AWS Weekly Roundup: AWS Builder Center, Amazon Q, Oracle Database@AWS, and more (July 14, 2025)

Summer is well and truly here in the UK! I’m a bit of a summer grinch though so, unlike most people, I’m not crazy about “the glorious sun” scorching me when I’m out and about. On the upside, this provides the perfect excuse to retreat to the comfort of a well-ventilated room where I can focus on coding and curating the latest AWS releases to bring you the highlights.

I also managed to escape the heat for most of yesterday while recording an episode for the AWS Developers Podcast where the wonderful Sebastien Stormaq and Tiffany Souterre interviewed me about games development. If you haven’t discovered it yet, I highly recommend you give it a go as the episodes are full of interesting lessons and insights from not just AWS, but customers and community members who share their stories and expertise in a relaxed conversation.

Alright, ready to discover some of the new things we released last week? Here are the highlights.

AWS Builder Center
There is a new home for AWS builders and community members! AWS Builder Center is a new place where cloud builders can connect, share knowledge, and access resources to enhance their AWS journey. The platform enables users to join community programs, discover trending topics, access AWS Skill Builder courses, participate in technical challenges, and more, using a single Builder ID sign-in.

One the features that I’m personally most excited about is the Wishlist. You can now create wishes and tell AWS directly about ways to improve our products and services or share original ideas that you think could help you and your teams. You can also browse and upvote existing wishes to support any suggestions that you think should be prioritized. The AWS teams will keep an eye on this and if a wish has enough traction it may just be considered!

Read the news blog post for a quick tour through some of the most exciting features or head over to AWS Builder Center and start exploring!

AI
The world of AI keeps moving fast and changing our world, by providing new and exciting ways to do things and become more productive. Here are two releases from last week that caught my attention.

  • Amazon Q chat in the AWS Management Console can now query AWS service data – Amazon Q Developer expands its capabilities by enabling natural language queries of data stored across AWS services like S3, DynamoDB, and CloudWatch, directly from the AWS Console, Slack, Microsoft Teams, and AWS Console Mobile Application. This enhancement streamlines cloud management and troubleshooting by allowing users to access and analyze service data through conversational interfaces, with access controls managed through IAM permissions.
  • Amazon CloudWatch and Application Signals MCP servers for AI-assisted troubleshooting – AWS has released two new Model Context Protocol (MCP) servers – CloudWatch MCP and Application Signals MCP – that enable AI agents to leverage observability data for automated troubleshooting through conversational interfaces. These open-source servers allow AI assistants to analyze metrics, alarms, logs, traces, and service health data across AWS environments, streamlining incident response and root cause analysis without requiring developers to manually navigate multiple AWS consoles.

Oracle Database@AWS
It seems like yesterday when Andy Jassy announced our partnership with Oracle to create Oracle Database@AWS, a jointly offered service that runs Oracle databases on Exadata infrastructure directly within AWS data centers, providing a unified AWS-Oracle experience. Fast forward to last week and Oracle Database@AWS has reached a significant milestone with its general availability release. It is now available in US East (N. Virginia) and US West (Oregon) regions, with plans to expand to 20 additional regions globally.

In addition, VPC Lattice has added support for Oracle Database@AWS enabling seamless connectivity between applications in VPCs and on-premises environments to Oracle database networks. The integration simplifies network management and provides secure access from Oracle Database@AWS to AWS services like Amazon S3 and Amazon Redshift, without requiring complex networking setup.

So if you’re looking to migrate your Oracle database workloads, now is a great time to explore Oracle Database@AWS as it offers a compelling path forward with minimal modifications required.

Additional highlights
Here are some other releases that I think many people will be happy about.

