u/InnerBank2400

I’m working through a design where each underlying system remains authoritative for its own resources, rather than putting another source of truth above everything.

The wider runtime only decides whether an operation has enough dependency state, readiness and verification to keep moving.

>The case I’m trying to pressure-test is partial execution. Say an operation spans several systems, three parts succeed and one fails. Each individual system may still be healthy, but the overall operation is incomplete.

Would you let the wider workflow block there, or does that eventually become another control layer operators have to fight with?

Interested in examples where this kind of boundary has worked badly in production.

Large network labs eventually reach the limits of a laptop or homelab. Keeping cloud compute running between sessions can also become expensive.

HybridOps.Core is an open-source MIT-0 workflow that deploys a private EVE-NG or GNS3 environment using your own Google Cloud account or Proxmox capacity.

>For learners without suitable local hardware, eligible new Google Cloud users can receive $300 of trial credit. Cost visibility and teardown between sessions keep more of that credit for active lab time.

It preserves lab definitions, QEMU overlays and each node-to-base-image map. On rebuild, declared bases are restored and overlays remapped; a committed overlay becomes the next base image.

The workflow includes:

• readiness and health checks
• deployment and private access
• lab images and guest networking
• archive and restoration
• cost-aware teardown

This allows cloud resources to be removed after a session without treating a large lab as one enormous backup file.

I am looking for EVE-NG and GNS3 users willing to test it with real topologies.

How large is your current lab, and how much is reusable base imagery versus changing node state?

>EVE-NG workflow:
https://docs.hybridops.tech/ops/runbooks/platform/blueprints/hyops-blueprint-eve-ng/

>GNS3 workflow:
https://docs.hybridops.tech/ops/runbooks/platform/blueprints/hyops-blueprint-gns3/

Need more RAM for EVE-NG/GNS3 labs? I built an on-demand cloud lab workflow

Large network labs eventually hit the same problem: laptop limits, homelab hardware limits, or paying for compute that sits idle most of the time.

I built a workflow that deploys EVE-NG or GNS3 in your own GCP account, lets you run the lab when needed, then removes the cloud resources afterwards.

Current workflow includes:

• automated EVE-NG/GNS3 deployment
• private access through GCP IAP
• preflight checks
• archive/restore so the lab can resume from its last saved state
• rebuild and destroy lifecycle

I’m looking for a few EVE-NG/GNS3 users to try it with real topologies and give feedback.

What size labs are you running today, and what is your current hardware limit?

EVE-NG workflow:
https://docs.hybridops.tech/ops/runbooks/platform/blueprints/hyops-blueprint-eve-ng/

Project / research context:
https://github.com/hybridops-tech/hybridops-core

The repo also contains the wider work around lifecycle management, validation and recovery for infrastructure operations.

Open to feedback, issues and contributions.

I am looking for practitioner views on a lifecycle problem, not a code review.

In many teams, temporary environments are treated as disposable until they quietly become important. They accumulate state, access paths, recovery assumptions, cost exposure and operational evidence. Then teardown becomes risky, but leaving them running also creates waste.

I built an open-source implementation that treats readiness, dependency order, access, health checks, cost visibility, state preservation and teardown as one runtime contract.

The question I am trying to validate is simple:

>What evidence should exist before a system is allowed to destroy or rebuild an environment that may contain useful state?

If you have dealt with ephemeral environments, recovery runs, lab platforms or image lifecycles, I would value a short sanity check. I can share the relevant paper and GitHub discussion.

>NOTE: I am not asking for code review or implementation help. I am trying to sanity-check one operating-design question.

I’m developing HybridOps Core, an MIT-0 open-source research implementation for governed infrastructure operations, and I’m looking for practitioners willing to give a short, candid technical assessment of specific parts of the work.

The work examines whether infrastructure intent, environment policy, dependency ordering, preflight, execution, verification and run records can be expressed through a stable runtime contract across heterogeneous environments.

I’ve published several technical papers alongside the implementation and opened focused GitHub review threads for independent critique. The aim is not a code audit or unpaid QA. Reviewers are being asked to assess the architecture, operating assumptions, failure boundaries and practical relevance of the work.

