# Best Practices Published articles for Best Practices. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Optimizing agent system prompts with Amazon Bedrock AgentCore DevFeed: [Optimizing agent system prompts with Amazon Bedrock AgentCore]() Original publisher: [Read original article]() Author: Han Ding Published: 2026-09-16T15:47:39Z Content type: article Language: en Sources: [Artificial Intelligence]() Topics: [Amazon Bedrock AgentCore](), [Prompt optimization](), [Prompt Engineering](), [Traces](), [Benchmark](), [A/B Testing](), [Automated prompt engineering]() Tags: [a-b-testing](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [benchmark](), [best-practices](), [evaluation](), [intermediate-200](), [open-source](), [prompt-optimization](), [system-prompts](), [traces]() ### AI overview This technical companion explains how Amazon Bedrock AgentCore's system prompt optimizer uses production agent traces and reward signals to propose revised system prompts. It describes the reflector engine, recommendation explanations, offline batch evaluation, online A/B testing, and promotion workflow, and reports benchmark results for Single Agent Reflector and the experimental open source Sub-Agent Reflector. ### Source excerpt AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This technical companion to the launch post explains how the system prompt optimizer's reflector engine works and shares benchmark results for the Single Agent and Sub-Agent Reflectors. ## Using static analysis in Python, JavaScript and more to make your system safer DevFeed: [Using static analysis in Python, JavaScript and more to make your system safer]() Original publisher: [Read original article]() Author: Khan Academy Published: 2018-07-26T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [JavaScript](), [Code quality](), [Python](), [Code review](), [Web Development](), [React]() Tags: [analysis](), [best-practices](), [code](), [code-quality](), [engineering](), [eslint](), [formatting](), [frontend](), [infrastructure](), [javascript](), [lint](), [news](), [python]() ### AI overview This article describes how Khan Academy uses custom linters and static analysis across JavaScript, Python, and Kotlin to prevent known bad patterns, keep duplicated logic or shared interfaces synchronized, and enforce frontend migration practices. ### Source excerpt By Kevin Dangoor "Linting" source code to look for errors is nothing new (the original "lint" tool turned ... Read more ## Operationalizing least privilege: Automate IAM remediation through your CI/CD pipeline DevFeed: [Operationalizing least privilege: Automate IAM remediation through your CI/CD pipeline]() Original publisher: [Read original article]() Author: Luis Pastor Published: 2026-09-15T15:53:51Z Content type: tutorial Language: en Sources: [AWS Security Blog]() Topics: [AWS Identity and Access Management (IAM)](), [CI/CD](), [Infrastructure as code](), [AWS CloudFormation](), [Amazon Web Services]() Tags: [aws](), [aws-cloudformation](), [aws-cloudtrail](), [aws-iam](), [aws-identity-and-access-management-iam](), [aws-organizations](), [best-practices](), [ci-cd](), [expert-400](), [iam](), [infrastructure-as-code-iac](), [least-privilege](), [pull-request](), [security](), [security-blog](), [security-identity-compliance](), [technical-how-to]() ### AI overview This article describes an automated workflow for operationalizing least privilege in AWS. It explains how AWS IAM Access Analyzer identifies unused permissions and how remediation can be routed through different paths for infrastructure-as-code-managed, manually created, and unused IAM principals. ### Source excerpt The principle of least privilege is straightforward to articulate but challenging to maintain at scale. When teams first deploy applications to AWS, they often grant broader permissions than strictly necessary; it's faster to get things working, and the plan is always to tighten permissions later. But later rarely comes. Permissions accumulate, AWS Identity and Access [...] ## How Databricks' marketers use data 3x more with Genie, an AI analytics assistant DevFeed: [How Databricks' marketers use data 3x more with Genie, an AI analytics assistant]() Original publisher: [Read original article]() Author: Elizabeth Dobbs; Thomas Russell; Katy Yuan; Sydney Sundell Published: 2026-09-15T00:36:33Z Content type: article Language: en Sources: [Databricks]() Topics: [databricks](), [Artificial Intelligence](), [data](), [dashboards]() Tags: [ai](), [best-practices](), [dashboards](), [data](), [databricks](), [enterprise](), [governance](), [marketing](), [metrics]() ### AI overview Databricks describes how its marketing