  • AWS Config now supports 12 new resource types – AWS Config has expanded its monitoring capabilities with support for 12 new resource types across services including BackupGateway, CloudFront, EntityResolution, Bedrock, and more. These additions are automatically tracked if you have enabled recording for all resource types, enhancing your ability to discover, assess, and audit AWS resources.
  • Amazon SageMaker Studio now supports remote connections from Visual Studio Code – Amazon SageMaker Studio now supports remote connections from Visual Studio Code, allowing developers to use their familiar VS Code setup while leveraging SageMaker’s scalable compute resources for AI development.
  • AWS Network Firewall: Native AWS Transit Gateway support in all regions – AWS Network Firewall now offers native integration with AWS Transit Gateway across all supported regions, enabling direct attachment and simplified traffic inspection between VPCs and on-premises networks. This integration eliminates the need for managing dedicated VPC subnets and route tables while providing multi-AZ redundancy for improved security and reliability.

Upcoming AWS Events
AWS Summit New York – this is definitely one to watch…literally! Registrations are closed due to capacity but you can tune in to watch live all the announcements and launches! No spoilers, but, trust me, there are a quite a few exciting things in store, so make sure to check it out.

AWS Gen AI LoftsAWS Gen AI Lofts are multi-day events offering hands-on workshops, expert guidance, and networking opportunities for developers and business leaders looking to explore or advance their generative AI journey. These events are hosted across multiple global locations including San Francisco, Berlin, Dubai, Dublin, Bengaluru, Manchester, Paris, and Tel Aviv, providing accessible opportunities to accelerate your generative AI adoption.

And that’s it for this week! Come back next Monday for more highlights and keep your AWS knowledge up to date as we cover the latest releases.

Matheus Guimaraes | @codingmatheus

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New White House cyber executive order pushes rules as code

In an era characterized by escalating cybersecurity threats, rapidly evolving technological landscapes, and heightened regulatory demands, organizations face significant pressure to modernize their Governance, Risk, and Compliance (GRC) practices. The federal government is also pivoting toward automation, with Policy-as-Code (PaC) becoming a foundational element in modern cybersecurity governance and compliance.

A critical driver accelerating this urgency is a recent executive order that explicitly underscores robust cybersecurity frameworks, continuous monitoring, and adaptive compliance strategies. In response, organizations must move toward adopting innovative solutions such as Policy-as-Code methodologies.

Aligning with the cyber EO

In June, the White House issued an executive order that directs the National Institute of Standards and Technology, the Cybersecurity and Infrastructure Security Agency, and the Office of Management and Budget to launch a pilot within one year that expresses federal cyber policy in a machine‑readable format. The same section instructs the Federal Acquisition Regulation Council to revise procurement rules so that by January 2027, agencies may buy only consumer IoT products whose Cyber Trust Mark can be parsed automatically. 

This isn’t just a technical experiment: It’s a blueprint for the future of cyber governance. This is a decisive endorsement of automation-based compliance and signals a governmentwide expectation that policy implementation must be verifiable, scalable, and code-driven.

These deadlines extend beyond federal departments. Any company that sells software, cloud services, or connected devices to the public sector will soon need to prove that its security controls are written and enforced through machine‑readable rules. The fastest and most reliable way to supply that proof is Policy-as-Code. Teams that move early will gain an advantage when the new rules shape purchasing decisions. Teams that wait risk a backlog of manual controls and a shrinking share of government business.

What is Policy-as-Code?

Policy-as-Code refers to the practice of translating governance, risk management, and compliance policies into machine-readable formats by leveraging automation, and creating a more structured, dynamic, and scalable compliance environment. Policy-as-Code removes ambiguity from interpretation and puts security policies on equal footing with infrastructure and application logic. The result is a proactive compliance governance that scales as fast as today’s threats. 

The Risk Management Framework (RMF) has long provided structured guidelines for organizations to categorize, select, implement, assess, authorize, and continuously monitor their information systems. However, traditional RMF processes often rely heavily on manual efforts, making them less responsive and increasingly prone to errors in today’s fast-paced digital environment. 

