Vagrant SSH CTRL C Bug Workaround - Decoding DevOps

Hi everyone!

I'm new in my DevOps journey, following a Udemy course named Decoding DevOps, and for now I'm liking it a lot, the only thing that was quite annoying is that the vagrant ssh command would exit the ssh client whenever you sent a CTRL+C, I couldn't find a way around it apart from using the normal SSH client through your Git BASH, so I just made a simple tidy noscript that automatically gets all the info needed from the VM and creates an alias for simple ssh connecting. Here is my repo, it's the first time I'm doing something like this, I know its really simple but tbh having it work on my end made me very happy and I want to just share this somewhere.

https://github.com/jovanjungic/vssh-sync

https://redd.it/1puxrzo
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Building a deterministic policy firewall for AI execution — would love infra feedback

I’m experimenting with a control-plane style approach for AI systems and looking for infra/architecture feedback.



The system sits between AI (or automation) and execution and enforces hard policy constraints before anything runs.



Key points:

\- It does NOT try to reason like an LLM

\- Intent normalization is best-effort and replaceable

\- Policy enforcement is deterministic and fails closed

\- Every decision generates an audit trail



I’ve been testing it in fintech, health, legal, insurance, and gov-style scenarios, including unstructured inputs.



This isn’t monitoring or reporting — it blocks execution upfront.



Repo here: https://github.com/LOLA0786/Intent-Engine-Api



Genuinely curious:

\- What assumptions would you attack?

\- Where would this be hard to operate?

\- What would scare you in prod?



https://redd.it/1pv6ox2
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Mist: self-hostable PaaS for deploying apps on your own infrastructure

Over the past few months, me and a friend have been building Mist, a self-hostable PaaS aimed at people running their own VPS or homelab setups.
Mist helps you deploy and manage applications on infrastructure you control using a Docker-based workflow, while keeping things lightweight and predictable.

Current features:
- auto-deployments on git push
- Docker-based application deployments
- multi-user architecture
- domain and TLS management

The project is fully open source. There’s a fairly large roadmap ahead, and we’re actively looking for contributors and early feedback from people who self-host or build infra tools.

Docs / project site: https://trymist.cloud
Source code: https://github.com/corecollectives/mist

Happy to answer questions or hear suggestions.

We’re still relatively new to software development and are building this in the open while learning and iterating.

https://redd.it/1pv7pk9
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Devops or Devlopment as a fresher

I don’t have much in-depth knowledge about web dev like I know only basic html, css, did some vibe coded projects from scratch and deployed it on vercel. By this I got to know about how backend and frontent works. How different tech stack works like surface knowledge, react, angular, different backend frameworks like django fastapi, as well as middlerware and where they are used, as well as built tools like vue, runtime environment, crud databases, supabase, sql, hiding .env before pushing to git, different package managers, microservices, RESTapi integration as well as different api options, tier 2 and tier 3 web architecture difference, all because of curiosity and AI. Now If u tell me to code without AI I will know which tech stack to use, what to build but not how to build it as I don’t know the syntax of each lang but understand the logic behind the structure of the project.

I am confused as a 4th sem btech student tier 3, I m not much inclined towards web dev learning it from scratch as well as long codes but I like top down or big picture approach how different systems work and manages lot of interactions without breaking, how it scales and most importantly I like to automate task rather than writing long codes, so I got to know about devops which fits my interest as I know Linux, noscripting, networking, yaml and also interest in learning cloud computing.

So I wanted to ask if I should go for pure devops instead of development will I get entry level jobs and internships.

Your guidance will be much appreciated 🙏

https://redd.it/1pv6csu
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I’m building runtime “IAM for AI agents” policies, mandates, hard enforcement. Does this problem resonate?

I’m working on an MVP that treats AI agents as **economic actors**, not just noscripts or prompts and I want honest validation from people actually running agents in production.