organization unified campaign, sales, CRM, web analytics, advertising, and other data in a governed lakehouse. It built Marge, a Genie Agents-based conversational analytics assistant that answers marketers' natural-language questions using governed enterprise data. The article says this approach helped the marketing department use data three times more often in decisions. ### Source excerpt Most marketing teams aspire to be data-driven. In practice, getting a trusted answer,... ## The generative AI customization spectrum: From prompt engineering to custom models on AWS DevFeed: [The generative AI customization spectrum: From prompt engineering to custom models on AWS]() Original publisher: [Read original article]() Author: Bhavya Sruthi Sode Published: 2026-09-14T15:47:12Z Content type: tutorial Language: en Sources: [Artificial Intelligence]() Topics: [Generative AI](), [Amazon Web Services](), [Prompt Engineering](), [Fine-tuning](), [Retrieval Augmented Generation (RAG)](), [Amazon Bedrock](), [foundation-models](), [Anthropic Claude](), [Nova](), [llama]() Tags: [advanced-300](), [ai](), [amazon-bedrock](), [anthropic-claude](), [aws](), [best-practices](), [chain-of-thought](), [fine-tuning](), [foundation-models](), [generative-ai](), [llama](), [nova](), [optimization](), [prompt-engineering](), [rag]() ### AI overview This AWS article presents an eight-step decision framework for customizing generative AI workloads. It compares progressively more involved approaches, including prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning, continued pre-training, and custom models such as Amazon Nova Forge, emphasizing that teams should start with the simplest approach and escalate when greater control or domain specificity is required. ### Source excerpt Pick the right generative AI customization approach on AWS with an 8-step decision framework, from prompt engineering and RAG to fine-tuning, continued pre-training, and Amazon Nova Forge. Start simple and escalate only when you must. ## How to Implement Feature Flags for Safe and Gradual Rollouts DevFeed: [How to Implement Feature Flags for Safe and Gradual Rollouts]() Original publisher: [Read original article]() Author: Abisoye Alli-Balogun Published: 2026-09-14T14:58:55Z Content type: article Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [feature flags](), [CI/CD](), [Deployment](), [Development](), [Tech Debt](), [Testing]() Tags: [architecture](), [best-practices](), [ci-cd](), [deployment](), [development](), [experimentation](), [feature-flags](), [how-to](), [tech-debt](), [testing]() ### AI overview This article explains how to implement feature flags for safe, gradual rollouts. It covers separating deployment from release, boolean toggles, percentage-based rollouts, user segmentation, experimentation, kill switches, lifecycle management, and common anti-patterns. ### Source excerpt Feature flags are one of the most powerful tools in a team's deployment arsenal. They decouple deployment from release, meaning your CI/CD pipeline can push code to production servers on every merge, ## How to scale Alloy as a central telemetry gateway: capacity planning, load testing, and production lessons DevFeed: [How to scale Alloy as a central telemetry gateway: capacity planning, load testing, and production lessons]() Original publisher: [Read original article]() Author: Fatjon Nebiu Published: 2026-09-12T11:22:06.456390Z Content type: tutorial Language: en Sources: [Grafana Labs blog on Grafana Labs]() Topics: [Grafana]() Tags: [analytics](), [auth](), [best-practices](), [cloud](), [cost](), [data](), [deployment](), [enterprise](), [grafana](), [grafana-alloy](), [grafana-cloud](), [how-to](), [kubernetes](), [logs](), [metrics](), [monitoring](), [observability](), [opentelemetry](), [platform](), [production](), [prometheus](), [scale](), [telemetry](), [testing](), [traces]() ### AI overview A practical guide to scaling Grafana Alloy as a centralized telemetry gateway. It covers capacity planning, load testing, and production considerations for collecting metrics, logs, and traces and forwarding them to Grafana Cloud. ### Source excerpt Running Alloy as a single-instance sidecar is simple. Running it as a centralized gateway that absorbs the full telemetry stream of an enterprise platform--tens of millions of active series, terabytes of logs per day, and tens of thousands of trace spans per second--is a different challenge altogether. To get it right, you need deliberate capacity planning, honest load testing, and a monitoring setup that doesn't rely on the very thing you're testing. As part of the Professional Services team here at Grafana Labs, we've seen this