Amazon Ec2

22 posts

slack3 min readCurated summary

Shipyard: How We Built Slack’s Next-Generation EC2 Platform

Slack’s Shipyard is a next-generation EC2 platform that replaces continuously modified, long-lived instances with immutable, deployable infrastructure artifacts. It combines layered machine images, service-level deployments, progressive rollouts, automated rollback, and short-lived instances to make EC2 operations more predictable and secure. The platform preserves EC2’s flexibility for workloads that cannot easily move to containers while adopting modern application-delivery practices. ## Why Slack Built Shipyard - Slack previously improved its Chef infrastructure with: - Multiple resilient Chef stacks - Versioned cookbook deployments - Safer promotion workflows - Split production environments and signal-based Chef runs - Despite these improvements, the traditional model of continuously updating instances still caused: - Infrastructure drift - Difficult service-level deployments - Coordination problems across infrastructure layers - Increasing operational complexity - Shipyard shifts infrastructure management from mutable instances and constant configuration enforcement to build pipelines, deployable artifacts, and automated safety mechanisms. ## Shipyard’s Core Capabilities - Supports AMD64 and ARM-based Graviton processors. - Supports Ubuntu, RHEL, and Amazon Linux. - Targets workloads that cannot easily migrate to containers, including: - Infrastructure services - Kubernetes worker nodes - Egress network stacks - Integrates with Slack’s Gondola deployment orchestrator for progressive rollouts. - Uses service health metrics to automatically pause deployments or roll back to a known-good version. - Uses layered images so instances perform less work during startup and provision quickly and consistently across regions. ## Configuration Management Without Continuous Mutation - Under the previous model, scheduled Chef jobs repeatedly checked and reapplied configuration. - Shipyard applies configuration during defined lifecycle stages, primarily: - Image baking - Initial instance provisioning - Service deployment - Configuration management tools no longer continuously modify the entire running system. - This reduces background workload, prevents unexpected overwrites, and makes instance behavior easier to understand. ## Fleet Inventory with Peekaboo - Shipyard introduces Peekaboo, a near-real-time inventory system for EC2. - Peekaboo uses AWS EventBridge, OpenSearch, and Lambda to collect cloud events and instance metadata. - It provides: - A fleet-exploration UI - An API for integrations - A command-line interface - Unlike Chef Server, Peekaboo is not limited to Shipyard-managed instances and can provide visibility across the entire EC2 fleet. ## Short-Lived Immutable Instances - Shipyard regularly rotates instances instead of relying on in-place updates. - Limited instance lifespans: - Reduce the window in which vulnerabilities can persist - Prevent long-term configuration drift - Encourage teams to replace instances rather than repair them manually - This makes infrastructure more closely resemble immutable application artifacts. ## The `slack-zero` Golden Image - `slack-zero` is Slack’s shared foundational AMI, maintained by the Compute Platform Team with security and monitoring teams. - It includes: - Operating-system hardening - Networking and service discovery - Monitoring and security agents - Common tools and foundational configuration - Service-specific images are built on top of `slack-zero`, similar to layering application images on a Docker base image. - When foundational components change, Slack produces a new immutable base image and rebuilds downstream service images to inherit updates. ## AWS Image Builder - Slack uses AWS Image Builder instead of Packer to create `slack-zero`. - Image Builder provides lifecycle policies that automatically remove old AMIs and reduce storage costs. - Each new image publishes its latest AMI identifier through an AWS Systems Manager parameter, helping downstream systems discover the current base image. Shipyard’s central recommendation is to treat EC2 infrastructure as versioned, replaceable artifacts rather than mutable machines. Combining trusted base images, automated provisioning, metric-driven deployment controls, fleet-wide inventory, and scheduled instance replacement gives Slack safer and more predictable EC2 operations at scale.