Current review areas include contract-driven runtime design, image lifecycle and verification, reproducible network environments, infrastructure authority and source-of-truth boundaries, and recovery operations.

If one of those areas overlaps with your experience, comment with the area and I’ll send the relevant paper and review thread. Critical findings and counterexamples are welcome.

I’m developing HybridOps Core, an MIT-0 open-source research implementation for governed infrastructure operations, and I’m looking for practitioners willing to give a short, candid technical assessment of specific parts of the work.

The work examines whether infrastructure intent, environment policy, dependency ordering, preflight, execution, verification and run records can be expressed through a stable runtime contract across heterogeneous environments.

I’ve published several technical papers alongside the implementation and opened focused GitHub review threads for independent critique. The aim is not a code audit or unpaid QA. Reviewers are being asked to assess the architecture, operating assumptions, failure boundaries and practical relevance of the work.

Current review areas include contract-driven runtime design, image lifecycle and verification, reproducible network environments, infrastructure authority and source-of-truth boundaries, and recovery operations.

If one of those areas overlaps with your experience, comment with the area and I’ll send the relevant paper and review thread. Critical findings and counterexamples are welcome.

I’m developing a platform engineering and infrastructure automation implementation intended to inform my planned doctoral research.

I’m looking for 3–5 senior practitioners willing to give a candid industry evaluation of the architecture, practical value and obvious limitations.

The work covers contract-driven automation, preflight validation, reproducible execution, structured run records, and hybrid on-prem/cloud operations.

Stack: Python, Bash, Terraform/HCL, Ansible, Packer, Kubernetes, Proxmox, AWS, Azure and GCP.

This is not a request for code or a full audit. A short technical assessment is enough.

If this overlaps with your production experience, please comment or DM me and I’ll send a concise review brief.

I’m developing a platform engineering and infrastructure automation implementation intended to inform my planned doctoral research.

I’m looking for 3–5 senior practitioners willing to give a candid industry evaluation of the architecture, practical value and obvious limitations.

The work covers contract-driven automation, preflight validation, reproducible execution, structured run records, and hybrid on-prem/cloud operations.

Stack: Python, Bash, Terraform/HCL, Ansible, Packer, Kubernetes, Proxmox, AWS, Azure and GCP.

This is not a request for code or a full audit. A short technical assessment is enough.

If this overlaps with your production experience, please comment or DM me and I’ll send a concise review brief.

I’m developing a platform engineering and infrastructure automation implementation intended to inform my planned doctoral research.

I’m looking for 3–5 senior practitioners willing to give a candid industry evaluation of the architecture, practical value and obvious limitations.

The work covers contract-driven automation, preflight validation, reproducible execution, structured run records, and hybrid on-prem/cloud operations.

Stack: Python, Bash, Terraform/HCL, Ansible, Packer, Kubernetes, Proxmox, AWS, Azure and GCP.

This is not a request for code or a full audit. A short technical assessment is enough.

If this overlaps with your production experience, please comment or DM me and I’ll send a concise review brief.

I’m developing a research implementation intended to form the basis of my future doctorate in platform engineering and infrastructure automation.

The work covers contract-driven automation, preflight validation, reproducible execution, structured run records, and hybrid on-prem/cloud operations.

Stack: Python, Bash, Terraform/HCL, YAML, Ansible, Packer, Kubernetes, Proxmox, GCP, Azure and AWS.

I’m seeking senior Platform Engineering, DevOps, SRE, cloud or infrastructure professionals willing to provide a short independent evaluation by official email, GitHub comment or published cross-reference.

The feedback will help shape the doctoral direction and ensure the research is grounded in real operational practice.

Please comment or DM me if this aligns with your experience.

Thank you

I’m developing a research implementation intended to form the basis of my future doctorate in platform engineering and infrastructure automation.

The work covers contract-driven automation, preflight validation, reproducible execution, structured run records, and hybrid on-prem/cloud operations.

Stack: Python, Bash, Terraform/HCL, YAML, Ansible, Packer, Kubernetes, Proxmox, GCP, Azure and AWS.

I’m seeking senior Platform Engineering, DevOps, SRE, cloud or infrastructure professionals willing to provide a short independent evaluation by official email, GitHub comment or published cross-reference.