The problem I keep seeing

Agents today can:

* spend money (LLM calls, APIs)
* call tools (email, DB, infra, MCP servers)
* act repeatedly and autonomously

But we mostly “control” them with:

* prompts
* conventions
* code



There’s no real concept of:

* agent identity
* hard authority
* budgets that can’t be bypassed
* deterministic enforcement



If an agent goes rogue, you usually find out **after** money is spent or damage is done.



What I’m building

A small infra layer that sits **outside** the LLM and enforces authority mechanically.



Core ideas:

* **Agent** = stable identity (not a process)
* **Policy** = static, versioned authority template (what **could** be allowed)
* **Rule** = context-based selection (user tier, env, tenant, etc.)
* **Mandate** = short-lived authority issued per invocation
* Enforcement = allow/block tool/MCP + LLM calls at runtime



No prompt tricks. No AI judgment. Just deterministic allow / block.



Examples:

* Free users → agent can only read data, $1 budget
* Paid users → same agent code, higher budget + more tools
* Kill switch → instantly block all future actions
* All actions audited with reason codes



What this is NOT

* Not an agent framework
* Not AI safety / content moderation
* Not prompt guardrails
* Not model alignment



It’s closer to IAM / firewall thinking, but for agents.



Why I’m unsure

This feels **obvious** once you see it, but also very infra-heavy.

I don’t know if enough teams feel the pain **yet**, or if this is too early.



I’d love feedback on:

1. If you run agents in prod: what failures scare you most?
2. Do you rely on prompts for control today? Has that burned you?
3. Would you adopt a hard enforcement layer like this?
4. What would make this a “no-brainer” vs “too much overhead”?



I’m not selling anything, just trying to validate whether this is a real problem worth going deeper on.

github repo for mvp (local only): [https://github.com/kashaf12/mandate](https://github.com/kashaf12/mandate)

https://redd.it/1pvat3j
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How do you automate license key delivery after purchase?

I’m selling a desktop app with one-time license keys (single-use). I already generated a large pool of unique keys and plan to sell them in tiers (1 key, 5 keys, 25 keys).

What’s the best way to automatically:

assign unused keys when someone purchases, and
email the key(s) to the buyer right after checkout?

I’m open to using a storefront platform + external automation, but I’m trying to avoid manual fulfillment and exposing the full key list to customers.

If you’ve done this before or have a recommended stack/workflow, I’d love to hear what works well and what to avoid.

Also, is this by chance possible on FourthWall?

https://redd.it/1pvhb5a
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Seeking a Mentor in DevOps for Guidance on Projects, Production Environments, and Managing Complexity

Hello, fellow DevOps enthusiasts!

I am actively looking for a mentor who can guide me through the intricacies of DevOps, particularly when it comes to managing real-world production environments and tackling the complexities that come with them. I’ve been exploring DevOps tools and concepts, but I feel that having someone with hands-on experience would greatly accelerate my learning.

Specifically, I'm looking for guidance on:

* Managing production environments at scale
* Optimizing CI/CD pipelines for larger projects
* Understanding and mitigating the complexities of infrastructure
* Best practices for automation, monitoring, and security in production
* Working on and improving existing projects with a focus on reliability and efficiency

If you have experience in these areas and would be willing to help me navigate the challenges, I would greatly appreciate your mentorship. I'm eager to learn, share ideas, and work on real-world projects that will enhance my skills.

Feel free to message me if you’re open to a mentorship opportunity, and I look forward to connecting with some of you!

Thanks in advance!

https://redd.it/1pvdqry
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Is there a book that covers every production-grade cloud architecture used or the most common ones?

Is there a recipe book that covers every production-grade cloud architecture or the most common ones? I stopped taking tutorial courses, because 95% of them are useless and cover things I already know, but I am looking for a book that features complete end-to-end IaC solutions you would find in big tech companies like Facebook, Google and Microsoft.

https://redd.it/1pvk0ni
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Would you consider putting an audit proxy in front to postgres/mysql

Lately I've been dealing with compliance requirements for on-prem database(Postgres). One of those is providing audit logs, but enabling slow query log for every query(i.e. log_min_duration_statement=0) is not recommended for production databases and pgAudit seems to be consuming too much I/O.

