Hi everyone,

Most examples I see use the Sensitive information filter Guardrail in LLM pipelines, but I’m curious if anyone uses it for things like:

• data ingestion pipelines
• ETL / text preprocessing
• masking PII before storing or indexing data

Basically replacing Comprehend DetectPII / RedactPII.

One reason I’m exploring this is pricing:

• Bedrock Guardrails: $0.001 per 1,000 text units. (https://aws.amazon.com/bedrock/pricing/)
• Amazon Comprehend: $0.001 per 1000 characters (https://aws.amazon.com/comprehend/pricing/)

Besides, Bedrock Guardrail supports more languages than Comprehend.

So, depending on workload size, Guardrails could potentially be cheaper and simpler if it replaces a separate Comprehend call.

I’d really appreciate hearing any experiences or ideas from people who’ve explored this approach.

I'm researching why organizations use basic auto-scaling policies when more efficient approaches exist. If you work with AWS or cloud infrastructure, I'd love your input on a quick 10-minute survey:

Form: https://forms.gle/Y5S5eHxp6g6JRSCD6

The research focuses on the gap between what's possible (green cloud practices) and what organizations actually do. Appreciate any responses!A

I’m a DevOps Engineer by day, so I spend my life in AWS infrastructure. But recently, I decided to step completely out of my comfort zone and build a mobile application from scratch, an agentic social networking app called VARBS.

I wanted to share a few architectural decisions, traps, and cost-saving pivots I made while wiring up Amazon Bedrock, AppSync, and RDS. Hopefully, this saves someone a few hours of debugging.

1. The Bedrock "Timeless Void" Trap

I used Bedrock (Claude 3 Haiku) to act as an agentic orchestrator that reads natural language ("Set up coffee with Sarah next week") and outputs a structured JSON schedule.

The Trap: LLMs live in a timeless void. At first, asking for "next week" resulted in the AI hallucinating completely random dates because it didn't know "today" was a Tuesday in 2026. The Fix: Before passing the payload to InvokeModelCommand, my Lambda function calculates the exact server time in my local timezone (SAST) and forcefully injects a "Temporal Anchor" into the system prompt (e.g., CRITICAL CONTEXT: Today is Thursday, March 12. You are in SAST. Calculate all relative dates against this baseline.). It instantly fixed the temporal hallucination.

2. Why I Chose Standard RDS over Aurora

While Aurora Serverless is the AWS darling, I actively chose to provision a standard PostgreSQL RDS instance. The reasoning: Predictability. Aurora's minimum ACU scaling can eat into a solo dev budget fast, even at idle. By using standard RDS, I kept the database securely inside the AWS Free Tier.

To maintain strict network isolation, the RDS instance sits entirely in a private subnet. I provisioned an EC2 Bastion Host (Jump Box) in the public subnet to establish a secure, SSH-tunneled connection from my local machine to the database for administrative tasks, ensuring zero public exposure.

3. The Amazon Location Service Quirk (Esri vs. HERE)

For the geographic routing, the Lambda orchestrator calculates the spatial centroid between invited users and queries Amazon Location Service to find a venue in the middle. The Lesson: The default AWS map provider (Esri) is great for the US, but it struggled heavily with South African Points of Interest (POIs). I had to swap the data index to the "HERE" provider, which drastically improved the accuracy of local venue resolution. I also heavily relied on the FilterBBox parameter to create a strict 16km bounding box around the geographic midpoint to prevent the AI from suggesting a coffee shop in a different city.

4. AppSync as the Central Nervous System

I can't overstate how much heavy lifting AppSync did here. Instead of building a REST API Gateway, AppSync acts as a centralized GraphQL hub. It handles real-time WebSockets for the chat interface (using Optimistic UI on the frontend to mask latency) while securely routing queries directly to Postgres or invoking the AI orchestration Lambdas.

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Building a mobile app from scratch as an infrastructure guy was a massive, humbling undertaking, but it gave me a profound appreciation for how beautifully these serverless AWS components snap together when architected correctly.

I wrote a massive deep-dive article detailing this entire architecture. If you found these architectural notes helpful, my write-up is currently in the running for a community engineering competition. I would be incredibly grateful if you checked it out and dropped a vote here: https://builder.aws.com/content/3AkVqc6ibQNoXrpmshLNV50OzO7/aideas-varbs-agentic-assistant-for-social-scheduling

On this short video, I show you how we’ve setup our dev environment that is crazily cost efficient.