As of today:

  • Release velocity has accelerated: Development teams merge code many times each day; manual assessment packages cannot keep pace.
  • Architectural complexity has grown: Hybrid clouds, containers, edge devices, and software‑as‑a‑service platforms create connections too dense for spreadsheet mapping.
  • Regulatory concurrency has intensified: Programs must show conformance with FISMA, FedRAMP, CMMC, the Secure Software Development Framework, multiple state privacy laws, and sector‑specific rules at the same time.

Policy-as-Code resolves these gaps because rules run continuously, update quickly, and leave a clear evidence trail. 

Strategic benefits of implementing Policy-as-Code

Organizations adopting Policy-as-Code experience several transformative benefits, positioning themselves advantageously within a highly competitive regulatory environment:

  • Risk reduction: Automated enforcement minimizes risks associated with human error, improving compliance accuracy and reducing vulnerabilities.
  • Audit efficiency: Immutable logs replace screenshots, shared drives, and labor‑intensive walk‑throughs.
  • Operational efficiency: Automating policy enforcement streamlines processes, significantly reducing the administrative burden and enabling teams to focus on strategic tasks rather than routine compliance checks.
  • Regulatory agility: When NIST updates a control catalog, teams change one file and push the update across every environment with a pull request.
  • Enhanced security posture: Real-time monitoring capabilities bolster an organization’s security posture, swiftly identifying and addressing potential threats or breaches.
  • Cost savings: By reducing the manual effort needed for compliance monitoring and enforcement, Policy-as-Code can lead to considerable cost reductions over time.
  • Greater resilience: Codified governance reduces ambiguity and enhances organizational readiness under stress.
Making it Work: practical steps for effective implementation

To effectively adopt Policy-as-Code and maximize its benefits, organizations should consider the following structured approach:

  • Comprehensive policy mapping and evaluation: Begin by evaluating every policy, regulation and policy applicable to your organization, map all the frameworks (e.g. NIST SP 800-53, ISO/IEC 27002 etc.) applicable to your organization, and assign a unique identifier to each of the mapped control. This mapping forms the foundation for robust automation.
  • Select an open declarative machine-readable language: Choose a well‑supported machine-readable format — like NIST’s Open Security Controls Assessment Language (OSCAL) or Open Policy Agent (OPA) — that integrates with existing infrastructure‑as‑code (IaC), container orchestration, and pipeline tools.
  • Convert prose to machine‑readable schemas: Translate Word and PDF controls into structured formats such as OSCAL.
  • Integration into development pipelines: Evaluate and deploy specialized automation platforms capable of integrating seamlessly into existing DevSecOps workflows and lifecycle. These platforms should offer real-time compliance verification, automated remediation capabilities, and ensure continuous validation of compliance at every stage of the software development process, from initial coding through deployment and operation.
  • Ongoing monitoring and continuous improvement: Implement robust tools for continuous compliance monitoring. Regularly review and update policy logic to accommodate evolving regulatory landscapes and cybersecurity threats.
  • Automate evidence collection: Connect cloud APIs, container scanners, and endpoint telemetry to a central repository so evidence accrues automatically.
  • Training and capacity building: Invest in targeted training programs to equip your teams with the necessary technical and conceptual understanding of Policy-as-Code methodologies and Git workflows, and teach developer teams regulatory vocabulary.
  • Cultural alignment and leadership support: Actively cultivate a culture that values compliance automation and proactive risk management. Secure buy-in and sustained support from senior leadership to ensure smooth adoption and integration.
  • Pilot and iterate: Begin with a high-priority control (e.g., encryption at rest) and run a focused pilot. Measure its effectiveness, gather stakeholder feedback, and iterate. Success here builds momentum.
  • Inform and measure impact: Codified controls should feed into your broader risk dashboards and compliance reporting mechanisms, track policy coverage, mean time to remediation, audit hours saved, and defects prevented. Share results with executive stakeholders.
The road ahead

The future of cybersecurity governance clearly points toward increased automation, dynamic regulatory adaptation, and highly responsive compliance frameworks. Policy-as-Code is not merely a temporary trend but a fundamental shift in how organizations approach GRC. Soon, federal contracts may require delivery of not only human-readable SSPs but also machine-verifiable compliance packages. Audits may involve running scripts instead of reviewing PDFs. And AI-powered governance engines will cross-check deployments against codified policies in real time.