Read original(opens in new tab)
aws3 min readCurated summary

Amazon EC2 C9g and C9gd instances powered by AWS Graviton5 processors are now available | Amazon Web Services

Amazon EC2 C9g and C9gd instances, powered by AWS Graviton5, are now generally available for compute-intensive workloads. They provide up to 25% better performance per vCPU than C8g, faster DDR5 memory, larger caches, and improved networking and EBS bandwidth. C9gd adds local NVMe SSD storage, making it suitable for workloads requiring both high CPU performance and low-latency temporary storage. ## Graviton5 Performance Improvements - Up to 25% higher performance per vCPU than previous-generation C8g instances. - DDR5 memory running at 8800 MT/s, described as the fastest memory available in a cloud processor instance. - Five times more L3 cache than Graviton4-based instances. - Up to three times higher packet-processing performance than Graviton4. - Benefits include faster in-memory analytics, higher throughput, and more responsive real-time applications. ## C9g and C9gd Workloads - C9g is designed for compute-heavy applications using Amazon EBS, including: - Batch processing - Video encoding - Distributed analytics - CPU-based machine learning inference - Agentic AI workloads - C9gd adds local NVMe SSD storage for: - HPC simulation scratch space - Machine learning inference caches - Ad-serving buffers - Other low-latency temporary-storage use cases - C9gd delivers up to 30% higher local storage performance than the previous generation. ## Networking, Storage, and Configuration - Available in 11 sizes from medium through 48xlarge, plus bare metal. - Up to 15% higher network bandwidth and 20% higher EBS bandwidth on average compared with the prior generation. - The largest instances provide up to 100 Gbps networking and 72 Gbps EBS bandwidth. - Instance Bandwidth Configuration allows up to 25% of bandwidth to be shifted between EBS and VPC networking. - Support includes ENA Express, up to 128 EBS volumes, and On-Demand, Spot, Savings Plans, Dedicated Instances, and Dedicated Hosts. - NVMe-equipped instances expose detailed I/O statistics, including latency histograms by I/O size at one-second granularity through CloudWatch or `nvme-cli`. ## Nitro Isolation Engine - C9g and C9gd are the first compute-optimized EC2 instances to use the AWS Nitro Isolation Engine. - The Rust-based Nitro System component isolates virtual machines by mediating access to memory, CPU register state, and I/O devices through a minimal API set. - AWS provides additional technical documentation covering the engine and its formal verification results. ## Availability - The instances are available in US East (Ohio and Northern Virginia), US West (Oregon), and Europe (Frankfurt). - They can be launched through the AWS Management Console, CLI, or SDKs, with more regions planned. For compute-intensive workloads, C9g is the general-purpose choice, while C9gd is preferable when fast local NVMe storage is also required.

Read original(opens in new tab)
aws2 min readCurated summary

Announcing Amazon EC2 G7 instances accelerated by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs | Amazon Web Services

Amazon EC2 G7 instances are now generally available with NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs and custom sixth-generation Intel Xeon processors. Compared with G6 instances, they provide up to 4.6× higher AI inference performance and 2.1× better graphics performance. AWS positions them for AI inference, rendering, video, virtual desktops, spatial computing, and GPU-accelerated analytics. ## GPU and Performance Improvements - Each GPU provides 32 GB of memory, with up to 256 GB across eight GPUs. - GPU memory capacity is 1.33× higher and bandwidth is 2.45× higher than G6. - GPUs include fifth-generation Tensor Cores and fourth-generation RT Cores. - G7 instances accelerate analytics workloads running on Amazon EMR with Amazon EKS. ## Networking and Storage - Up to 700 Gbps of EFA-enabled networking—seven times the G6 throughput. - Up to 7.6 TB of local NVMe SSD storage keeps large models and datasets close to the GPUs. - Support for NVIDIA GPUDirect P2P and GPUDirect RDMA with EFA enables low-latency GPU communication across GPUs, nodes, and FSx for Lustre. ## Video Processing - Ninth-generation NVENC and sixth-generation NVDEC engines support 4:2:2 encoding and decoding. - They deliver up to 1.5× more concurrent video streams than G6 instances. ## Instance Configurations - Seven instance sizes are available. - Configurations offer up to: - 8 NVIDIA RTX PRO 4500 GPUs - 192 vCPUs - 768 GiB of system memory - 700 Gbps network bandwidth - 7.6 TB local NVMe storage - Detailed instance specifications were listed as “coming soon” in the announcement. ## Software and Availability - AWS provides Deep Learning AMIs and NVIDIA Workstation AMIs with preinstalled drivers. - Amazon EKS users should build AMIs with NVIDIA driver version R595. - Supported operating systems include Amazon Linux, Ubuntu, RHEL, and Windows Server. - NVIDIA integration supports DirectX, Vulkan, and OpenGL. - G7 instances are initially available in US East (Ohio) and US West (Oregon). - Purchasing options include On-Demand, Savings Plans, Spot Instances, and Dedicated Instances for selected sizes. G7 instances are a strong option for GPU-intensive workloads requiring higher inference, graphics, networking, and video performance. Organizations can launch them through the EC2 console and evaluate pricing across the available purchasing models.

