aws·Mar 19, 2026·4 min readCurated summary

20 years in the AWS Cloud – how time flies! | Amazon Web Services

AWS’s 20-year evolution reflects a shift from foundational cloud infrastructure to managed services for AI, automation, and agentic applications. The author argues that AWS’s most important innovations come from responding to customer needs rather than chasing every fashionable technology. Personal experiences with AWS and its community illustrate how cloud services have enabled developers, researchers, and businesses to pursue previously impractical projects. ## AWS’s Impact on the Author’s Career - The author met AWS blogger Jeff Barr in Seoul in 2006, shortly after Amazon began promoting API-based services. - Inspired by Barr, the author began building APIs for third-party developers and later used AWS for large-scale academic research. - The author’s company became one of Korea’s earliest AWS customers in 2014. - AWS helped make advanced computing capabilities accessible to individuals, startups, researchers, and enterprises. ## Innovation Driven by Customer Needs - AWS has grown to more than 240 cloud services and launches thousands of features each year. - The author highlights the importance of distinguishing genuine technological trends from temporary distractions. - AWS’s evolution spans deep learning, generative AI based on large language models, and today’s agentic AI. - The central innovation principle is to listen to customers and solve their most important problems, rather than adopting technology simply because it is fashionable. ## Major AWS Milestones The article recalls foundational services from AWS’s first decade, including: - Amazon S3 and EC2 in 2006 - Amazon RDS and VPC in 2009 - DynamoDB and Redshift in 2012 - WorkSpaces and Kinesis in 2013 - AWS Lambda in 2014 - AWS IoT in 2015 ## Containers and Serverless Databases - Amazon ECS, launched in 2014, simplified running containers across managed EC2 clusters. - Amazon EKS later added managed Kubernetes, while AWS Fargate enabled serverless container deployment. - Amazon Aurora provided highly available relational databases at scale. - Aurora Serverless evolved from version 1 to version 2, which can scale down to zero. - Aurora DSQL, launched in 2025, extends the serverless model to distributed SQL workloads requiring continuous availability. ## Making Machine Learning More Accessible - Amazon SageMaker, launched in 2017, provided an end-to-end managed environment for building, training, and deploying ML models. - In 2024, AWS introduced the next-generation SageMaker platform for data, analytics, and AI, along with SageMaker AI for model development and deployment. - AWS also developed specialized hardware: - Inferentia for low-latency inference - Trainium for high-performance AI training - Trainium3 UltraServers for improved economics in generative AI workloads ## Improving Cloud Price Performance - EC2 A1 instances introduced AWS Graviton processors based on Arm architecture. - Later Graviton generations expanded price-performance benefits across services such as ECS, EKS, Lambda, RDS, ElastiCache, EMR, and OpenSearch Service. - More than 90,000 customers have reportedly adopted Graviton-based infrastructure. ## Hybrid Cloud and Edge Computing - AWS Outposts brings AWS infrastructure and services into customer data centers and edge locations. - Available configurations range from 1U and 2U servers to 42U racks and multi-rack deployments. - Customers use Outposts for low-latency access, local processing, data residency, and applications with on-premises dependencies. ## Generative AI and Agentic Development - Amazon Bedrock provides access to multiple AI models and managed capabilities for building secure generative AI applications. - Bedrock AgentCore extends the platform to deploying and operating agents at scale. - More than 100,000 customers use Bedrock for personalization, workflow automation, and insight generation. - Amazon CodeWhisperer evolved into Amazon Q Developer, adding conversational assistance, project-based generation, and code transformation. - The service later evolved into Kiro, an agentic development tool centered on spec-driven development and autonomous coding tasks. - AWS expanded model choice through Amazon Titan and Amazon Nova, including services for building frontier models and browser-automation agents. AWS’s history suggests that the strongest path forward is to use AI and cloud services to address concrete customer and business challenges. The author’s examples present AWS as an evolving platform whose value comes not only from individual launches, but from steadily making advanced infrastructure, machine learning, and autonomous software development more accessible.

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Database DesignMachine LearningKubernetesAWS+4

aws·Mar 18, 2026·2 min readCurated summary

Our First 2026 Heroes Cohort Is Here! | Amazon Web Services

AWS has announced its first 2026 Heroes cohort, recognizing Maurizio, Ray Goh, and Sheyla Leacock for combining technical expertise with community leadership. Their work spans cloud architecture, generative AI, machine learning, and cybersecurity, while emphasizing mentorship, education, and meaningful human connections. Together, they demonstrate how technology leaders can expand access to skills and strengthen communities globally. ## Maurizio – Pignola, Italy - CTO and organizer of the AWS User Group Basilicata. - Has spent more than a decade developing cloud communities and technology ecosystems in areas where they previously did not exist. - Founded an international technology conference in a small mountain village, connecting global experts with local developers. - Covers topics including cloud architecture, DevOps, and web scaling, alongside creative networking opportunities. - Mentors children, university students, and professionals transitioning into cloud careers. - Combines technical leadership with inclusive, cross-generational community building. ## Ray Goh – Singapore - AI and machine learning community leader involved in AWS programs since 2018. - Founded The Gen-C in 2024, offering public library workshops on generative AI, LLM fine-tuning, and AWS AI agents. - Has spoken at major AWS events and contributed to the AWS Machine Learning Blog. - Led DBS Bank’s AWS DeepRacer initiative, which trained more than 3,100 employees. - Trained over 1,300 ASEAN students in LLM techniques in 2025. - Supports skills-based programs teaching AI and machine learning to women, children, and young people. ## Sheyla Leacock – Panama City, Panama - IT security professional, mentor, technical writer, and international speaker. - Leads the AWS User Group in Panama and participates in AWS Community Days and regional meetups. - Has spoken at AWS Summits, AWS re:Invent PeerTalk sessions, and more than 20 international conferences. - Publishes educational content focused on AWS cloud computing and cybersecurity. - Works with universities as a guest lecturer to help develop future technology and security professionals. - Strengthens the cloud and cybersecurity ecosystem through education, knowledge sharing, and community leadership. The new cohort highlights the broader impact of community-driven technology leadership. Readers can visit the AWS Heroes webpage to learn more about the program or connect with a Hero.