The EO’s emphasis on rules-as-code is just the beginning. The EO also sets timelines for managing AI vulnerabilities and adopting post‑quantum cryptography. Agencies must publish an AI vulnerability dataset by Nov. 1 and must transition to quantum‑resistant encryption by 2030. 

The clock is ticking. Agencies must pilot rules as code by June 2026, and suppliers must attach machine-readable security labels by January 2027. Organizations that translate policy into executable pipelines now will close vulnerabilities faster, cut assessment costs, and enter bid rooms as trusted partners. Those that wait will face manual backlogs, increased expenses, and shrinking market share once the grace period ends. Policy-as-Code is no longer experimental, but an operational and compliance imperative that will distinguish tomorrow’s security-ready organizations from everyone else.

The future of cyber and AI governance won’t be documented; it will be deployed!

Ibrahim Waziri Jr. is a principal security product manager in Microsoft’s Cybersecurity, Cloud, AI & Trust Engineering Team, a cybersecurity fellow at New America, and an adjunct professor of cybersecurity at Marymount University.

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Experimental Suspicious Domain Feed, (Sun, Jul 13th)

We have had a "newly registered domain" feed for a few years. This feed pulls data from ICANN's centralized zone data service (https://czds.icann.org) and TLS certificate transparency logs.

The ICANN CZDS is a good start, but it only offers data from top-level domains collaborating with ICANN. Missing are in particular country-level domains. Country-level zone files can be hard to come by, so we use TLS certificate transparency logs as a "cheap" alternative. Pretty much all domain registrars will, by default, create a "parked" website, and with that, they will make a certificate. Even if they do not, any halfway self-respecting phishing site will use TLS and register a certificate with a public certificate authority at one point. The TLS certificate transparency logs also help capture older domains.

Each day, we capture around 250,000 new domains using this system. But of course, we want to know which domains are used for malicious purposes. However, as the sample below shows, there are a lot of "odd" domain names.

domainname
jgcinversiones.com
h20manager.net
1sbrfreebet.com
stability.now
mdskj.top
internationalone19.com
clistrict196.org
agenteinsider.com
720airpano.com
dhofp.tax
bos228btts.lol
japansocialmarketing.org
mummyandimedia.com
1dyzfd.buzz
oollm.shop
snapztrailk.store
perumice.com
nrnmy.sbs
commaexperts.com
softfragments.com

So I searched for some commonly used criteria to identify "bad" domain names, and found these:

  • A domain name is very short or very long
  • The entropy of the domain name (is it just random characters?)
  • Does it contain a lot of numbers or hyphens?
  • Is it an international domain name, and if so, is it valid? Does it mix different scripts (=languages)?
  • Does it contain keywords like "bank" or "login" that are often used with phishing sites, or brand names like "Apple" or "Google"?

We have now added a score to each domain name that can be used to rank them based on these criteria. You can find a daily report here, and the score was added to our "recentdomain" API feed. This is experimental, and the exact algorithm we use for the score will change over time.

We used to have an "old" supicous domain feed that was mostly based on correlating a few third party feeds, but over time these feeds went away or became commercial and we could no longer use them.

Feedback is very welcome.