Read original(opens in new tab)
aws2 min readCurated summary

Amazon ECS introduces new high-resolution metrics for faster service auto scaling | Amazon Web Services

Amazon ECS now supports 20-second high-resolution metrics for faster service auto scaling. AWS reports that scale-out triggers improved from 363 to 86 seconds, while total scaling and task provisioning dropped from 386 to 109 seconds. The update helps applications handle traffic spikes more reliably, reduce excess baseline capacity, and achieve aggressive scaling with simpler target-tracking policies. ## Faster Scaling with High-Resolution Metrics - ECS service auto scaling can use predictive, scheduled, or reactive target-tracking policies. - New 20-second metrics allow ECS to detect workload changes faster than standard 60-second metrics. - AWS benchmarking showed: - 76% faster scale-out triggering, or 4.2× improvement. - 72% faster total scaling and task provisioning, or 3.5× improvement. - Faster scaling can reduce latency and failures during sudden demand increases. ## Lower Costs and Simpler Configuration - Applications may reduce baseline task counts because capacity can be added quickly during spikes. - This can lower compute costs without sacrificing availability. - High-resolution target tracking can provide aggressive scaling behavior that previously required custom step-scaling policies. ## Configuration and Supported Metrics - Enable high-resolution metrics for the ECS service, then configure a target-tracking scaling policy. - New options include: - `ECSServiceAverageCPUUtilizationHighResolution` - `ECSServiceAverageMemoryUtilizationHighResolution` - The feature works with AWS Fargate, ECS Managed Instances, and Amazon EC2. - It can be configured through the ECS console, AWS SDKs, AWS CLI, Application Auto Scaling, or CloudFormation. - Existing services must first enable high-resolution metrics and complete deployment before their scaling policy can be updated. ## Cost and Availability - The ECS feature itself has no additional charge. - High-resolution CloudWatch metrics incur additional CloudWatch costs, unlike standard 60-second metrics. - The capability is available now. For workloads with unpredictable or rapid traffic changes, enabling high-resolution metrics with target tracking can improve responsiveness while reducing the need for overprovisioned ECS tasks.

Read original(opens in new tab)
aws4 min readCurated summary

AWS Weekly Roundup: AWS FinOps Agent in preview, Gemma 4 on Bedrock, Kiro Pro Max, and more (June 15, 2026) | Amazon Web Services