I'm writing a simple proxy which will pass all authentication and other setup and then parse every message and log all queries. Since the proxy is stateless it is easy to scale it and it doesn't eat the precious resources of the primary database. The parsing/logging is happening asynchronously from the proxying

So far it is working good, I still need to hammer it with more load tests and do some edge case testing (e.g. behavior when the database is extremely slow). I wrote the same thing for MySQL with the idea to open-sourcing it.

I'm not sure if other people will be interested in utilizing such proxy, so here I am asking about your opinion.

Edit: Grammar

https://redd.it/1pvm6qv
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Versioning cache keys to avoid rolling deployment issues

During rolling deployments, we had multiple versions of the same service running concurrently, all reading and writing to the same cache. This caused subtle and hard-to-debug production issues when cache entries were shared across versions.



One pattern that worked well for us was versioning cache keys \- new deployments write to new keys, while old instances continue using the previous ones. This avoided cache poisoning without flushing Redis or relying on aggressive TTLs.



I wrote up the reasoning, tradeoffs, and an example here:

https://medium.com/dev-genius/version-your-cache-keys-to-survive-rolling-deployments-a62545326220



How are others handling cache consistency during rolling deploys? TTLs? blue/green? dual writes?

https://redd.it/1pvow88
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🛡️ Built MCP Guard - a security proxy for Cursor/Claude agents (I'm the dev)

Hey everyone! 👋

I've been working on something for the past few weeks and wanted to share it here.

The problem I faced:
I use Cursor with MCP to interact with my databases. One day, I accidentally let my agent run with full read/write/delete access. I watched in horror as it started building queries... and I realized I had zero control over what it could do.

What if it runs DROP TABLE users instead of SELECT *?

What I built:
MCP Guard - a lightweight security proxy that sits between your AI agent and your MCP servers.

Features:

Block dangerous commands (DROP, DELETE, TRUNCATE, etc.)
Generate API keys with rate limits and RBAC
Full audit logs of every agent interaction
Sub-3ms latency
Why I'm posting here:
I'm launching the beta on Dec 28 and looking for feedback from actual users. Not trying to sell anything - the free tier gives you 1,000 requests/month with no credit card.

If you're using MCP with Cursor/Claude and have thoughts on security, I'd love to hear from you.

Link: https://mcp-shield.vercel.app

Happy to answer any questions! I'm the sole developer behind this, so AMA about how it works. 🔥

https://redd.it/1pvw25o
@r_devops

what actually helps once ai code leaves the chat window?



ai makes it easy to spin things up, but once that code hits a real repo, that’s where i slow down. most of my time goes into figuring out what depends on what and what i’m about to accidentally break.

i still use chatgpt for quick thinking and cosine just to trace logic across files. nothing fancy.

curious what others lean on once ai code is real.

https://redd.it/1pvwxey
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Securing the frontend application and backend apis

Hi all,

In am looking for a reliable solution to secure the frontend url and backend apis so that is only accisible to people who has our VPN. Is it possible to do so ? I am using AWS currently, how I can do that reliably. Please help!

https://redd.it/1pvwujj
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Throwback 2025 - Securing Your OTel Collector

Hi there, Juraci here. I've been working with OpenTelemetry since its early days and this year I started Telemetry Drops - a bi-weekly ~30 min live stream diving into OTel and observability topics.

We're 7 episodes in since we started four months ago. Some highlights:

AI observability and observability with AI (two different things!)
The isolation forest processor
How to write a good KubeCon talk proposal
A special about the Collector Builder

One of the most-watched so far is this walkthrough of how to secure your Collector - based on a blog post I've been updating for years as the Collector evolves.

https://youtube.com/live/4-T4eNQ6V-A

New episodes drop ~every other Friday on YouTube. If you speak Portuguese, check out Dose de Telemetria, which I've been running for some years already!

Would love feedback on what topics would be most useful - what OTel questions keep you up at night?

https://redd.it/1pw15e0
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Your localhost, online in seconds.Public URL for everyone

Tired of complex tunneling tools?