Johannes B. Ullrich, Ph.D. , Dean of Research, SANS.edu
Twitter|

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

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Securing Data in the AI Era

The 2025 Data Risk Report: Enterprises face potentially serious data loss risks from AI-fueled tools. Adopting a unified, AI-driven approach to data security can help.
As businesses increasingly rely on cloud-driven platforms and AI-powered tools to accelerate digital transformation, the stakes for safeguarding sensitive enterprise data have reached unprecedented levels. The Zscaler ThreatLabz

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UK arrests four for cyberattacks on major British retailers

Three teenagers and a 20-year-old woman were arrested Thursday by the U.K.’s National Crime Agency for their alleged role in cyberattacks on major retailers Marks & Spencer (M&S), Co-op, and Harrods.

The arrests, comprising British and Latvian nationals, followed sustained investigations into attacks that crippled the retailers’ operations. The NCA’s National Cyber Crime Unit detained all four at their homes and seized their electronic devices.

“Since these attacks took place, specialist NCA cybercrime investigators have been working at pace and the investigation remains one of the Agency’s highest priorities,” Deputy Director Paul Foster, head of the NCA’s National Cyber Crime Unit, said in a statement. “Today’s arrests are a significant step in that investigation but our work continues, alongside partners in the U.K. and overseas, to ensure those responsible are identified and brought to justice.”

The particular incidents that led to these arrests occurred in April, with attackers crippling the online services of Marks & Spencer, a popular retailer in the U.K. The company’s online sales channels were halted, contactless payments and click-and-collect options were disrupted, and in-store product availability suffered. The attack also resulted in the theft of customer information, including names, email addresses, and postal data. Recovery efforts began in June, with the retailer eventually restoring sections of its online business across the U.K.

Industry experts and law enforcement agencies in several countries have attributed the attacks to a cybercriminal group known as Scattered Spider. The loose-knit collective has infiltrated more than 100 businesses since 2022, hitting organizations in hospitality and gaming, manufacturing, technology and cloud services, telecommunications, retail, manufacturing, food production, insurance and financial services, media, apparel, business process outsourcing, health care, transportation and aviation, according to researchers. 

The group is allegedly also behind cyberattacks on several U.S.-based insurance companies, United Natural Foods, and aviation companies WestJet and Hawaiian Airlines

The group is an offshoot of The Com, a much larger grassroots network of more than 1,000 people responsible for a vast catalog of crimes, including social engineering, crypto theft, phishing, SIM swapping, extortion, sextortion, swatting, kidnapping and murder. 

All four arrested are being held on suspicion of violating the U.K.’s Computer Misuse Act, blackmail, money laundering and participating in the activities of an organized crime group.

The post UK arrests four for cyberattacks on major British retailers appeared first on CyberScoop.

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New Amazon EC2 P6e-GB200 UltraServers accelerated by NVIDIA Grace Blackwell GPUs for the highest AI performance

Today, we’re announcing the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P6e-GB200 UltraServers, accelerated by NVIDIA GB200 NVL72 to offer the highest GPU performance for AI training and inference. Amazon EC2 UltraServers connect multiple EC2 instances using a dedicated, high-bandwidth, and low-latency accelerator interconnect across these instances.

The NVIDIA Grace Blackwell Superchips connect two high-performance NVIDIA Blackwell tensor core GPUs and an NVIDIA Grace CPU based on Arm architecture using the NVIDIA NVLink-C2C interconnect. Each Grace Blackwell Superchip delivers 10 petaflops of FP8 compute (without sparsity) and up to 372 GB HBM3e memory. With the superchip architecture, GPU and CPU are colocated within one compute module, increasing bandwidth between GPU and CPU significantly compared to current generation EC2 P5en instances.

With EC2 P6e-GB200 UltraServers, you can access up to 72 NVIDIA Blackwell GPUs within one NVLink domain to use 360 petaflops of FP8 compute (without sparsity) and 13.4 TB of total high bandwidth memory (HBM3e). Powered by the AWS Nitro System, P6e-GB200 UltraServers are deployed in EC2 UltraClusters to securely and reliably scale to tens of thousands of GPUs.