AWS’s June 15, 2026 roundup highlights rapid adoption of AI-native development, a preview of the AWS FinOps Agent, and major infrastructure and model releases. AWS reports significant productivity gains from agent-assisted engineering, while new services target cost optimization, observability, security, and developer workflows. The overall direction is toward more autonomous, context-aware tools integrated throughout the AWS ecosystem. ## AI-Native Development at AWS - Amazon engineering teams are restructuring development around AI agents. - A six-engineer team rebuilt the Amazon Bedrock inference engine in 76 days, compared with an original estimate of 30 developers over 12–18 months. - Structured Amazon Stores pilots achieved a median 4.5× improvement in normalized deployment velocity, with some teams exceeding 10×. - Recommended practices for “frontier teams” include: - Building steering files, coding standards, and structured repositories to provide agent context. - Expecting an initial productivity slowdown while workflows change. - Maintaining a backlog of well-scoped tasks that agents can execute in parallel. - Writing structured specifications before generating code. - Moving testing earlier so agents can detect and correct issues. - AWS cautions that commit velocity is only one measure; future work will address release management, operations, security, and end-of-life upgrades. ## AWS FinOps Agent Preview - AWS FinOps Agent helps finance and engineering teams: - Answer AWS cost questions and generate reports. - Identify rightsizing, idle-resource, and Savings Plans opportunities. - Investigate cost anomalies automatically. - Schedule recurring FinOps workflows. - Recommendations come from AWS Cost Optimization Hub and AWS Compute Optimizer. - The agent can open Jira tickets and post anomaly-investigation findings to Slack. ## New EC2 M9g and M9gd Instances - M9g and M9gd instances use AWS Graviton5 processors and the sixth-generation Nitro System. - They provide: - Up to 25% better compute performance than Graviton4. - Up to 35% faster web applications and ML inference. - Up to 30% faster database performance. - Up to 15% more network bandwidth and 20% more EBS bandwidth than M8g. - Graviton5 adds PCIe Gen6, DDR5-8800 memory, and a 5× larger L3 cache. - The Nitro Isolation Engine uses formal verification to provide mathematically proven VM isolation. - M9gd adds up to 11.4 TB of local NVMe SSD storage and 30% higher IOPS than M8gd. - Instance Bandwidth Configuration can shift bandwidth between EBS and VPC networking by up to 25%. ## Bedrock Model Updates - Anthropic Claude Fable 5 launched on Bedrock with: - Extended asynchronous task execution. - Advanced vision for diagrams, charts, and PDFs. - Proactive self-verification. - Access required Data Retention API opt-in and 30-day retention for inputs and outputs. - Anthropic later asked AWS to revoke access to Claude Fable 5 and Claude Mythos 5 in response to a U.S. government export-control directive. - Google DeepMind’s Gemma 4 models are available in three versions: - Gemma 4 31B for reasoning and coding, with a 256K-token context window. - Gemma 4 26B-A4B, a mixture-of-experts model for cost- and latency-sensitive use. - Gemma 4 E2B for low-latency interactive applications. - All variants support function calling, structured output, reasoning, streaming, multimodal inputs, and more than 35 languages. ## OpenSearch MCP Apps for Agentic Observability - OpenSearch MCP Apps bring logs, traces, metrics, and alerts into compatible agentic environments such as Claude Desktop and VS Code. - Agents can investigate incidents across OpenSearch and Amazon Managed Service for Prometheus. - Each tool call produces both: - A text summary for the agent. - An interactive visualization displayed in the conversation. - Available tools cover log, metric, and trace analysis; service performance; topology; agent health; cluster health; dynamic visualizations; and instrumentation scoring. ## Additional AWS Updates - AWS CLI v1 is entering maintenance mode: - Dependencies such as `botocore` and `s3transfer` will be vendored into the CLI. - Future releases will focus on critical bugs and security fixes. - AWS recommends migrating to CLI v2. - AWS Workload Credentials Provider provides short-term credentials for applications running outside AWS, including on-premises and third-party environments, without requiring long-term access keys. - Kiro Pro Max adds higher usage limits, access to newer frontier models, and additional agentic development capabilities for professional teams. AWS’s latest releases suggest that teams should prepare for AI agents to handle not only code generation, but also cost management, observability, testing, and operational workflows. Migrating to AWS CLI v2, evaluating Bedrock’s newest models, and establishing strong repository context and specifications are practical next steps.

Read original(opens in new tab)
aws3 min readCurated summary

Now available: Amazon EC2 M9g and M9gd instances powered by new AWS Graviton5 processors | Amazon Web Services