firsthand working with customers. In this post, we'll walk you through the best practices we follow to help them find success, and we'll do so using real, anonymized data from a recent engagement. We'll cover how we sized and load tested a production Alloy central collector deployment on Kubernetes, what the numbers looked like under real stress, and how the cluster behaves today handling the full production telemetry workload for a large enterprise platform. By the end, you should have a better sense for how you can create your own central gateway for collecting telemetry in Grafana Cloud. Why a central gateway? Before diving into numbers, it's worth explaining the pattern. In a central gateway setup, all telemetry from application teams--metrics, logs, and traces--flows to a shared Alloy fleet via OTLP or native Prometheus/Loki write protocols. Alloy buffers, processes, batches, and forwards everything to Grafana Cloud. This gives you several things that per-team sidecar deployments struggle to provide: A single control plane: Auth, rate limiting, and routing in one place so application teams don't need to manage Grafana Cloud credentials Centralized buffering: Ensure a transient Grafana Cloud slowdown doesn't immediately cause data loss at the source Cost visibility: Configure the gateway to only accept telemetry data containing the label or attribute that is mandatory for cost-attribution Protocol normalization: Send OTLP, Prometheus Remote ## Monitoring production agent lifecycle with AWS DevOps Agent and AgentCore Evaluations DevFeed: [Monitoring production agent lifecycle with AWS DevOps Agent and AgentCore Evaluations]() Original publisher: [Read original article]() Author: Meghana Ashok Published: 2026-09-11T18:26:38Z Content type: article Language: en Sources: [Artificial Intelligence]() Topics: [ai observability](), [AWS IAM](), [incident](), [Orchestration](), [telemetry]() Tags: [advanced-300](), [agent](), [agents](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [aws](), [aws-identity-and-access-management-iam](), [best-practices](), [devops](), [incident](), [infrastructure-monitoring](), [logs](), [metrics](), [monitoring](), [orchestration](), [production](), [tracing]() ### AI overview The article describes monitoring production multi-agent systems with Amazon Bedrock AgentCore Evaluations for continuous quality assessment and AWS DevOps Agent for autonomous infrastructure incident investigation. ### Source excerpt Multi-agent systems fail in ways traditional monitoring misses. This post presents a dual-layer approach to monitoring production agents: Amazon Bedrock AgentCore Evaluations for continuous quality scoring and AWS DevOps Agent for autonomous infrastructure investigation, shown on a four-agent airline reservation system. ## From zero-shot forecast to purchase order with Amazon Bedrock AgentCore DevFeed: [From zero-shot forecast to purchase order with Amazon Bedrock AgentCore]() Original publisher: [Read original article]() Author: Hyunsoo Kim, Ph.D. Published: 2026-09-11T14:08:01Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [AI Bots](), [Training AI Models](), [SDKs]() Tags: [advanced-300](), [agents](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [automation](), [best-practices](), [orchestration](), [strands-agents](), [time-series](), [training](), [zero-shot]() ### AI overview An architecture article on using Amazon Chronos2 zero-shot forecasting and Bedrock AgentCore multi-agent orchestration to turn demand forecasts into validated purchase orders without per-product model training. ### Source excerpt Combine zero-shot forecasting with Amazon Chronos2 and multi-agent orchestration on Amazon Bedrock AgentCore to turn demand forecasts into validated purchase orders. No per-product model training, with business rules, auditability, and cost that scales to zero. ## AI, Disruption, and Standards DevFeed: [AI, Disruption, and Standards]() Original publisher: [Read original article]() Author: L. Jeffrey Zeldman Published: 2026-09-10T16:12:17Z Content type: opinion Language: en Sources: [Jeffrey Zeldman]() Topics: [Artificial Intelligence](), [ai-governance](), [web-standards](), [Generative AI](), [MCP](), [a2ui](), [Accessibility]() Tags: [a2ui](), [accessibility](), [ai](), [ai-governance](), [appearances](), [architecture](), [best-practices](), [design](), [designers](), [ethics](), [formats](), [generative-ai](), [governance](), [mcp](), [open-source](), [standards](), [ux](), [video](), [web-standards](), [webstandards]() ### AI overview This article introduces a video panel on AI and standards featuring Jeffrey Zeldman and Patrick Neeman. The discussion connects lessons from