The feedback will help shape the doctoral direction and ensure the research is grounded in real operational practice.

Please comment or DM me if this aligns with your experience.

Thank you

I’m developing a research implementation intended to form the basis of my future doctorate in platform engineering and infrastructure automation.

The work covers contract-driven automation, preflight validation, reproducible execution, structured run records, and hybrid on-prem/cloud operations.

Stack: Python, Bash, Terraform/HCL, YAML, Ansible, Packer, Kubernetes, Proxmox, GCP, Azure and AWS.

I’m seeking senior Platform Engineering, DevOps, SRE, cloud or infrastructure professionals willing to provide a short independent evaluation by official email, GitHub comment or published cross-reference.

The feedback will help shape the doctoral direction and ensure the research is grounded in real operational practice.

Please comment or DM me if this aligns with your experience.

Thank you

Large EVE-NG and GNS3 labs can quickly outgrow a laptop or small home server. Buying more RAM or keeping a powerful server running all year does not always make sense when the capacity is only needed for occasional labs.

Cloud compute solves the hardware problem, but it introduces another one: forgetting an expensive VM and its supporting resources running after the lab is finished.

I’ve built repeatable HybridOps blueprints that deploy either EVE-NG or GNS3 inside your own GCP account, with the environment lifecycle and cost awareness built into the workflow.

The deployment provides:

• A private, nested-virtualisation-capable GCP VM
• A dedicated VPC with no public IP on the lab server
• Private access through GCP IAP
• Automated EVE-NG or GNS3 installation
• Guest internet access for lab nodes
• Preflight checks for project access and billing readiness
• Explicit lab archive and restore before teardown
• Deploy, access, rebuild and destroy commands
• Billing status and resource-age reminders so idle labs are less likely to be forgotten

The idea is to create the lab when extra compute is needed, preserve the topology, and destroy the cloud resources afterwards rather than paying for an always-on server.

EVE-NG deployment guide:

https://docs.hybridops.tech/ops/runbooks/platform/blueprints/hyops-blueprint-eve-ng/

Source:

https://github.com/hybridops-tech/hybridops-core

I’m looking for EVE-NG and GNS3 users to test the workflow with real labs. No coding is required.

If interested, comment with:

• EVE-NG or GNS3
• Rough number of nodes in your usual topology
• Your current laptop/server RAM
• Whether you have GCP trial credits available

Edit: the project is opensource; this is a call for testers and contributors

Large EVE-NG and GNS3 labs can quickly outgrow a laptop or small home server. Buying more RAM or keeping a powerful server running all year does not always make sense when the capacity is only needed for occasional labs.

Cloud compute solves the hardware problem, but it introduces another one: forgetting an expensive VM and its supporting resources running after the lab is finished.

I’ve built repeatable HybridOps blueprints that deploy either EVE-NG or GNS3 inside your own GCP account, with the environment lifecycle and cost awareness built into the workflow.

The deployment provides:

• A private, nested-virtualisation-capable GCP VM
• A dedicated VPC with no public IP on the lab server
• Private access through GCP IAP
• Automated EVE-NG or GNS3 installation
• Guest internet access for lab nodes
• Preflight checks for project access and billing readiness
• Explicit lab archive and restore before teardown
• Deploy, access, rebuild and destroy commands
• Billing status and resource-age reminders so idle labs are less likely to be forgotten

The idea is to create the lab when extra compute is needed, preserve the topology, and destroy the cloud resources afterwards rather than paying for an always-on server.

This is not a hosted free-lab service. It runs in your own GCP account, so normal GCP charges apply. The cost control comes from the disposable lifecycle, billing checks and archive-before-destroy workflow.

EVE-NG deployment guide:

https://docs.hybridops.tech/ops/runbooks/platform/blueprints/hyops-blueprint-eve-ng/

Source:

https://github.com/hybridops-tech/hybridops-core

I’m looking for EVE-NG and GNS3 users to test the workflow with real labs. No coding is required.

If interested, comment with:

• EVE-NG or GNS3
• Rough number of nodes in your usual topology
• Your current laptop/server RAM
• Whether you have GCP trial credits available

Edit: the project is opensource; this is a call for testers and contributors

Hi all,

I'm looking to connect with IT professionals who are open to exchanging LinkedIn recommendations.