AWS has generally released Amazon EC2 M9g and M9gd instances, powered by its Graviton5 processors. They deliver higher compute, memory, networking, and storage performance while improving energy efficiency and security. M9g targets general-purpose workloads, while M9gd adds up to 11.4 TB of local NVMe SSD storage for low-latency applications. ## Graviton5’s Performance Improvements - Graviton5 provides up to: - 25% better compute performance than Graviton4 - 35% faster web applications and ML inference - 30% faster database workloads - It includes: - 192 CPU cores - Five times more L3 cache - Up to 33% lower inter-core latency - DDR5-8800 memory - PCIe Gen6 support - These features improve concurrency, memory bandwidth, and CPU-heavy workloads such as agentic AI, code generation, real-time reasoning, and multi-step orchestration. - Customer results include: - ClickHouse: 36% better performance than M8g without code changes - Honeycomb: 36% higher throughput per core - HubSpot: up to 60% shorter MySQL query duration ## Networking and Storage Enhancements - M9g and M9gd provide: - Up to 15% higher network bandwidth - Up to 20% higher EBS bandwidth on average - Up to twice the network bandwidth on the largest instance - Instance Bandwidth Configuration lets customers shift bandwidth between EBS and VPC networking by up to 25%. - This is useful for databases, query processing, logging, and other workloads with demanding I/O requirements. ## Nitro Isolation Engine - M9g and M9gd introduce the Nitro Isolation Engine, an enhancement to the AWS Nitro System. - It isolates virtual machines by controlling access to: - Memory - CPU register state - I/O devices - The component uses formal verification to mathematically prove isolation behavior rather than relying solely on testing. - AWS describes Nitro as the first formally verified cloud hypervisor. ## M9g General-Purpose Instances - M9g instances provide one vCPU per 4 GiB of memory. - Suitable workloads include: - Application servers and microservices - Web applications and containerized applications - Midsize data stores and caching fleets - Gaming servers - Large-scale Java applications - Code repositories - Agentic AI workloads ## M9gd Instances with Local NVMe Storage - M9gd adds up to 11.4 TB of local NVMe SSD storage. - It offers up to 30% higher IOPS and storage performance than Graviton4-based M8gd instances. - Recommended for: - Low-latency caches and scratch files - Data and log processing - Media processing - Batch workloads - Key-value stores - Gaming and application servers ## Availability and Migration Resources - M9g and M9gd are available in: - US East (N. Virginia) - US East (Ohio) - US West (Oregon) - Europe (Frankfurt) - Purchasing options include Savings Plans, On-Demand, Spot Instances, Dedicated Instances, and Dedicated Hosts. - AWS provides a Graviton Getting Started Guide, Graviton Savings Dashboard, and AWS Transform for migrating Java applications from x86 to Graviton. Organizations seeking better compute efficiency, higher I/O throughput, or lower-cost Arm infrastructure should evaluate M9g for general-purpose workloads and M9gd when local NVMe storage is required.

Read original(opens in new tab)
aws3 min readCurated summary

AWS Weekly Roundup: AWS Transform at 1 year, Claude Platform on AWS, EC2 M3 Ultra Mac instances, and more (May 18, 2026) | Amazon Web Services

AWS’s May 18, 2026 roundup highlights the rapid expansion of AI-assisted modernization, cloud infrastructure, and developer tooling. AWS Transform reached its first anniversary after processing billions of lines of code and migrating hundreds of thousands of servers, while new services provide direct Claude access, stronger Mac development hardware, improved analytics, and automated security remediation. The roundup also covers multicloud connectivity, AI research funding, community events, and startup credits. ## AWS Transform Reaches Its First Anniversary - AWS Transform launched a year earlier for modernizing .NET, mainframe, and VMware workloads. - New capabilities include: - Custom AWS-managed or user-defined code transformations - Language and framework upgrades - Performance optimization and code analysis - Full-stack Windows modernization - Mainframe reimagining and automated testing - In its first 12 months, customers: - Migrated hundreds of thousands of servers - Saved more than 1.6 million hours - Processed over 4.5 billion lines of code - AWS Transform agents are now available in Kiro, Claude, Cursor, and Codex. ## Major Product Launches - **Claude Platform on AWS:** Provides Anthropic’s native Claude APIs, console, and beta features through existing AWS accounts and billing. Anthropic operates the service, and customer data is processed outside the AWS security boundary. - **EC2 M3 Ultra Mac instances:** Use Apple M3 Ultra Mac Studio hardware with a 28-core CPU, 60-core GPU, 32-core Neural Engine, and 256 GB of unified memory. Compared with M4 Max instances, they offer more CPU, GPU, Neural Engine cores, and memory for parallel Xcode simulators and on-device machine learning. - **Redshift RG instances:** AWS Graviton-based instances run workloads up to 2.4 times faster than previous RA3 instances while costing 30% less per vCPU. They include a vectorized engine for Apache Iceberg and Parquet data. - **Bedrock Advanced Prompt Optimization:** Compares original and optimized prompts across as many as five models, helping users improve performance or migrate between models. - **AWS Security Agent repository scanning:** The preview feature analyzes entire codebases and generates fixes linked to specific files and lines. It is free for existing Security Agent customers during the preview. - **AWS Interconnect for OCI:** Enables private, resilient multicloud connections to Oracle Cloud Infrastructure. The same open specification already supports Google Cloud and is planned for Azure later in 2026. ## Research, Community, and Startup Updates - AWS is investing $110 million in the Build on Trainium program to give university researchers access to purpose-built AI chips. - Research at institutions including UC Berkeley, MIT, and Carnegie Mellon is open source, allowing improvements to benefit the broader developer community. - AWS Community Days 2026 will take place globally, with agendas organized by local developer communities. - The Kiro Startups Credit program has reopened, offering eligible organizations up to one year of Kiro Pro+ credits applied through AWS accounts. AWS’s latest updates emphasize managed AI tools, faster specialized hardware, automated modernization, and broader support for developers and researchers. Organizations can particularly benefit by evaluating AWS Transform, Bedrock prompt optimization, new Mac instances, and the expanding multicloud connectivity options.