the web standards movement to AI interfaces, focusing on fragmented user experiences, accessibility, interoperability, provenance, and the role of open-source and community efforts. ### Source excerpt Individually, we have very little power, but together we have a great deal of power. In response to a series of Medium articles by Patrick Neeman--like this one that addressed issues of AI governance, fairness, and standardization--publisher Louis Rosenfeld invited Patrick and me to come on his show and talk about AI and standards. A [...] The post AI, Disruption, and Standards appeared first on Jeffrey Zeldman Presents. ## Laravel Queue Gotchas Collected from Experience DevFeed: [Laravel Queue Gotchas Collected from Experience]() Original publisher: [Read original article]() Author: Freek Van der Herten (freek@spatie.be) Published: 2026-09-10T12:06:27Z Content type: tutorial Language: en Sources: [freek.dev - all blogposts]() Topics: [Laravel](), [gotchas]() Tags: [best-practices](), [gotcha](), [gotchas](), [laravel](), [practical](), [queues]() ### AI overview An article about gotchas in Laravel queues that the author says they collected through experience. ### Source excerpt Laravel queues are great out of the box, until they bite. Over the years I've collected a few gotchas the hard way. Let me save you the headache. Read more ## Architecting SASE solutions using AWS Local Zones DevFeed: [Architecting SASE solutions using AWS Local Zones]() Original publisher: [Read original article]() Author: Lakshmi VP Published: 2026-09-09T20:36:09Z Content type: tutorial Language: en Sources: [AWS Compute Blog]() Topics: [networking](), [Network Services]() Tags: [advanced-300](), [architecture](), [aws](), [aws-local-zones](), [aws-marketplace](), [best-practices](), [edge](), [latency](), [routing](), [sase](), [security](), [zero-trust]() ### AI overview The article explains how AWS Local Zones can support SASE deployments by placing virtual security appliances closer to distributed users to reduce latency while maintaining security controls. ### Source excerpt Organizations with geographically distributed workforces face a trade-off between security and low-latency access. This post explores how to use AWS Local Zones and Secure Access Service Edge (SASE) solutions to deploy virtual security appliances closer to end users, covering key design principles, capacity planning, and traffic routing. ## From noise to signal: Monitoring Amazon DocumentDB like a pro DevFeed: [From noise to signal: Monitoring Amazon DocumentDB like a pro]() Original publisher: [Read original article]() Author: Deepak Deepesh Published: 2026-09-09T15:23:20Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Amazon DocumentDB](), [site-reliability-engineering](), [Amazon CloudWatch Logs](), [Database]() Tags: [amazon](), [amazon-cloudwatch](), [amazon-cloudwatch-logs](), [amazon-documentdb](), [best-practices](), [database](), [devops](), [expert-400](), [health](), [how-to](), [logs](), [metrics](), [monitoring](), [on-call](), [operations](), [performance](), [production]() ### AI overview A tutorial on monitoring production Amazon DocumentDB clusters with tiered alerts, CloudWatch metrics, Performance Insights, profiler logs, slow-query diagnosis, and garbage-collection health checks. ### Source excerpt Learn how to build a tiered alerting strategy for Amazon DocumentDB by organizing CloudWatch metrics into Critical, Warning, and Advisory tiers, diagnosing slow queries through three complementary lenses, and monitoring garbage collection health before it becomes a cluster-wide incident. ## Join our live webinars: Migrating from Atlassian to YouTrack DevFeed: [Join our live webinars: Migrating from Atlassian to YouTrack]() Original publisher: [Read original article]() Author: Elena Pishkova Published: 2026-09-09T12:51:07Z Content type: news Language: en Sources: [The JetBrains Blog]() Topics: [migration](), [AI Bots]() Tags: [ai-agents](), [atlassian](), [best-practices](), [data-center](), [demo](), [deployment](), [documentation](), [events](), [helpdesk](), [knowledge-base](), [livestreams](), [mcp](), [migration](), [project-management](), [tutorials](), [webinar](), [workflows](), [youtrack](), [youtrack-server]() ### AI overview JetBrains announces live webinars about migrating from Atlassian products to YouTrack. Sessions cover moving projects, users, and data from Jira, Confluence, and Jira Service Management, with migration demos, deployment and pricing information, customer stories, and regional sessions. ### Source excerpt Atlassian is discontinuing sales and support for Data Center products. If you're exploring alternatives, join us for a live