that Amazon was abusing the intent of the open-source license and profiting off the project. 

Amazon has since renamed Amazon Elasticsearch Service, to Amazon OpenSearch Service. 

With this resolution, the companies hope to remove any confusion in the marketplace and provide clarity to their communities and customers.

This resolution means that there is now only one Elasticsearch and it comes from Elastic. When using Elasticsearch, regardless of it being the Elastic Cloud service in AWS, Azure, or Google Cloud, it is coming directly from the people who created the product.

According to Elastic, in the future it will be looking to collaborate more with Amazon in order to bring added ease of use to their shared customer base who use Elastic on AWS. Elastic has already seen benefits from its partnership around recent areas of investment geared towards streamlining data ingestion and making onboarding easier to Elastic Cloud on AWS.

Additionally, Elastic has announced over 20 new integrations in order to streamline data ingestion into Elastic. These include AWS FireLens, Amazon S3 Storage Lens, the Elastic Serverless Forwarder in the AWS Serverless Application Repository, Elastic and AWS Web Application Firewall, and the Elastic and AWS Network Firewall.  

Elastic Cloud has also been certified as a part of the AWS ISV Workload Migration Program. This works to support the migration of customers to Elastic Cloud on AWS and allows Elastic to simplify the migration process with onboarding guidance and migration resources.

The post Elastic and Amazon reach an agreement on trademark infringement lawsuit appeared first on SD Times.

These updates include: 

• A new Detector Library that describes the detectors that CodeGuru Reviewer uses when looking for possible defects and includes code samples for Java and Python
• New security detectors that work to detect log-injection flaws in Java and Python code 

These new features are available today in all AWS Regions where Amazon CodeGuru is offered. For more information, visit here. 

JFrog Xray updates 

DevOps company JFrog today introduced contextual analysis security capabilities in JFrog Xray, the company’s DevSecOps solution. These new features enable users to more precisely determine the threat level and relevance of common vulnerability exposures (CVEs).

The goal of this update is to create more rapid and accurately-prioritized remediation of security vulnerabilities. This provides for a holistic, automated, and scalable solution geared at finding, replacing, recovering, and prioritizing hazardous CVEs. 

“With so many vulnerabilities these days, customers need solutions that help them focus on what actually needs protection. By providing binary-level detection of each vulnerability, Xray’s contextual analysis helps developers and security teams make more informed decisions about a particular vulnerability’s impact so they can confidently and quickly execute remediation plans, while reducing overhead,” said Nati Davidi, SVP of JFrog Security. 

Sysdig and Snyk announce partnership

The unified container and cloud security company, Sysdig, and the developer security company, Snyk, today announced the integration of Sysdig Secure with Snyk Container. This combination works to cover container security from development through operations. 

According to internal testing, this allows for the elimination of 95% of vulnerability alerts using runtime intelligence from Sysdig Secure with Snyk Container. 

“For too long, developers have been tasked with the impossible: fighting the unrelenting vulnerability noise that compromises both their speed as well as their company’s overall security. Together with Sysdig, we’re now empowering millions more developers worldwide to innovate securely. We’re excited for what’s ahead as together we advance the global DevSecOps movement in 2022 and beyond,” said Peter McKay, chief executive officer at Snyk.

The post SD Times news digest: Updates announced for Amazon CodeGuru Reviewer; JFrog Xray updates; Sysdig and Snyk announce partnership appeared first on SD Times.