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AIDatabase DesignMachine LearningAWS+4

aws·Mar 16, 2026·3 min readCurated summary

AWS Weekly Roundup: Amazon S3 turns 20, Amazon Route 53 Global Resolver general availability, and more (March 16, 2026) | Amazon Web Services

Amazon S3 marked its 20th anniversary with major milestones in scale, performance, and cost reduction, while AWS introduced account regional namespaces for improved bucket-name control. The week’s featured launch was the general availability of Amazon Route 53 Global Resolver, providing secure, globally accessible DNS resolution across 30 AWS Regions. Other updates covered stateful AI agent infrastructure, Windows Server 2025, simplified AWS identity access, and reusable Redshift ingestion templates. ## Amazon S3 Reaches 20 Years - Launched publicly on March 14, 2006, S3 has grown from object storage into a foundational cloud service. - As of March 2026, it stores: - More than 500 trillion objects - Hundreds of exabytes of data - Over 200 million requests per second globally - Storage prices have fallen by approximately 85% since launch, to just over $0.02 per gigabyte. - New account regional namespaces let organizations reserve bucket names within their own account namespace by adding an account-specific suffix. - Adoption can be enforced with IAM and AWS Organizations service control policies using the `s3:x-amz-bucket-namespace` condition key. ## Route 53 Global Resolver Becomes Generally Available - Amazon Route 53 Global Resolver is an internet-reachable, anycast DNS resolver for authorized clients anywhere. - It is available across 30 AWS Regions and supports IPv4 and IPv6 DNS queries. - It resolves: - Public internet domains - Private domains associated with Route 53 private hosted zones - Security features include filtering for malicious, unsafe, DNS tunneling, and Domain Generation Algorithm (DGA) domains. - General availability adds protection against Dictionary DGA threats. - Centralized DNS query logging is also included. ## Additional AWS Service Updates - **Bedrock AgentCore Runtime** - Adds stateful MCP server support through the `Mcp-Session-Id` header. - Dedicated microVMs isolate each user session and preserve context across interactions. - MCP servers can use elicitation, sampling, and progress notifications in addition to resources, prompts, and tools. - **Amazon WorkSpaces** - Adds Windows Server 2025 bundles for WorkSpaces Personal and WorkSpaces Core. - Security features include TPM 2.0, UEFI Secure Boot, Credential Guard, HVCI, Secured-core server, and DNS-over-HTTPS. - Existing Windows Server 2016, 2019, and 2022 bundles remain supported. - **AWS Builder ID** - Adds GitHub and Amazon as sign-in options alongside Google and Apple. - Users can access AWS Builder Center, Training and Certification, and Kiro without maintaining separate credentials. - **Amazon Redshift** - Introduces reusable templates for `COPY` operations. - Templates centralize frequently used parameters, improve consistency, and automatically apply future updates to subsequent loads. - The feature is available in commercial and AWS GovCloud Regions. ## Upcoming AWS Events - AWS Summits are scheduled for Paris, London, and Bengaluru. - AWS Community Days are planned in Pune, San Francisco, and Romania. - AWS will participate in NVIDIA GTC 2026 in San Jose. - AWS Community GameDay Europe will offer hands-on troubleshooting challenges across more than 50 cities. For practitioners, the most significant developments are Route 53 Global Resolver for centralized global DNS security, S3 namespaces for organizational naming governance, and AgentCore’s stateful MCP support for more capable AI applications.

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Database DesignAmazon S3Aws IamAmazon Redshift+4

aws·Mar 13, 2026·3 min readCurated summary

Twenty years of Amazon S3 and building what’s next | Amazon Web Services

Amazon S3 began in 2006 as a simple web service for storing and retrieving objects, but its emphasis on security, durability, availability, performance, and elasticity enabled it to become foundational infrastructure. Over two decades, it scaled from roughly one petabyte to hundreds of exabytes while preserving API compatibility, reducing prices, and expanding beyond object storage. Amazon’s long-term vision is for S3 to serve as a universal foundation for data, analytics, and AI workloads. ## The Original S3 Philosophy - S3 introduced two basic operations: - `PUT` to store an object - `GET` to retrieve it - The service abstracted away complex infrastructure so developers could focus on applications. - Its five enduring design principles are: - **Security:** Data is protected by default. - **Durability:** Designed for 11 nines of durability, with a lossless operating model. - **Availability:** Failure is assumed and handled throughout the system. - **Performance:** Storage capacity can grow without degrading performance. - **Elasticity:** Capacity expands and contracts automatically. ## From One Petabyte to Hundreds of Exabytes - At launch, S3 had approximately: - One petabyte of capacity - 400 storage nodes across 15 racks and three data centers - 15 Gbps of bandwidth - A maximum object size of 5 GB - A price of $0.15 per GB - Today, S3: - Stores more than 500 trillion objects. - Serves over 200 million requests per second. - Operates across 123 Availability Zones in 39 AWS Regions. - Supports objects up to 50 TB—10,000 times larger than the original limit. - Storage prices have fallen by roughly 85%, to slightly above 2 cents per GB. - S3 Intelligent-Tiering has saved customers more than $6 billion in storage costs. - The S3 API has become an industry standard, with many other storage systems offering compatible interfaces. ## Backward Compatibility and Long-Term Reliability - Code written against S3 in 2006 still works without modification. - AWS has repeatedly replaced disks, storage systems, and request-processing code while preserving access to older data. - This compatibility reflects S3’s goal of remaining infrastructure that “just works” despite continuous internal change. ## Engineering for Durability and Scale - Microservices continuously inspect every byte across the fleet. - Auditor services detect degradation and automatically trigger repair and re-replication. - Automated formal methods mathematically verify correctness in areas such as: - The index subsystem - Cross-Region replication - Access policies - AWS has progressively rewritten performance-critical components in Rust over the past eight years. - Rust improves performance while preventing memory-safety bugs and other classes of errors at compile time. - S3 follows the principle that scale should improve the service: larger, more distributed workloads become increasingly decorrelated, improving reliability for all customers. ## S3 as a Foundation for Data and AI Amazon’s future vision is for customers to store data once in S3 and work with it directly, avoiding costly copies and specialized systems. - **S3 Tables** provides managed Apache Iceberg tables with automated maintenance to improve query performance and reduce storage costs. - **S3 Vectors** supports semantic search and retrieval-augmented generation, with up to 2 billion vectors per index and sub-100 ms query latency. - Within five months of launch, customers created over 250,000 indexes, ingested more than 40 billion vectors, and executed over 1 billion queries. - **S3 Metadata** enables centralized, faster data discovery without recursively listing large buckets. These additions extend S3 from inexpensive object storage into a broader platform for analytics, search, and AI while retaining its scale and cost advantages.

