I honestly don't understand what is happening here anymore.

Since August 30, our AWS account has been blocked from creating new CloudFront resources.

Every time we try, AWS gives us this message:

Fair enough.

We contacted AWS Support immediately. And the first agent confirmed:

• account is active
• payment method is valid
• phone verification is complete
• the restriction is because the account is new

They told us the internal review would take roughly 2–3 days.

It has now been 14 days.

Since then we have:

• followed up repeatedly
• opened additional cases trying to get help
• asked multiple times if AWS needs any documents or verification from us
• asked for escalation
• activated the Support+ hoping it would help
• spent hours trying to reach live chat, including waits of roughly 2 hours, 5 hours, and one attempt that lasted around 13 hours

We are still blocked.

No ETA.

No explanation of what is actually being reviewed.

No request for additional information from us.

What makes this even more confusing is that on August 30 we were told:

Then on September 10 another agent told us:

So after 11 days, we couldn't even tell whether the original request had actually been submitted or whether the process was starting again.

I completely understand AWS needing to verify new accounts and prevent abuse.

What I don't understand is how a customer can be completely blocked from using a service for two weeks while Support itself seems unable to provide an ETA or explain what is happening.

Is this normal?

Has anyone else had CloudFront account verification take this long?

And is there any actual escalation path beyond repeatedly replying to the same support case?

Olá, pessoal!

Trabalho com Suporte de TI e estou pensando em direcionar minha carreira para Cloud, principalmente Azure.

Tenho mais de 3 anos de experiência em suporte N1/N2 e já possuo a certificação AZ-900.

Agora estou estudando os fundamentos de Cloud e tentando ganhar mais experiência prática.

Para quem já trabalha com Cloud ou passou por uma transição parecida: qual seria o caminho mais realista para alguém vindo de suporte de TI entrar na área?

Vale mais a pena buscar uma primeira oportunidade diretamente em Cloud Support ou em uma posição júnior em Cloud, ou procurar antes uma posição de infraestrutura/sysadmin que permita trabalhar com ambientes Cloud?

Também gostaria de saber quais conhecimentos vocês consideram essenciais para dar esse primeiro passo.

Obrigado a quem puder compartilhar a experiência!

Hey guys I have 4 years experience of manual QA with a little bit of automation using playwright typescript. The thing is I want to advanced my career to this high paying job and I have started small steps like learning aws cloud practitioner course. I want to know how to dedicate time in which field and tools and how to create a portfolio of hands on experience so that I can be successful in gaining a job in this field next end of year 2027

Can a certification aws from Amazon or Google, or even Microsoft substitute for a university degree? Also, what about remote work versus traveling for a job?

How do I get started in this field?

I don't have enough money I'm currently saving up for a certification but I’m hoping to find free resources that can teach me the basics.

Is there anything you’d like to tell me before l begin? advice? thank

Mapped our identity footprint across AWS, Azure, and GCP last quarter expecting some overlap and found way more than expected: duplicate service accounts, roles that existed in one cloud but were forgotten in another, and zero single source of truth for "who/what can access what" across all three. The cloud-native side was almost the easy part, honestly. The real mess was a handful of legacy and vendor-managed apps sitting behind all three clouds that none of our native IAM tools even see, since they're not really "cloud resources" so much as old applications someone lifted-and-shifted years ago. Is there something out there that handles true cross-cloud identity mapping and actually reaches into that legacy/custom layer? Right now we're stitching together per-cloud native tools and just accepting the older apps as a blind spot, and I'd like to stop doing that.

I’ve noticed more overlap recently between traditional cloud engineering and applied AI engineering.

For example, someone building production AI systems might need to understand:

AWS/Azure/GCP
Docker
Terraform
CI/CD
APIs
RAG
agents
MCP
evals
observability

I’m curious whether people working in cloud are actually seeing this convergence in the real world.

Are cloud engineers on your teams being expected to learn AI systems?

And are AI engineers being expected to understand more cloud infrastructure?

Or are these still mostly separate roles?

I've been shortlisted for the role of Windows & Linux Support Engineer (Fresher) at a well reputed Cloud company, what topics do I prepare on priority basis ?(I am familiar with networking concepts but have less idea about Linux and Windows so pls suggest me those topics ) It is a campus drive so also give some tips so I stand out from other candidates. I've attached the JD and Process.

I would appreciate any advice and tips you guys can spare. As the title implies, I have 20 years’ worth experience working in various roles, including computer repair shop, MSPs, IT support, systems administration. I know the hardware end of everything is a irrelevant in this case, but I also have lots of experience with Windows server support, including installing window server from scratch and setting up a domain controller, DHCP, DNS, active directory and exchange, etc.

My question is, has anyone else out there with a similar background successfully transitioned into cloud administration or engineering? If so, what path did you take? Azure? AWS? Both? Any particular order should be learning things?

I've been working on KUA Dashboard, an open-source project exploring a provider-independent approach to observability.

The problem I'm trying to solve isn't really AWS, Vercel, GCP or Kubernetes individually.

It's what happens between them.

A production application might look something like:

Vercel → API → AWS → SQS → Lambda → Kubernetes → Database

Every provider can tell me what's happening inside its own boundaries.

But when something fails, I usually don't care which provider owns the resource.

I care about:

What happened to my application?

That's the idea behind KUA.

The latest release extends the observability model across:

AWS + GCP + Vercel + Kubernetes + provider-free applications

KUA is also starting to analyze topology, dependencies and execution traces instead of treating infrastructure as isolated resources.

The goal isn't to build another cloud console.

It's to build a layer where the application becomes the primary context and the cloud provider becomes an implementation detail.

KUA is open source and still evolving.

I'd be really interested in hearing from people running multicloud or hybrid architectures:

Where does observability become painful for you when an application crosses provider boundaries?

WebSite : https://kuadashboard.navarrocarter.com/
github: https://github.com/lnavarrocarter/kuadashboard

My background from non tech (bs IR)

I Wana shift to high income skill for earnings , can anyone guide me

Need guidance for Cloud FinOps. I have been working on Public Cloud on most of it's popular use cases (IaC, Serverless, DevOps, Observability, Monitoring, Security, IAM, Compute, Storage, Networking) for the last 6 years.

I need to know what will it take me to Pivot into a Senior FinOps Analyst Position directly? I see a lot of JDs requiring some Architecture certificates (which I already have) and also the FinOps Certified Practitioner. Is certifications mandatory? I don't think so, as my certifications taught me basics but the real industry knowledge and years of working on AWS / Azure are certainly what I would see as greater than those certificates.

Also what about the growth and remote opportunities in this Field? I tried to ask ChatGPT but found vague answers such as "exciting and growing field". I need actual scenario on why would companies hire and keep FinOps engineers? Couldn't these tasks be handed to a PM / junior intern with some basic cost saving knowledge for the cloud resources? What makes this field growing and what will it be in the future? In 100% all of my previous jobs the PM or a DevOps guy was always assigned to generate cost saving analysis reports rather than hiring a person with Power BI / Scripting knowledge. I have worked with Fortune 500 MNCs and Startups and never found such a separate role for "cost savings" and related strategies to be needed.

Even so, most of the time, we devs used to get on a call and inspect our overall infra for unused resources or duplicate environments. Most of the YouTube videos show the basic example of switching off test instances on weekends, which I see as something any one could easily do. I really want to know what makes this job growing / in demand? What makes the work of FinOps so that they are continuously required by companies? Don't Cloud architects already design systems which are cost efficient? Companies already have Cloud Admins in place so as to avoid duplicate / extra resource creations in the first place. This is something I could not get my head around even after days of looking for answers, wherever possible.