session on September 30 to see how Jira-to-YouTrack migration works, including a demo and real customer stories. Register for the worldwide English-language webinar, hosted by the YouTrack team, or attend a regional session in Japanese hosted [...] ## Evaluation-First AI Agents: How Zepto Scales Customer Support on Databricks and MLflow DevFeed: [Evaluation-First AI Agents: How Zepto Scales Customer Support on Databricks and MLflow]() Original publisher: [Read original article]() Author: Gireesh Sreedhar KP; Deepak Dhankani; Eash Sharma Published: 2026-09-09T03:00:00Z Content type: article Language: en Sources: [Databricks]() Topics: [AI Agent](), [databricks](), [AI Infrastructure](), [real-time]() Tags: [agents](), [ai](), [ai-engineering](), [architecture](), [best-practices](), [blog](), [company](), [customer](), [customers](), [data-science-and-ml](), [data-strategy](), [databricks](), [efficiency](), [engineering](), [evaluation](), [india](), [industries](), [operations](), [platform](), [product](), [production](), [real-time](), [retail-consumer-goods](), [scale](), [workflows]() ### AI overview This Databricks and MLflow case study describes how Zepto uses an evaluation-first, multi-agent AI system to operate customer support at more than 100,000 tickets per day. It focuses on the system architecture, evaluation framework, quality gate, and development and production loops used to improve reliability as volume, product categories, languages, and failure modes expand. ### Source excerpt Zepto's Push for Reliable, Real-Time Customer SupportZepto is one of India's fastest-growing... ## A Multi-Module Android Template with Kotlin Convention Plugins, Lint Rules, and Design System Tokens DevFeed: [A Multi-Module Android Template with Kotlin Convention Plugins, Lint Rules, and Design System Tokens]() Original publisher: [Read original article]() Author: Shamil Gulmetov Published: 2026-09-09T01:34:18Z Content type: tutorial Language: en Sources: [ProAndroidDev - Medium]() Topics: [Template](), [Android](), [Architecture & Design](), [Kotlin](), [Gradle](), [Jetpack Compose](), [Dependency injection](), [Automation](), [Refactoring](), [now-in-android]() Tags: [android](), [android-app-development](), [android-architecture](), [android-studio](), [architecture](), [automation](), [best-practices](), [build](), [compose](), [dependency-injection](), [gradle](), [how-to](), [jetpack-compose](), [kotlin](), [now-in-android](), [refactoring]() ### AI overview This tutorial presents an Android Architecture Template based on patterns from Google's Now in Android repository. It describes a multi-module structure with Gradle Version Catalogs, Kotlin Convention Plugins, Jetpack Compose design tokens and dark-theme support, dependency injection, custom Lint rules, and a terminal-based renaming tool. ### Source excerpt How to streamline your development workflow with pre-configured Kotlin Convention Plugins, custom Lint rules, and unified design system tokens. Creating a new Android application from scratch in modern engineering is rarely as simple as clicking File -> New -> New Project in Android Studio. Before writing a single line of business logic, developers face hours -- or even days -- of repetitive infrastructure setup: Configuring a scalable multi-module architecture. Setting up Gradle Version Catalogs and writing custom Kotlin Convention Plugins to eliminate build script duplication. Standardizing design tokens and dark theme support in Jetpack Compose. Wiring up Hilt Dependency Injection for Coroutine Dispatchers, network, and Application Scopes. Enforcing architectural boundaries and team coding standards using custom static analysis (Lint) rules. Google's official Now in Android (NiA) repository is the recognized gold standard for modern Android engineering. However, because NiA is a full-featured showcase app with domain logic (news feeds, authors, bookmarks, offline sync), using it as a starter kit is cumbersome: developers must strip out existing features while risking breaking build pipelines. This Android Architecture Template bridges that gap: a clean, production-ready starter kit that extracts NiA's best architectural patterns into an isolated foundation. To make it enterprise-ready with zero room for error, it includes a standalone automation tool. Instead of manual refactoring, run a single terminal command to rename and brand the entire architecture in seconds. Acknowledgments & Credits Core architectural decisions, build-logic convention plugins, and static analysis infrastructure in this template are directly inspired by Google's official Now in Android (NiA) repository. Rather than reinventing the wheel, this