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Database DesignRustAPIMicroservices+4

aws·Mar 12, 2026·2 min readCurated summary

Introducing account regional namespaces for Amazon S3 general purpose buckets | Amazon Web Services

Amazon S3 now lets customers create general purpose buckets in an account regional namespace, making bucket names predictable and reusable across AWS Regions. Names combine a customer-selected prefix with an account-, Region-, and namespace-specific suffix, preventing other accounts from claiming them. The feature preserves existing general purpose bucket capabilities while improving governance and automation. ## Account Regional Bucket Namespaces - Bucket names use a format such as `mybucket-123456789012-us-east-1-an`. - The suffix identifies the AWS account and Region, ensuring that other accounts cannot create buckets using it. - The combined prefix and suffix must be between 3 and 63 characters. - Buckets support the same features as general purpose buckets in the global namespace. ## Governance and Policy Controls - IAM policies and AWS Organizations service control policies can enforce namespace usage. - The new `s3:x-amz-bucket-namespace` condition key allows organizations to require account regional bucket creation. ## Creating Buckets - In the S3 console, select **Account regional namespace** when creating a bucket. - AWS CLI requests use the `--bucket-namespace account-regional` option. - SDKs can pass `BucketNamespace: "account-regional"` to the `CreateBucket` API. - Applications can use STS to retrieve the account ID and the SDK’s Region to construct compliant names. ## Infrastructure as Code - CloudFormation templates can use `AWS::AccountId` and `AWS::Region` to construct bucket names. - The `BucketNamespace: "account-regional"` property enables the feature. - `BucketNamePrefix` can be used when only the customer-defined prefix should appear in the template; AWS adds the account regional suffix automatically. ## Limitations and Availability - Existing global-namespace buckets cannot be renamed into the account regional namespace; new buckets must be created. - The feature applies only to S3 general purpose buckets. - S3 table and vector buckets use account-level namespaces, while directory buckets use zonal namespaces. - It is available in 37 AWS Regions, including AWS China and GovCloud Regions, with no additional cost. Organizations can adopt account regional namespaces to simplify bucket provisioning, prevent naming conflicts, and enforce consistent naming through IAM, Organizations policies, and infrastructure-as-code tools.

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Amazon S3Aws CliAws CloudformationAws Iam+3

aws·Mar 9, 2026·3 min readCurated summary

AWS Weekly Roundup: Amazon Connect Health, Bedrock AgentCore Policy, GameDay Europe, and more (March 9, 2026) | Amazon Web Services

The March 9, 2026 AWS Weekly Roundup highlights AWS’s growing focus on agentic AI, healthcare automation, security, and developer productivity. Major updates include Amazon Connect Health, centralized policies for Bedrock agents, private AI assistants on Lightsail, and new tools for troubleshooting and durable Lambda workflows. The roundup also previews community events, including GameDay Europe, NVIDIA GTC, AWS Summits, and regional Community Days. ## Major AWS Product Launches - **Amazon Connect Health** is generally available with five healthcare-focused AI agents: - Patient verification - Appointment management - Patient insights - Ambient documentation - Medical coding - These capabilities are HIPAA-eligible and designed to integrate with existing clinical workflows within days. - **Bedrock AgentCore Policy** provides centralized, fine-grained controls for agent-to-tool interactions. - Policies can be written in natural language. - AWS converts them into Cedar, its open-source policy language. - Controls operate outside application code, supporting security and compliance teams. - **OpenClaw on Amazon Lightsail** enables deployment of private autonomous AI assistants. - Includes sandboxed sessions, security controls, HTTPS, and device-pairing authentication. - Uses Amazon Bedrock by default and supports Slack, Telegram, WhatsApp, and Discord integrations. ## Pricing, Cost Management, and Security - **VPC Encryption Controls** became a paid feature on March 1, 2026. - Monitor mode detects unencrypted traffic. - Enforce mode blocks traffic that does not meet encryption requirements. - Controls apply to traffic within and across VPCs in a region. - **Database Savings Plans** now cover Amazon OpenSearch Service and Amazon Neptune Analytics. - Customers can save up to 35% with a one-year commitment. - Savings apply across engine, instance family, size, and AWS Region. - **Amazon GameLift Servers DDoS Protection** adds a co-located relay network. - Client traffic is authenticated with access tokens. - Per-player traffic limits help mitigate attacks. - The feature adds no cost for GameLift Servers customers. ## Developer and Operations Improvements - **Elastic Beanstalk AI-powered environment analysis** sends events, health data, and logs to Amazon Bedrock when environments degrade. - It returns troubleshooting recommendations tailored to the affected environment. - AWS now allows **IAM roles to be created directly inside service workflows**, reducing the need to switch to the IAM console. Supported services include EC2, Lambda, EKS, ECS, Glue, and CloudFormation. - **Kiro’s new Lambda durable functions power** assists developers with long-running, multi-step applications and AI workflows. - It provides guidance on replay models, waits, concurrency, error handling, and deployment. ## AWS Community Projects - One community project demonstrates a persistent AI memory layer using **MCP, Amazon Bedrock, and a Chrome extension**, allowing agents to retain context across sessions and applications. - Another experimental application treats the AI model as the runtime, generating a complete interactive web application from a single prompt without a conventional codebase, framework, or persistent state. ## Community Events and AWS Activities - **AWS Community GameDay Europe** takes place March 17, offering team-based challenges using real AWS services. - AWS will participate in **NVIDIA GTC 2026** in San Jose from March 16–19, with sessions, demos, booths, and discounted passes. - Upcoming **AWS Summits** include Paris, London, and Bengaluru. - Upcoming **AWS Community Days** include events in Slovakia, Pune, and Mexico City. AWS’s latest announcements show a clear emphasis on practical AI agents, stronger governance, and automation across infrastructure and application development. Developers and cloud teams should review the new security and pricing changes while exploring the AI tools and upcoming hands-on community events.