Portex cli exposes your localhost to the internet in seconds. Features secure tunnels with end-to-end encryption, one-click PIN protection for client demos, and a built-in traffic inspector to debug webhooks instantly.

No forced logins, just portex start. Works on macOS, Windows & Linux.

https://portex.space/

https://redd.it/1pvyzeb
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Cache npm dependencies

I am trying to cache my npm dependencies so every time my GitHub Actions runs, it pulls the dependencies from cache unless package-lock.json changes. I tried the code below, but it does not work (the npm install is still happening on every run):

build:

runs-on: ubuntu-latest

needs: security



steps:

- uses: actions/checkout@v3



- name: Set up Node.js version

uses: actions/setup-node@v4

with:

node-version: '14.17.6'

cache: 'npm'



- name: Cache node modules

uses: actions/cache@v3

with:

path: ~/.npm

key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}

restore-keys: |

${{ runner.os }}-node-



- name: npm install and build

run: |

export NODE_OPTIONS="--max-old-space-size=4096"

npm ci

npm run build

env:

CI: false

REACT_APP_ENV: dev



- name: Zip artifact for deployment

run: cd build && zip -r ../release.zip *



- name: Upload artifact for deployment job

uses: actions/upload-artifact@v4

with:

name: node-app

path: `release.zip`

https://redd.it/1pw5ars
@r_devops

What 2025 Taught Me About DevOps

As 2025 comes to an end, I’ve been reflecting on what actually changed for me as a DevOps Engineer.
\- Not the tools I use.
\- Not the certifications I hold.
But how I think about systems, failures, and tradeoffs.

This year brought up patterns I’ve now seen repeatedly across interviews, production incidents, and mentoring other engineers.

Here are the 10 lessons that stood out, starting with the one that matters most:

\- Most outages come from small configuration changes, not big mistakes, eg, AWS and Cloudflare outages.

\- Tools are just tools. Understanding systems is what separates engineers.

\- Platform engineering is becoming the default way teams scale safely.

\- GitOps is no longer optional in serious environments.

\- Certifications stopped being reliable signals on their own.

\- AI increases leverage, but only if fundamentals are solid.

\- Boring and proven technology continues to outperform trendy/fancy alternatives.

\- Cloud cost is now an engineering responsibility, not just finance.

\- Fundamentals (Linux, networking, Git, communication) outlast trends.

\- Protect your peace, or this field will eat you alive

None of these lessons came from theory.
They came from actual systems, real interviews, real failures, and real conversations with engineers at different stages of their careers.

If you’re heading into 2026 trying to decide what to focus on next, my advice is simple: Understand fundamentals, understand systems and services before tools, learn to communicate well, and remember to protect your peace.

Happy holidays, and may your deployments be ever in your favour. 🎄🧑🏽‍🎄

https://redd.it/1pw4ury
@r_devops

What checks do you run before deploying that tests and CI won’t catch?

Curious how others handle this.

Even with solid test coverage and CI in place, there always seem to be a few classes of issues that only show up after a deploy, things like misconfigured env vars, expired certs, health endpoints returning something unexpected, missing redirects, or small infra or config mistakes.

I’m interested in what manual or pre deploy checks people still rely on today, whether that’s noscripts, checklists, conventions, or just experience.

What are the things you’ve learned to double check before shipping that tests and CI don’t reliably cover?

https://redd.it/1pw5phr
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Scaling beyond basic VPS+nginx: Next steps for a growing Go backend?

I come from a background of working in companies with established infrastructure where everything usually just works. Recently, I've been building my own SaaS and micro-SaaS projects using Go (backend) and Angular. It's been a great learning experience, but I’ve noticed that my backends occasionally fail—nothing catastrophic, just small hiccups, occasional 500 errors, or brief downtime.

My current setup is as basic as it gets: a single VPS running nginx as a reverse proxy, with a systemd service running my Go executable. It works fine for now, but I'm expecting user growth and want to be prepared for hundreds of thousands of users.