template focuses on developer ergonomics--making Google's best practices instantly usable out of the box. 1. Modular Project Architecture The repository ## 10+ best practices to improve your email deliverability DevFeed: [10+ best practices to improve your email deliverability]() Original publisher: [Read original article]() Author: Jesse Sumrak Published: 2026-09-09T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [email](), [SendGrid](), [API]() Tags: [best-practices](), [deliverability](), [domain](), [email](), [industry-insights](), [marketing](), [sendgrid](), [spam](), [spoofing](), [subscriber]() ### AI overview This tutorial explains email deliverability and presents more than ten practices for improving inbox placement, including domain authentication, double opt-in, non-spammy subject lines, list cleaning, and avoiding spam traps. It also distinguishes delivery from deliverability and discusses sender reputation and subscriber engagement. ### Source excerpt Email deliverability determines whether your messages reach inboxes or spam folders. Follow these 10+ best practices to improve your deliverability rates. ## Getting started with Oracle Database@AWS: A complete onboarding guide DevFeed: [Getting started with Oracle Database@AWS: A complete onboarding guide]() Original publisher: [Read original article]() Author: Raghu Soma Published: 2026-09-08T16:59:29Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Oracle Database](), [cloud-infrastructure](), [AWS IAM]() Tags: [aws](), [aws-marketplace](), [best-practices](), [database](), [guide](), [iam](), [infrastructure](), [intermediate-200](), [onboarding](), [oracle](), [oracle-database-aws]() ### AI overview A step-by-step guide to onboarding Oracle Database@AWS, covering service selection, AWS Marketplace offers, prerequisites, OCI tenancy linking, and IAM configuration before provisioning. ### Source excerpt A practical, step-by-step guide to getting Oracle Database@AWS up and running. It covers the five procurement and onboarding steps, from securing your AWS Marketplace offer through validating prerequisites, linking your OCI tenancy, and configuring IAM, so you can move from purchase to a provisioning-ready environment. ## AgentOps: How to build AI agents at scale DevFeed: [AgentOps: How to build AI agents at scale]() Original publisher: [Read original article]() Author: Matar Peles Published: 2026-09-06T18:44:36Z Content type: tutorial Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [AI Agent](), [Artificial Intelligence](), [Provisioning](), [Authorization](), [Cloud]() Tags: [agents](), [ai](), [ai-agents](), [best-practices](), [build-ai-agents](), [developer](), [how-to](), [platform](), [provisioning](), [workflow]() ### AI overview This article presents AgentOps as the practice of creating, running, and operating AI agents reliably in production and at scale. It recommends governing agents throughout their lifecycle, starting with an agent registry and a standardized golden-path workflow for creating new agents. The proposed workflow captures an agent's purpose and dependencies, obtains approval for sensitive access, creates scoped service accounts with minimum permissions, provisions the agent on a selected platform, and registers it. ### Source excerpt AgentOps is the practice of running AI agents reliably at scale. See what it covers, which teams own it, and where to start. ## Incident response guide for AWS CloudTrail investigations - Part 2 DevFeed: [Incident response guide for AWS CloudTrail investigations - Part 2]() Original publisher: [Read original article]() Author: Oscar Diaz Published: 2026-09-03T21:15:53Z Content type: article Language: en Sources: [AWS Security Blog]() Topics: [Incident response](), [AWS CloudTrail](), [AWS IAM](), [web applications]() Tags: [advanced-300](), [amazon-bedrock](), [aws](), [aws-cloudtrail](), [aws-identity-and-access-management-iam](), [best-practices](), [incident-response](), [security-blog](), [security-identity-compliance]() ### AI overview An incident-response guide for investigating AWS CloudTrail events through a multi-stage attack scenario. It traces an SSRF vulnerability on an EC2-hosted web application to IMDSv1 credential harvesting, IAM activity, and unauthorized Amazon Bedrock access across Regions. ### Source excerpt In Part 1 of this guide, we examined two common incident scenarios: cross-account Amazon Simple Storage Service (Amazon S3) data deletion with ransomware implications, and cryptocurrency mining deployed through AWS CloudFormation using exposed AWS Management Console credentials. We also introduced key incident response terminology and investigative frameworks for