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Database DesignPostgreSQLAmazon BedrockAmazon Ec2+4

aws·Mar 4, 2026·3 min readCurated summary

Introducing OpenClaw on Amazon Lightsail to run your autonomous private AI agents | Amazon Web Services

Amazon Lightsail now offers a preconfigured OpenClaw instance for running a private, autonomous AI assistant without managing a complex installation. The setup uses Amazon Bedrock by default and supports browser access plus messaging integrations such as WhatsApp, Discord, and Telegram. AWS aims to simplify deployment while addressing the security concerns of running an agent that can access email, files, and the web. ## Launching OpenClaw on Lightsail - In the Lightsail console, create a new instance. - Select: - A preferred AWS Region and Availability Zone - Linux/Unix as the platform - OpenClaw as the blueprint - A 4 GB memory plan is recommended for performance. - The instance typically reaches a running state within minutes. ## Pairing the Browser - Use **Connect using SSH** from the Lightsail Getting Started tab. - Copy the dashboard URL and security credentials shown in the SSH welcome message. - Open the dashboard and enter the access token in the **Gateway Token** field. - Approve the pairing from the terminal by entering `y`, then `a`. - Once pairing succeeds, the dashboard displays an **OK** status. ## Enabling Amazon Bedrock - OpenClaw is preconfigured to use Amazon Bedrock as its AI provider. - Copy the setup script from the Getting Started tab. - Run it in AWS CloudShell to enable Bedrock API access. - After completion, use the **Chat** section of the dashboard to interact with the assistant. ## Messaging Integrations OpenClaw can connect to services such as Telegram and WhatsApp, allowing users to interact with the assistant from a phone or messaging client. It can perform tasks including email management, web browsing, and file organization. ## Permissions and Costs - The setup script creates an IAM role with permissions to access Bedrock. - IAM policies can be customized, but removing required permissions may stop the assistant from generating responses. - Lightsail charges are based on the selected instance plan’s on-demand hourly rate. - Bedrock usage is billed according to tokens processed. - Third-party models offered through AWS Marketplace may add software charges. ## Security Considerations - Do not expose the OpenClaw gateway directly to the public internet. - Treat the gateway authentication token like a password. - Rotate the token regularly. - Store credentials in environment files rather than hardcoding them in configuration. - Review OpenClaw’s gateway security guidance before granting the agent access to sensitive systems. OpenClaw on Lightsail is available in all commercial AWS Regions where Lightsail operates. It provides a convenient deployment path, but users should carefully control IAM permissions, monitor costs, and secure the gateway before connecting personal data or messaging accounts.

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Amazon BedrockAi AssistantAws IamSsh+2

aws·Mar 2, 2026·3 min readCurated summary

AWS Weekly Roundup: OpenAI partnership, AWS Elemental Inference, Strands Labs, and more (March 2, 2026) | Amazon Web Services