Read original(opens in new tab)
aws3 min readCurated summary

AWS Weekly Roundup: Amazon Bedrock AgentCore payments, Agent Toolkit for AWS, and more (May 11, 2026) | Amazon Web Services

The May 11, 2026 AWS roundup highlights growing support for autonomous AI agents, especially through Amazon Bedrock AgentCore’s managed payment capabilities. It also covers new tools for building secure agents on AWS, enhanced WorkSpaces automation, faster EC2 instances, and updates across Valkey, vector search, and agentic SRE operations. ## AgentCore Payments for Autonomous Agents - Amazon Bedrock AgentCore previewed managed payments for AI agents. - Agents can autonomously pay for: - APIs - MCP servers - Web content - Other agents - The service was developed with Coinbase and Stripe to handle billing, credentials, and compliance. - Developers can connect: - Coinbase CDP wallets - Stripe Privy wallets - Session-level spending limits help control agent transactions. - Potential applications include research agents purchasing live market data and coding agents calling paid APIs during execution. ## New Tools for Building AI Agents on AWS - **Agent Toolkit for AWS** provides production-ready tools and guidance at no additional charge. - It aims to reduce coding errors and token usage while adding enterprise security controls. - The toolkit replaces AWS Labs’ earlier MCP servers, plugins, and skills. - **AWS MCP Server** is now generally available as a managed, remote MCP server. - It provides secure, authenticated access to AWS services. - Agents interact through a small, standardized set of tools. - It is included in the Agent Toolkit for AWS. ## AI-Controlled Workspaces and New EC2 Instances - **Amazon WorkSpaces for AI agents** entered preview. - Agents can securely access and operate desktop applications. - Managed WorkSpaces environments provide governance and compliance controls. - The capability targets large-scale automation of everyday workflows. - New **EC2 M8idn/M8idb and R8idn/R8idb instances** use sixth-generation Intel Xeon processors and AWS Nitro cards. - They provide up to 43% better compute performance per vCPU than prior generations. - M8idn and R8idn offer up to 600 Gbps of network bandwidth. - M8idb and R8idb offer up to 300 Gbps of EBS bandwidth. ## Valkey and Vector Search Updates - Valkey, the community-driven Redis alternative, marked its second anniversary. - It has surpassed: - 100 million Docker pulls - 225 contributors - 1,500 pull requests - Valkey’s development pace is described as roughly twice that of Redis over the same period. - Valkey 9.0 is available through Amazon ElastiCache. - Amazon Aurora PostgreSQL-Compatible Edition can query billion-scale Amazon S3 Vectors using standard SQL. - Vector similarity searches can be combined with relational filters, such as price, inventory, or tenant, in a single query. ## Agentic Site Reliability Engineering - AWS DevOps Agent can be configured with “Spaces” that define investigation scopes. - It integrates with Amazon CloudWatch, Splunk, GitHub, and Slack. - Webhooks can trigger automated investigations. - The system can create mitigation plans and produce agent-ready specifications for coding tools such as Kiro. AWS’s latest updates emphasize autonomous agents that can transact, operate software, investigate incidents, and interact with cloud services while remaining governed by enterprise security and spending controls. Teams interested in these capabilities should start with the Agent Toolkit for AWS and explore the related previews and documentation.