EC2 P6e-GB200 UltraServers deliver up to 28.8 Tbps of total Elastic Fabric Adapter (EFAv4) networking. EFA is also coupled with NVIDIA GPUDirect RDMA to enable low-latency GPU-to-GPU communication between servers with operating system bypass.

EC2 P6e-GB200 UltraServers specifications
EC2 P6e-GB200 UltraServers are available in sizes ranging from 36 to 72 GPUs under NVLink. Here are the specs for EC2 P6e-GB200 UltraServers:

UltraServer type GPUs
GPU
memory (GB)
vCPUs Instance memory
(GiB)
Instance storage (TB) Aggregate EFA Network Bandwidth (Gbps) EBS bandwidth (Gbps)
u-p6e-gb200x36 36 6660 1296 8640 202.5 14400 540
u-p6e-gb200x72 72 13320 2592 17280 405 28800 1080

P6e-GB200 UltraServers are ideal for the most compute and memory intensive AI workloads, such as training and inference of frontier models, including mixture of experts models and reasoning models, at the trillion-parameter scale.

You can build agentic and generative AI applications, including question answering, code generation, video and image generation, speech recognition, and more.

P6e-GB200 UltraServers in action
You can use EC2 P6e-GB200 UltraServers in the Dallas Local Zone through EC2 Capacity Blocks for ML. The Dallas Local Zone (us-east-1-dfw-2a) is an extension of the US East (N. Virginia) Region.

To reserve your EC2 Capacity Blocks, choose Capacity Reservations on the Amazon EC2 console. You can select Purchase Capacity Blocks for ML and then choose your total capacity and specify how long you need the EC2 Capacity Block for u-p6e-gb200x36 or u-p6e-gb200x72 UltraServers.

Once Capacity Block is successfully scheduled, it is charged up front and its price doesn’t change after purchase. The payment will be billed to your account within 12 hours after you purchase the EC2 Capacity Blocks. To learn more, visit Capacity Blocks for ML in the Amazon EC2 User Guide.

To run instances within your purchased Capacity Block, you can use AWS Management Console, AWS Command Line Interface (AWS CLI) or AWS SDKs. On the software side, you can start with the AWS Deep Learning AMIs. These images are preconfigured with the frameworks and tools that you probably already know and use: PyTorch, JAX, and a lot more.

You can also integrate EC2 P6e-GB200 UltraServers seamlessly with various AWS managed services. For example:

  • Amazon SageMaker Hyperpod provides managed, resilient infrastructure that automatically handles the provisioning and management of P6e-GB200 UltraServers, replacing faulty instances with preconfigured spare capacity within the same NVLink domain to maintain performance.
  • Amazon Elastic Kubernetes Services (Amazon EKS) allows one managed node group to span across multiple P6e-GB200 UltraServers as nodes, automating their provisioning and lifecycle management within Kubernetes clusters. You can use EKS topology-aware routing for P6e-GB200 UltraServers, enabling optimal placement of tightly coupled components of distributed workloads within a single UltraServer’s NVLink-connected instances.
  • Amazon FSx for Lustre file systems provide data access for P6e-GB200 UltraServers at the hundreds of GB/s of throughput and millions of input/output operations per second (IOPS) required for large-scale HPC and AI workloads. For fast access to large datasets, you can use up to 405 TB of local NVMe SSD storage or virtually unlimited cost-effective storage with Amazon Simple Storage Service (Amazon S3).

Now available
Amazon EC2 P6e-GB200 UltraServers are available today in the Dallas Local Zone (us-east-1-dfw-2a) through EC2 Capacity Blocks for ML. For more information, visit the Amazon EC2 pricing page.

Give Amazon EC2 P6e-GB200 UltraServers a try in the Amazon EC2 console. To learn more, visit the Amazon EC2 P6e instances page and send feedback to AWS re:Post for EC2 or through your usual AWS Support contacts.

Channy

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