The March 2, 2026 AWS Weekly Roundup focuses on AWS’s expanding AI ecosystem, including a major strategic partnership with OpenAI and new tools for production AI development. It also highlights services for video transformation, enterprise security, application isolation, and agentic workloads. The broader message is that AWS is moving AI from experimentation toward scalable, enterprise-ready operations. ## OpenAI and AWS Strategic Partnership - Amazon will invest $50 billion in OpenAI: - $15 billion initially. - A further $35 billion subject to conditions. - AWS and OpenAI are developing a Stateful Runtime Environment for OpenAI models through Amazon Bedrock. - The environment allows applications to: - Preserve context and prior work. - Operate across tools and data sources. - Access compute resources. - AWS becomes OpenAI Frontier’s exclusive third-party cloud distribution provider for building and managing AI-agent teams. - The companies are expanding their existing $38 billion agreement by another $100 billion over eight years. - OpenAI plans to consume approximately 2 gigawatts of AWS Trainium capacity, including Trainium3 and Trainium4. ## Major AWS Product Launches - **AWS Security Hub Extended** - Provides integrated procurement and management for partner security products. - Includes vendors such as CrowdStrike, Okta, Splunk, Zscaler, and others. - Offers one AWS bill, pay-as-you-go pricing, unified Security Hub operations, and Level 1 support for Enterprise Support customers. - **AWS Elemental Inference** - Uses AI to transform live and on-demand video for mobile and social platforms. - Automatically creates vertical video for TikTok, Instagram Reels, and YouTube Shorts. - Extracts highlight clips with 6–10 seconds of latency. - Early media customers reported at least 34% savings on AI-powered live video workflows. - **MediaConvert Probe API** - Provides free, rapid media metadata analysis without processing the video. - Returns information such as codecs, pixel formats, and color spaces. - **OpenAI-Compatible Projects API for Amazon Bedrock** - Adds application-level isolation for generative AI workloads. - Improves access control, cost tracking, and organizational observability through OpenAI-compatible APIs. - **Amazon Location Service LLM Context** - Provides curated context for AI agents through Kiro, Claude Code, and the open Agent Skills format. - Helps developers implement location-aware features more accurately. - **Open-Source EKS Node Monitoring Agent** - Makes the agent’s implementation available for inspection, customization, and community contributions. - **AWS AppConfig and New Relic Integration** - Supports automated rollback through New Relic Workflow Automation. - Aims to reduce deployment issue detection and remediation from minutes to seconds. ## Strands Labs and Additional AWS Resources - AWS introduced **Strands Labs**, a separate organization for experimental agentic AI projects. - Its initial projects are: - Robots. - Robots Sim. - AI Functions. - Other highlighted resources cover: - Managing 6,000 AWS accounts with a three-person platform team. - Building event-driven agents with Bedrock AgentCore and Knowledge Bases. - Shifting complexity from application code into platform operations through account-per-tenant architectures. ## AWS Community Highlights - A practical guide for running effective Kiro AI coding workshops. - A comparison of traditional RAG using FAISS with GraphRAG using Neo4j to evaluate hallucination reduction in travel agents. - New AWS CLI v2 output options, including structured error output and the `off` format. ## Upcoming Events - **NVIDIA GTC 2026:** March 16–19 in San Jose, with AWS sessions, demos, and booths. - **AWS Summits:** Paris on April 1, London on April 22, and Bengaluru on April 23–24. - **AWS Community Days:** Events in Tokyo, Chennai, Slovakia, and Pune during March. AWS’s latest announcements point toward a tightly integrated AI platform combining specialized hardware, managed agent infrastructure, enterprise security, and production-focused developer tools. Organizations evaluating AI adoption should watch these services closely, particularly Bedrock’s new stateful and application-isolation capabilities and Elemental Inference’s automated media workflows.

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AI AgentsGenerative AIAmazon BedrockRAG+4

aws·Feb 26, 2026·2 min readCurated summary

AWS Security Hub Extended offers full-stack enterprise security with curated partner solutions | Amazon Web Services

AWS Security Hub Extended expands Security Hub from an AWS-focused service into a broader enterprise security platform. It combines AWS services such as GuardDuty and Inspector with curated partner solutions covering endpoints, identity, email, networks, data, cloud, AI, and security operations. The plan simplifies procurement and operations through AWS billing, normalized findings, and a unified console. ## Curated Partner Security Solutions - Includes offerings from partners such as CrowdStrike, Okta, Proofpoint, SailPoint, Splunk, Zscaler, and others. - Covers security needs across endpoint, identity, email, network, data, browser, cloud, AI, and security operations. - Lets organizations combine AWS and partner tools to detect risks spanning multiple parts of their technology stack. ## Simplified Procurement and Billing - AWS acts as the seller of record. - Customers receive pre-negotiated pay-as-you-go pricing, one monthly bill, and no long-term commitments. - Consumption-based metering is handled automatically after onboarding. - AWS Enterprise Support customers receive unified Level 1 support. ## Unified Findings and Operations - Findings from participating solutions are emitted in the Open Cybersecurity Schema Framework (OCSF). - Security Hub automatically aggregates and normalizes findings in one location. - The unified view helps teams prioritize and respond to critical risks more quickly. ## Access and Availability - Customers can find the offerings in the Security Hub console under **Management → Extended plan**. - Partner details, subscriptions, and onboarding are available directly through the console. - The plan is generally available in all commercial AWS Regions where Security Hub operates. - Pricing supports either flexible pay-as-you-go or flat-rate options. Organizations seeking broader security coverage can use Security Hub Extended to consolidate partner procurement, billing, findings, and operations through a single AWS-managed experience.

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Cloud SecurityAws Security HubOcsfEnterprise Security+3

aws·Feb 24, 2026·2 min readCurated summary

Transform live video for mobile audiences with AWS Elemental Inference | Amazon Web Services

AWS Elemental Inference is a fully managed AI service that transforms landscape live and on-demand video into mobile-ready vertical formats and automatically generates clips. It works in real time alongside AWS Elemental MediaLive, reducing 6–10 seconds of latency compared with minutes of traditional postproduction. AWS aims to help broadcasters publish content to TikTok, Instagram Reels, YouTube Shorts, and similar platforms without manual editing or specialized AI expertise. ## Mobile-Optimized Video Transformation - Smart Crop reformats landscape broadcasts into a 9:16 vertical format. - AI tracks subjects and keeps important action visible while preserving broadcast quality. - The service can process live content as it is being broadcast, helping publishers capture viral moments quickly. - Clip generation identifies notable events—such as game-winning plays in soccer or basketball—and produces clips for rapid distribution. ## Deployment and Workflow Integration - Users can create and manage feeds through the standalone AWS Elemental Inference console. - A feed contains feature configurations and moves from `CREATING` to `AVAILABLE`. - Outputs can be configured for vertical cropping or clipping; clip outputs require a name, the `Clipping` type, and an `ENABLED` status. - AWS Elemental Inference can also be enabled directly in existing AWS Elemental MediaLive channels without changing the surrounding video architecture. - MediaLive includes an AWS Elemental Inference tab showing the service ARN, data endpoints, feed outputs, enabled features, and operational status. ## Real-Time Agentic AI Processing - The service analyzes video continuously and independently performs cropping and clip-generation workflows. - Its agentic AI operates without human prompting or manual intervention. - Multiple AI features run in parallel against the same stream through a “process once, optimize everywhere” model. - Fully managed foundation models are automatically updated and optimized, removing the need for dedicated AI infrastructure or specialist teams. - Processing latency is approximately 6–10 seconds. ## Availability and Pricing - AWS Elemental Inference is initially available in: - US East (N. Virginia) - US West (Oregon) - Europe (Ireland) - Asia Pacific (Mumbai) - It can be accessed through the MediaLive console or MediaLive APIs. - Consumption-based pricing charges for the features used and video processed, with no upfront commitment. - AWS plans additional capabilities and tighter integration with other Elemental services, including features aimed at video monetization. AWS Elemental Inference is best suited to broadcasters and streamers that need to repurpose live content for mobile platforms quickly. Organizations already using MediaLive can add automated cropping and clip generation with minimal architectural change.