Read original(opens in new tab)
aws4 min readCurated summary

AWS Weekly Roundup: What’s Next with AWS 2026, Amazon Quick, OpenAI partnership, and more (May 4, 2026) | Amazon Web Services

The AWS weekly roundup highlights a major shift toward agentic AI across Amazon’s products and its partnership with OpenAI. The biggest announcements include expanded Amazon Quick capabilities, four specialized Amazon Connect solutions, and OpenAI models and Codex becoming available through Amazon Bedrock. AWS also introduced new EC2 instances, agent optimization tools, Ruby 4.0 support for Lambda, and a transition plan from Amazon Q Developer to Kiro. ## What’s Next with AWS 2026 - AWS and OpenAI executives presented new ways businesses are using AI agents to automate operations. - The announcements centered on Amazon Quick, Amazon Connect, and deeper integration with OpenAI through Amazon Bedrock. ## Amazon Quick Expands Beyond Chat - A new desktop app, currently in preview, connects Quick to local files, calendars, and communications without requiring a browser. - Users can sign up with a personal email or Google, Apple, GitHub, or Amazon credentials; an AWS account is not required. - Quick can generate: - Documents - Presentations - Infographics - Images - New integrations include Google Workspace, Zoom, Airtable, Dropbox, and Microsoft Teams. - The preview “Build custom apps with Quick” feature lets users create intelligent applications, dashboards, and web pages using natural-language instructions. ## Amazon Connect Becomes Four Agentic AI Products - **Amazon Connect Decisions** applies Amazon’s operational expertise and supply-chain tools to help organizations move from reactive crisis management to proactive planning. - **Amazon Connect Talent** provides AI-led interviews, science-backed assessments, and consistent candidate evaluations for large-scale hiring. - **Amazon Connect Customer**, the renamed customer-service product, supports personalized voice, chat, and digital experiences, with conversational AI that can be configured in weeks. - **Amazon Connect Health** supports patient verification, appointment management, patient insights, ambient documentation, and medical coding. ## OpenAI Partnership Expands Through Amazon Bedrock - OpenAI models, including GPT-5.5 and GPT-5.4, are coming to Bedrock in limited preview. - Customers can use existing Bedrock APIs with AWS security, governance, and cost controls, without managing new infrastructure. - **Codex on Amazon Bedrock** brings OpenAI’s coding agent into AWS environments: - Authentication uses AWS credentials. - Inference runs through Bedrock. - Usage can count toward AWS cloud commitments. - Initial access includes the Codex CLI, desktop app, and Visual Studio Code extension. - **Bedrock Managed Agents powered by OpenAI** combines OpenAI models with AWS infrastructure and the OpenAI harness for long-running, production-oriented agent workflows. ## New EC2 Instance Families - **M8in and M8ib** instances are generally available, offering up to 43% higher performance than M6in and M6ib. - M8in provides up to 600 Gbps of network bandwidth. - M8ib provides up to 300 Gbps of EBS bandwidth. - **R8in and R8ib** target memory-intensive workloads such as commercial databases, data lakes, and SAP HANA. - **C8ine and M8ine** provide up to 2.5 times higher packet performance per vCPU and up to twice the internet-gateway throughput of their predecessors. - These network-optimized instances are designed for virtual firewalls, load balancers, security appliances, and 5G user-plane workloads. ## AgentCore and Lambda Updates - Bedrock AgentCore Optimization, in preview, adds: - Production-trace analysis - Recommendations for system prompts and tool descriptions - Batch evaluations - A/B testing against live traffic - Recommendations require human approval before deployment. - AWS Lambda now supports Ruby 4.0 as a managed runtime and container base image. - Ruby 4.0 support includes advanced logging features such as structured JSON logs, configurable log levels, and custom CloudWatch log groups. ## Amazon Q Developer Moves Toward Kiro - Amazon Q Developer IDE plugins and paid subscriptions will reach end of support on April 30, 2027. - New signups will be blocked beginning May 15, 2026. - Existing subscriptions can continue adding users until then. - Opus 4.6 will leave Q Developer Pro on May 29, 2026, while newer coding models such as Opus 4.7 will be exclusive to Kiro. - Q Developer experiences in the AWS Console, documentation, mobile app, Slack, and Microsoft Teams are unaffected. AWS’s direction is increasingly centered on managed AI agents integrated into everyday business workflows. Organizations adopting these services should evaluate the new Bedrock, Quick, and Connect capabilities while also planning migration from Q Developer to Kiro before the announced support deadlines.

Read original(opens in new tab)
aws3 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.

Read original(opens in new tab)
aws3 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.

Read original(opens in new tab)
aws2 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.

Read original(opens in new tab)
aws3 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.

Read original(opens in new tab)
aws3 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.

Read original(opens in new tab)
aws3 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.

Read original(opens in new tab)