My question is: once you’ve outgrown this simple setup, what’s the logical next step to scale without overcomplicating things? I’m not looking to jump straight into Kubernetes or a full-blown microservices architecture just yet, but I do need something more resilient and scalable than a single point of failure.

What would you recommend? I’d love to hear about your experiences and any straightforward, incremental improvements you’ve made to scale your Go applications.

Thanks in advance!

https://redd.it/1pw5uwx
@r_devops

Migrating legacy GCE-based API stack to GKE

Hi everyone!

Solo DevOps looking for a solid starting point

I’m starting a new project where I’m essentially the only DevOps / infra guy, and I need to build a clear plan for a fairly complex setup.

Current architecture (high level)

* Java-based API services
* Running on multiple Compute Engine Instance Groups
* A dedicated HAProxy VM in front, routing traffic based on URL and request payload
* One very large MySQL database running on a GCE VM
* Several smaller Cloud SQL MySQL instances replicating selected tables from the main DB (apparently to reduce load on the primary)
* One service requires outbound internet access, so there’s a custom NAT solution backed by two GCE VMs (Cloud NAT was avoided due to cost concerns)

Target direction / my ideas so far

* Establish a solid IaC foundation using Terraform + GitHub Actions
* Design VPCs and subnetting from scratch (first time doing this for a high-load production environment)
* Build proper CI/CD for the APIs (Docker + Helm)
* Gradually migrate services to GKE, starting with the least critical ones

My concerns/open questions:

* What’s a cost-effective and low-maintenance NAT strategy in GCP for this kind of setup?
* How would you approach eliminating HAProxy in a GKE-based architecture (Ingress, Gateway API, L7 LB, etc.)?
* Any red flags in the current DB setup that should be addressed early?
* How would you structure the migration to minimize risk, given there’s no existing IaC?

If you’ve done a similar GCE → GKE migration or built something like this from scratch:

* What would you tackle first?
* Any early decisions you wish you had made differently?
* Any recommended starting point, reference architecture, or pitfalls to watch out for?

Appreciate any insights 🙏

https://redd.it/1pw7evz
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Building my Open-Source 11labs Ops Tool: Secure Backups + Team Access

I am building an open-source, free tool to help teams manage and scale ElevenLabs voice agents safely in production.

I currently run 71 agents in production for multiple clients, and once you hit that level, some things become painful very fast: collaboration, QA, access control, backups, and compliance.

This project is my attempt to solve those problems in a clean, in-tenant way.

Advanced workflow optimization: Let senior team members run staging versions of their workflow and agent, do controlled A/B testing with real conversation QA, compare production vs. staging, and deploy changes with proper QA and approbation process.
Granular conversation access for teams: Filter and scope access by location, client, case type, etc. Session-backed permissions ensure people only see what they are authorized to see.
Advanced workflow optimization and QA: Run staging versions of agents and workflows, replay real conversations, do controlled A/B testing, compare staging vs production, and deploy changes with proper review.
Incremental backups and granular restore: Hourly, daily, or custom schedules. Restore only what you need, for example workflow or KB for a specific agent.
Agent and configuration migration: Migrate agents between accounts or batch-update settings and KBs across many agents.
Full in-tenant data sovereignty: Configs, workflows, backups, and conversation history stay in your cloud or infrastructure. No third-party egress.
Flexible deployment options: Terraform or Helm/Kubernetes Self-hosted Docker (including bare metal with NAS backups) Optional 100 percent Cloudflare Workers and Workers AI deployment

Demo (rough but shows the core inspector, workflow replay, permissions, backups, etc.):

Video: https://www.youtube.com/watch?v=Pzu2CVWnpl8

I'll push the code to GitHub early January 2026. Project name will change soon (current temp name conflicts with an existing "Eleven Guard" SSL monitoring company).

I am building this primarily for my own use, but I suspect others running ElevenLabs at scale may run into the same issues. If you have feature requests, concerns, or feel there are tools missing to better manage ElevenLabs within your company, I would genuinely love to hear about them. 😄

https://redd.it/1pwb44y
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