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AIAI AgentsFoundation ModelsLive Streaming+4

aws·Feb 23, 2026·3 min readCurated summary

AWS Weekly Roundup: Claude Sonnet 4.6 in Amazon Bedrock, Kiro in GovCloud Regions, new Agent Plugins, and more (February 23, 2026) | Amazon Web Services

AWS’s February 23, 2026 roundup highlights continued investment in AI-assisted development, cloud infrastructure, and production-grade agents. Major launches include Claude Sonnet 4.6 in Amazon Bedrock, Kiro for GovCloud, customizable SageMaker deployments for Nova models, and new EC2 and Aurora capabilities. The post also points developers toward agent tooling, operational best practices, community resources, and upcoming events. ## Developer Conferences and AI Collaboration - AWS teams discussed “renascent software,” where humans and AI work together as co-developers through Kiro. - Developer Week sessions focused on: - Agent memory - Multi-agent architectures - Meta-tooling - Hooks - Production deployment of AI agents - At dev/nexus in Atlanta, AWS speakers will cover AI agents with Spring and MCP, along with AI-assisted Java modernization. ## Major AWS Launches - **Claude Sonnet 4.6 in Amazon Bedrock** - Provides near-Opus 4.6 intelligence at lower cost. - Targets coding, agent workloads, and professional knowledge work. - Designed for fast, high-quality task completion at scale. - **Amazon EC2 Hpc8a instances** - Powered by 5th Gen AMD EPYC processors. - Deliver up to 40% higher performance, increased memory bandwidth, and 300 Gbps Elastic Fabric Adapter networking. - Intended for simulations, engineering, and tightly coupled HPC workloads. - **Custom Amazon Nova models with SageMaker Inference** - Supports configuration of instance types, auto-scaling policies, and concurrency. - Enables deployments to be tuned for specific performance and cost requirements. - **Nested virtualization on EC2** - Allows KVM or Hyper-V virtual machines to run inside virtual EC2 instances. - Supports mobile emulators, automotive hardware simulation, and Windows Subsystem for Linux environments. - **Aurora encryption by default** - New database clusters automatically use server-side encryption with AWS-owned keys. - Encryption is transparent, fully managed, and has no additional cost or performance impact. - **Kiro in AWS GovCloud** - Brings Kiro’s agentic development capabilities to teams working on government missions. - Supports regulated environments requiring stringent security controls. ## Agent Tools and Operational Reliability - AWS introduced open-source **Agent Plugins for AWS** that add AWS-specific skills to coding agents. - The `deploy-on-aws` plugin can generate: - Architecture recommendations - Cost estimates - Infrastructure-as-code - AWS also highlighted automated reasoning research led by Byron Cook, applying formal verification techniques to AI-generated code and critical agent decisions. - Recommended practices for AWS DevOps Agent focus on configuring Agent Spaces to balance broad investigation capabilities with operational efficiency. - AWS reports that DevOps Agent has handled thousands of escalations and achieved an estimated root-cause identification rate above 86% within Amazon. ## Community Projects and Resources - Community content includes: - A practical guide to AWS for developers entering their first job. - An AI agent that automates job searching. - A Kiro Power integrating 25 MCP tools, 10 steering guides, and structured development guidance. - AWS encourages developers to use the AWS Builder Center to exchange knowledge and discover community content. ## Upcoming Events and Hackathons - 2026 AWS Summits are scheduled for Paris, London, and Bengaluru. - The six-week Amazon Nova AI Hackathon runs through March 16, with $40,000 in prizes across areas such as agentic AI, multimodal applications, UI automation, and voice. - Upcoming AWS Community Days include events in Ahmedabad, Tokyo, Chennai, Slovakia, and Pune. Developers interested in AI-assisted coding, agent operations, or high-performance cloud workloads should explore the new Bedrock, Kiro, SageMaker, and Agent Plugin capabilities, while using AWS events and community forums for practical guidance.

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AI AgentsGenerative AIAmazon BedrockAmazon Ec2+4

aws·Feb 16, 2026·2 min readCurated summary

Amazon EC2 Hpc8a Instances powered by 5th Gen AMD EPYC processors are now available | Amazon Web Services