I'm happy to review your profile/work and return the favour where appropriate.

If you're interested, feel free to DM me. Thanks!

I wrote up a reference scenario that uses VyOS as the routed edge across Proxmox, Hetzner, and GCP.

The design uses a stable VyOS edge pair on Hetzner, an on-prem VyOS VM on Proxmox, and IPsec/BGP between the surfaces. GCP peers into the Hetzner edge through HA VPN and Cloud Router.

The main point is not that this removes every dynamic-address problem. The on-prem peer still needs a stable identity or endpoint, such as a fixed IPv4 address or FQDN. The useful bit is that the site detail is contained at the site-extension layer. GCP and the wider platform route through the stable Hetzner edge instead of peering directly with the on-prem site.

Both sides run VyOS, so the operational shape stays consistent: route-based IPsec, BGP neighbour checks, import/export policy, and ordinary CLI inspection on each edge.

The implementation separates the lifecycle pieces:

1. build/publish the VyOS image artifact
2. seed it into Hetzner and Proxmox
3. provision the edge nodes
4. apply WAN policy
5. capture tunnel and BGP evidence before handoff

I would value VyOS-specific feedback on the wording and operating model, especially around:

1. whether the IPsec/BGP boundary is described cleanly
2. what checks should be captured before calling the edge path ready
3. what should link back to VyOS docs instead of being explained in this scenario

Article: https://hybridops.tech/blog/vyos-edge-hybrid-wan-hetzner/

Reference scenario: https://docs.hybridops.tech/reference-scenarios/hybrid-wan-edge-site-extension/

I have been working on a Proxmox automation path for a problem I kept running into: Terraform can create the VM, but that does not always mean the platform is safe to build on.

The current HybridOps path does a few things before downstream services run.

NetBox/IPAM owns VM addressing.

Proxmox SDN is treated as a shared foundation instead of separate per-environment drift.

The VM step fails if the SDN authority is missing or the VM never becomes reachable over SSH.

Templates can be smoke-tested by cloning, booting, checking guest-agent IP, then cleaning up.

RKE2 and PostgreSQL HA are then built on top of that same VM/IPAM/SDN path.

The part I would like feedback on is the operating model:

Would you trust NetBox/IPAM as the source of truth before VM creation, or do you prefer keeping Proxmox/Terraform as the main authority and syncing inventory after?

Docs: https://docs.hybridops.tech/reference-scenarios/authoritative-onprem-foundation/

Core repo: https://github.com/hybridops-tech/hybridops-core

Hi everyone,

I’m looking for a few people using AI coding tools who want to practise contributing to a real open-source project.

The project is HybridOps. It is around infrastructure automation, Terraform, Kubernetes/GitOps, Proxmox SDN, validation scripts, runbooks, and operational docs.

This is not a toy app. The useful work is more like testing quickstarts, improving docs, checking examples, adding validation notes, fixing small repo issues, and opening clean PRs.

You do not need to be a DevOps expert. Basic Git/GitHub helps because the work happens through issues, branches, commits, and pull requests. If Git is still new to you, that is okay too.

I’m especially interested in people who use AI tools but still want to learn the proper engineering side: review, test, explain the change, and ship it cleanly.

Repos:

https://github.com/hybridops-tech/hybridops-core

https://github.com/hybridops-tech/terraform-proxmox-sdn

If you’re interested, comment with what you want to practise: Python, Terraform, Kubernetes/GitOps, Bash, CI, docs, or testing.

Hi everyone,

I’m looking for a few senior DevOps, platform engineering, or infrastructure professionals to review my open source work and give honest feedback.

The work covers hybrid infrastructure operations, Terraform, Kubernetes, Proxmox SDN, runbooks, validation workflows, and operational docs.

I’m not looking for a generic endorsement. I’d value a real review: what looks strong, what is unclear, and what should improve.

If the work genuinely looks solid after review, I’d also appreciate a short LinkedIn recommendation based on what you saw.

Not sure if links are allowed here, so I can DM the project links to anyone interested.

Thanks.