analyzing AWS CloudTrail events. In this second [...] ## Incident response guide for AWS CloudTrail investigations - Part 1 DevFeed: [Incident response guide for AWS CloudTrail investigations - Part 1]() Original publisher: [Read original article]() Author: Oscar Diaz Published: 2026-09-03T21:15:39Z Content type: tutorial Language: en Sources: [AWS Security Blog]() Topics: [AWS CloudTrail](), [Incident response](), [AWS IAM]() Tags: [advanced-300](), [analysis](), [aws-cloudtrail](), [best-practices](), [guide](), [incident-response](), [logs](), [security](), [security-blog](), [security-identity-compliance]() ### AI overview A practical guide to investigating suspicious AWS activity through CloudTrail logs. It covers scenarios such as cross-account unauthorized access, cryptocurrency mining, and AI service abuse, with investigation questions, annotated logs, and preventive lessons. ### Source excerpt AWS CloudTrail logs contain the evidence you need when investigating suspicious activity in your AWS environment, but knowing which fields matter and how to interpret them can mean the difference between surface-level analysis and uncovering the full scope of an incident. This guide walks you through real-world scenarios, showing you how to analyze CloudTrail events [...] ## Get to VMware Cloud Foundation Faster with VMware Pro Cloud Services DevFeed: [Get to VMware Cloud Foundation Faster with VMware Pro Cloud Services]() Original publisher: [Read original article]() Author: paula swanson Published: 2026-09-03T20:21:10Z Content type: article Language: en Sources: [VMware Blogs]() Topics: [Cloud]() Tags: [architectures](), [best-practices](), [cloud](), [cloud-infrastructure](), [cloud-services](), [infrastructure](), [modernization](), [private-cloud](), [vcf-professional-services](), [vmware](), [vmware-cloud-foundation]() ### AI overview The article presents VMware Pro Cloud Services as a way to deploy VMware Cloud Foundation faster and deliver a public-cloud experience on premises. It describes pre-packaged services for designing, deploying, configuring, integrating, and operationalizing a secure private cloud, using VMware reference architectures and practices developed through customer engagements. ### Source excerpt Public clouds have upped the ante when it comes to what we expect from private cloud solutions. Our smartphones and fast access to public cloud resources have conditioned us to expect instant access to what we need when we need it. Anything less feels antiquated and cumbersome, leaving your business users frustrated and disenchanted. To ... Continued The post Get to VMware Cloud Foundation Faster with VMware Pro Cloud Services appeared first on VMware Blogs. ## UX Conference November Announced (Nov 16 - Nov 19) DevFeed: [UX Conference November Announced (Nov 16 - Nov 19)]() Original publisher: [Read original article]() Published: 2026-09-03T04:50:49Z Content type: article Language: en Sources: [NN/g latest articles and announcements]() Topics: [AI Strategy](), [Artificial Intelligence](), [Accessibility]() Tags: [ai](), [best-practices](), [design](), [event](), [training](), [ux](), [web]() ### AI overview Live online UX training courses covering best practices, hands-on exercises, AI-enhanced design workflows, AI product strategy, user research with AI, AI experiences, design systems, and user experience analytics. Sessions are offered for Asia/AU and the USA, with optional UX Certificate specialties. ### Source excerpt Take up to 2 in-depth training courses, teaching user experience best practices for successful design. Live online training focused on long-lasting skills for UX professionals. Nov 16 - Nov 19, 2026 (Americas) | Nov 17 - Nov 20 (Asia/AU). ## UX Conference September Announced (Sep 14 - Sep 25) DevFeed: [UX Conference September Announced (Sep 14 - Sep 25)]() Original publisher: [Read original article]() Published: 2026-09-01T20:37:45Z Content type: article Language: en Sources: [NN/g latest articles and announcements]() Topics: [User interface design](), [AI Strategy](), [AI Chat]() Tags: [ai](), [best-practices](), [collaboration](), [design](), [evaluation](), [event](), [management](), [skills](), [training](), [ux]() ### AI overview NN/G announces live virtual UX training courses running September 14-25, 2026. The program covers UX best practices, design systems, usability testing, AI-related UX strategy and writing, collaboration, and certification pathways. ### Source excerpt Take up to 5 in-depth training courses, teaching user experience best practices for successful design. Training focused on long-lasting skills for UX professionals. September 14 - September 25, 2026. [Next page]()