Amazon EC2 Hpc8a instances are now generally available for tightly coupled, compute-intensive HPC workloads. Powered by 5th Gen AMD EPYC processors reaching 4.5 GHz, they provide up to 40% more performance, 42% higher memory bandwidth, and 25% better price-performance than Hpc7a instances. AWS targets applications such as fluid dynamics, weather modeling, design simulations, and crash analysis. ## Instance Specifications - Available in a single `96xlarge` configuration: - 192 CPU cores - 768 GiB memory - 300 Gbps Elastic Fabric Adapter (EFA) networking - Uses a 1:4 core-to-memory ratio. - Customers can customize the number of cores at launch to better match workload requirements. - Simultaneous Multithreading (SMT) is disabled to maximize HPC performance. - Sixth-generation AWS Nitro cards handle virtualization, storage, and networking tasks separately from the CPUs. ## Supported HPC Services - Integrates with AWS ParallelCluster and AWS Parallel Computing Service (AWS PCS) for cluster creation and job submission. - Supports Amazon FSx for Lustre, offering sub-millisecond latency and throughput of up to hundreds of gigabytes per second. - High-bandwidth, low-latency networking is designed for workloads requiring extensive communication between compute nodes. ## Availability and Purchasing - Initially available in: - US East (Ohio) - Europe (Stockholm) - Offered through On-Demand Instances and Savings Plans. - Regional availability and future expansion can be checked through AWS Capabilities by Region. Hpc8a instances are best suited for organizations needing faster simulation results and efficient scaling across tightly coupled HPC workloads. Teams can launch them through the Amazon EC2 console and combine them with AWS cluster and storage services for a complete HPC environment.

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Amazon Ec2Amd EpycAws Nitro SystemHigh Performance Computing+4

aws·Feb 16, 2026·3 min readCurated summary

Announcing Amazon SageMaker Inference for custom Amazon Nova models | Amazon Web Services

Amazon SageMaker Inference now generally supports deploying and scaling full-rank customized Amazon Nova models. The feature gives production workloads more control over instance types, autoscaling, context length, concurrency, and batch settings while improving cost efficiency through optimized GPU utilization. Customers can train Nova Micro, Nova Lite, and Nova 2 Lite models with SageMaker Training Jobs or HyperPod, then deploy them as managed real-time or asynchronous endpoints. ## Custom Nova Model Support - Supports customized Nova Micro, Nova Lite, and Nova 2 Lite models. - Models can use: - Continued pre-training - Supervised fine-tuning - Reinforcement fine-tuning - Custom models can be trained through Amazon SageMaker Training Jobs or Amazon HyperPod. - SageMaker Inference provides managed deployment, scaling, and HTTPS access for production workloads. - GPU utilization and inference costs can be optimized with Amazon EC2 G5 and G6 instances instead of relying exclusively on P5 instances. - Autoscaling can respond to five-minute usage patterns. - Configurable context length, concurrency, and batch size help balance latency, cost, and accuracy. ## Deploying Through SageMaker Studio - In SageMaker Studio, users select a trained Nova model from the Models menu. - Choosing **Deploy**, **SageMaker AI**, and **Create new endpoint** starts deployment. - Deployment settings include: - Endpoint name - Instance type - Initial and maximum instance counts - Permissions - Networking configuration - Supported launch instance types vary by model: - Nova Micro: G5, G6, and P5 options, including `g5.12xlarge` through `g6.48xlarge` and `p5.48xlarge` - Nova Lite: `g5.48xlarge`, `g6.48xlarge`, and `p5.48xlarge` - Nova 2 Lite: `p5.48xlarge` - Provisioning takes time because SageMaker must create infrastructure, download model artifacts, and initialize the inference container. - Once the endpoint is `InService`, users can test it in the Studio Playground using chat prompts. ## Deploying with the SageMaker SDK - Deployment requires two SageMaker resources: - A model object referencing the Nova artifacts and inference container - An endpoint configuration specifying the instance type and count - Model artifacts can be stored in Amazon S3 and referenced with an S3 prefix. - Environment variables configure inference behavior, including: - `CONTEXT_LENGTH` - `MAX_CONCURRENCY` - `DEFAULT_TEMPERATURE` - `DEFAULT_TOP_P` - The endpoint configuration creates a real-time endpoint, such as one using an `ml.g5.12xlarge` instance. - SageMaker supports network isolation and execution roles for secure deployment. ## Inference and Request Configuration - Endpoints support synchronous real-time inference in streaming or non-streaming modes. - Asynchronous endpoints are available for batch-style processing. - Requests can configure: - Maximum output tokens - Temperature - Top-p and top-k sampling - Log probabilities - Streaming usage statistics - Reasoning effort, with `low` and `high` options - The example request asks the model to compare quarterly spending against budget and identify variances above 10 percent. SageMaker Inference provides a complete path from Nova customization to production deployment. Teams should select instance types and tune context length, concurrency, batching, and sampling parameters based on their workload’s latency, cost, and accuracy requirements.

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Machine LearningAWSAmazon Ec2Fine Tuning+3

aws·Feb 16, 2026·3 min readCurated summary

AWS Weekly Roundup: Amazon EC2 M8azn instances, new open weights models in Amazon Bedrock, and more (February 16, 2026) | Amazon Web Services