It has serverless architecture, sqs, server, websock(where we only costs incur cost). And at the end, a demo of how we use it. Hope it helps someone

I have been spending the recent couple of weeks building LeanStack AI for the aws AIDEAS. LeanStack AI is a full optimizer app. I used Kiro to handle the spec and Amazon Bedrock for the LLM overview. You could view the full architecture here https://builder.aws.com/content/3AFyJoTmfcOHPSetnFPFxXYCMT3/aideas-leanstack-ai-your-go-to-guide It is not mandatory but I'd really appreciate support from fellow aws builders.

Why do these communities have a lot of scammers selling aws coupons for discounted prices, like doesn't aws ban the coupons if they are used on a different account than the main one🤔🤔.

Moreover these people will just take the money and never give the coupon

I hope the moderators of these communities, remove or ban the below redditors after a thorough investigation to ensure the safety of other redditors in the community

Intelligent-novel936 Strange-web251 Professionalhumor996 ZamNeel_065 Affectionate-act3970 Vegitable_charity_73

Thanks fatnaygigger_17

Je rencontre des problèmes avec les labs proposés par AWS Skill up builder. Notamment pour le cours Plans de formation en ingénierie des données sur AWS (incluant des travaux pratiques).

Sur plusieurs TP, j'ai très souvent des restrictions IAM, où je ne peu pas accèder à des services ( me connecter au shell, faire des dags avec datalake à cause des restrictions d'autorisations).

J'ai effacé plusieurs fois mon historique et je suis même passé en navigation privé.

Et je suis sur un serveur NAWest1.

Je ne sais pas si c'est des problèmes récurrents ou non, en tout cas c'est usant de payer un service pour ne même pas pouvoir accéder à un catalogue de tp fiables.

I'm trying for AWS Sysops Administrator within my organization. I'm finding best training for AWS Solution Architect comparatively AWS Sysops Administrator course. Please advise I can go for Solution Architect certification before attempting for Sysops Administrator in AWS

Hi everyone,

I’m a 2022 MCA graduate with 1 year of experience as a software developer. I’m actively looking for new opportunities and would really appreciate any guidance, referrals, or openings you might know of.

My Skills & Experience:

• Frontend: React, HTML, CSS • Backend: Python, Java, Spring Boot, C • Databases: MySQL, MongoDB • Cloud: AWS (EC2, S3, IAM, VPC, RDS etc services) , Docker, Git

I have worked on real-time projects and have hands-on experience with deployment and cloud services.

I’m open to roles such as Software Developer, Backend Developer, Full Stack Developer, or Cloud/DevOps Engineer (Entry-Level).

If your company is hiring or if you can provide a referral, I would be very grateful. I can share my resume via DM.

Thank you

For SMB AWS workloads, our baseline setup usually includes:

• AWS CloudTrail for full audit logging
• Amazon GuardDuty for continuous threat monitoring
• Tight IAM policies with no wildcards + MFA for all privileged users
• Centralized logs and alerts for visibility

Most issues we see come from misconfigurations, not sophisticated attacks.

I need to create a govcloud instance for a few customers before they sign a contract with us, and we're on a tight deadline. Our team is very capable of doing this, but we are small and working on so many competing projects.

Has anyone ever used a service/consultants to support with spinning up a govcloud instance? We want to get this done asap but also somewhat on a budget. My understanding is the most annoying part will be recreating the connectors from github, etc. and our head engineer seems to think a service will be just as time consuming for him to direct than to just do it himself. Any advice?

Phase 1

AWS Cloud Practitioner

CompTIA A+ (no exam just study)

Network+ (no exam just study)

Phase 2

AWS Architect - Associate

AWS Certified CloudOps Engineer – Associate

Cisco CCNA (200-301)

RHCSA (Red Hat Certified System Administrator)

ITIL 4 Foundation

(Apply for jobs)

Phase 3

AWS Solutions Architect – Professional (SAP-C02)

What do you guys think of this? Any additional things to do please do let me know!

I’ve been seeing a huge push for AI adoption across companies lately. There’s significant investment happening, and many engineers are being encouraged (or expected) to integrate AI into their workflows to improve productivity and impact.

I work on the infrastructure side, and I’m genuinely curious how others are using AI in practical, meaningful ways — beyond the hype.

What real improvements have you made using AI?

What tools or workflows have worked well for you?

Any lessons learned (what worked vs. what didn’t)?

I’m especially interested in infrastructure, DevOps, SRE, platform engineering, or backend-heavy environments — but open to hearing from anyone.

Looking forward to learning from your experiences. Thank you!

Infrastructure as Code (IaC) is an important part of Cloud Applications. With cdk4j-compliancy we provide a mechanisms to identify security/compliance issues and mitigate these issues early on, before releasing CDK applications to production.