AWS’s February 16, 2026 roundup highlights the launch of Amazon EC2 M8azn instances, which deliver substantial performance gains for compute-intensive workloads. It also covers expanded Amazon Bedrock model and networking support, improved observability in EKS Auto Mode, more efficient OpenSearch Serverless capacity management, and configurable RDS backup settings during snapshot restoration. The post concludes with upcoming AWS conferences, summits, and community events. ## Amazon EC2 M8azn Instances - Powered by fifth-generation AMD EPYC processors with a maximum frequency of 5 GHz. - Compared with M5zn instances, they provide: - Up to 2× compute performance - 4.3× higher memory bandwidth - 10× larger L3 cache - Up to 2× networking throughput - Up to 3× EBS throughput - Built on the AWS Nitro System with sixth-generation Nitro Cards. - Available in nine sizes, from 2 to 96 vCPUs and up to 384 GiB of memory, including two bare-metal options. - Designed for high-performance workloads such as financial analytics, high-frequency trading, CI/CD, gaming, simulations, and HPC. ## New Open-Weight Models in Amazon Bedrock - Bedrock now supports six fully managed models: - DeepSeek V3.2 - MiniMax M2.1 - GLM 4.7 - GLM 4.7 Flash - Kimi K2.5 - Qwen3 Coder Next - The models target reasoning, agentic intelligence, autonomous coding, and cost-efficient production deployments. - They use Project Mantle and support OpenAI-compatible APIs. - DeepSeek V3.2, MiniMax 2.1, and Qwen3 Coder Next are also available in Kiro. ## Amazon Bedrock PrivateLink Support - AWS PrivateLink now supports the `bedrock-mantle` endpoint in addition to `bedrock-runtime`. - Project Mantle provides serverless inference, quality-of-service controls, automated capacity management, and OpenAI API compatibility. - PrivateLink support for OpenAI-compatible endpoints is available in 14 AWS Regions. ## EKS Auto Mode Logging - EKS Auto Mode now supports CloudWatch Vended Logs for managed capabilities such as: - Compute autoscaling - Block storage - Load balancing - Pod networking - Logs can be delivered to CloudWatch Logs, Amazon S3, or Amazon Data Firehose. - The feature includes AWS authentication and authorization and is offered at a lower price than standard CloudWatch Logs. ## OpenSearch Serverless Collection Groups - Collection Groups allow multiple collections to share OpenSearch Compute Units while retaining separate KMS keys and access controls. - Shared capacity can reduce OCU costs. - Administrators can define both minimum and maximum OCU limits, ensuring baseline capacity for latency-sensitive applications. ## RDS Snapshot Restore Improvements - RDS now lets users view and configure backup retention periods and preferred backup windows before or during snapshot restoration. - Restored databases no longer need post-restore backup configuration changes. - The feature supports all major RDS engines, Aurora editions, commercial AWS Regions, and GovCloud at no additional cost. ## Upcoming AWS Events - AWS Summits in Paris, London, and Bengaluru during April 2026. - AWS AI and Data Conference in Ireland on March 12, focusing on Bedrock, SageMaker, QuickSight, agent deployment, data integration, and governance. - AWS Community Days in Ahmedabad, Slovakia, and Pune. Overall, the announcements emphasize faster specialized compute, broader managed AI model access, stronger private connectivity, and improved operational controls across AWS services.

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KubernetesGenerative AIAmazon BedrockCloud Computing+4

aws·Feb 9, 2026·3 min readCurated summary

AWS Weekly Roundup: Claude Opus 4.6 in Amazon Bedrock, AWS Builder ID Sign in with Apple, and more (February 9, 2026) | Amazon Web Services

The February 9, 2026 AWS roundup highlights updates across infrastructure, security, databases, and AI. Major announcements include new EC2 instances, cross-account DynamoDB replication, improved identity controls, CloudFront mutual TLS, Claude Opus 4.6 in Bedrock, and structured model outputs. AWS also announced AWS Community Day Romania for April 23–24, 2026. ## Compute, Networking, and Configuration - **New EC2 C8id, M8id, and R8id instances** - Powered by custom Intel Xeon 6 processors. - Deliver up to 43% higher performance and 3.3× more memory bandwidth than previous-generation instances. - **AWS Network Firewall price reductions** - Reduces hourly and data-processing costs for NAT Gateways service-chained with Network Firewall secondary endpoints. - Removes additional data-processing charges for Advanced Inspection and TLS inspection. - **Amazon ECS Network Load Balancer support** - Enables managed linear and canary deployments for applications using NLBs. - Supports TCP/UDP workloads, low-latency services, long-lived connections, and static IP requirements. - **Expanded AWS Config coverage** - Adds support for 30 resource types across services such as Amazon EKS, Amazon Q, and AWS IoT. - Improves resource discovery, auditing, assessment, and remediation. ## Databases and Operations - **Cross-account DynamoDB global table replication** - Allows multi-Region, multi-active tables to replicate across AWS accounts. - Improves resilience, account-level workload isolation, and independent security and governance controls. - **Improved Amazon RDS connection experience** - Generates connection snippets for Java, Python, Node.js, `psql`, and other tools. - Adjusts examples automatically for authentication settings, including IAM token-based authentication. - Adds CloudShell integration for connecting to databases directly from the RDS console. ## Identity and Security - **AWS Builder ID adds Sign in with Apple** - Apple users can access services such as AWS Builder Center, Training and Certification, re:Post, AWS Startups, and Kiro. - Complements the existing Google sign-in option. - **More identity-provider claim validation in AWS STS** - Supports selected claims from Google, GitHub, CircleCI, and OCI. - These claims can be used as condition keys in IAM trust policies and resource control policies for more precise federated-access controls and data perimeters. - **Account names in the AWS Management Console** - Displays the account name in the navigation bar, making it easier to distinguish between authorized AWS accounts. - **CloudFront origin mutual TLS** - Lets CloudFront authenticate to origins using certificates. - Helps restrict backend access to verified CloudFront distributions across AWS, on-premises, third-party cloud, and external CDN environments. ## AI and Amazon Bedrock - **Claude Opus 4.6 available in Amazon Bedrock** - Anthropic’s latest model targets complex coding, agentic tasks, enterprise workflows, and professional work requiring deep reasoning and reliability. - **Structured outputs in Amazon Bedrock** - Models can return responses matching developer-defined JSON schemas. - Reduces the need for prompt-based JSON enforcement and additional validation, making production integrations more predictable. ## Upcoming AWS Event - **AWS Community Day Romania — April 23–24, 2026** - Features more than 10 technical sessions from AWS Heroes, Solutions Architects, and industry experts. - Includes networking opportunities for developers, architects, entrepreneurs, and students. These updates emphasize stronger infrastructure performance, better multi-account governance, more secure authentication, and more reliable AI application development. Teams should evaluate the new services based on their networking, resiliency, identity, and structured-output requirements.

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Generative AIAWSAmazon BedrockAmazon Ec2+4