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Show HN: Anyshift.io – Terraform "Superplan"
Hello Hacker News! We're Roxane, Julien, Pierre, Mawen and Stephane from Anyshift.io. We are building a GitHub app (and platform) that detects Terraform complex dependencies (hardcoded values, intricated-modules, shadow IT…), flags potential breakages, and provides a Terraform ‘Superplan’ for your changes.
To do that we create and maintain a digital twin of your infrastructure using Neo4j.
- 2 min demo : https://app.guideflow.com/player/dkd2en3t9r https://app.guideflow.com/player/dkd2en3t9r
- try it now: https://app.anyshift.io/ https://app.anyshift.io/ (5min setup).
We experienced how dealing with IaC/Terraform is complex and opaque. Terraform ‘plans’ are hard to navigate and intertwined dependencies are error prone: one simple change in a security group, firewall rules, subnet CIDR range... can lead to a cascading effect of breaking changes.
I’ve dealt in production with those issues since Terraform’s early days. In 2016, I wrote a book about Infrastructure-as-code and created driftctl based on those experiences (open source tool to manage drifts which was acquired by Snyk).
Our team is building Anyshift because we believe this problem of complex dependencies is unresolved and is going to explode with AI-generated code (more legacy, weaker sense of ownership). Unlike existing tools (Terraform Cloud/Stacks, Terragrunt, etc...), Anyshift uses a graph-based approach that references the real environment to uncover hidden, interlinked changes.
For instance, changing a subnet can force an ENI to switch IP addresses, triggering an EC2 reconfiguration and breaking DNS referenced records. Our GitHub app identifies these hidden issues, while our platform uncovers unmanaged “shadow IT” and lets you search any cloud resource to find exactly where it’s defined in your Terraform code.
To do so, one of our key challenges was to achieve a frictionless setup, so we created an event-driven reconciliation system that unifies AWS resources, Terraform states, and code in a Neo4j graph database. This “time machine” of your infra updates automatically, and for each PR, we query it (via Cypher) to see what might break.
Thanks to that, the onboarding is super fast (5 min):
1. Install the Github app
2. Grant AWS read only access to the app
The choice of a graph database was a way for us to avoid scale limitations compared to relational databases. We already have a handful of enterprise customers running it in prod and can query hundreds of thousands of relationships with linear search times. We'd love you to try our free plan to see it in action
We're excited to share this with you, thanks for reading! Let us know your thoughts or questions here or in our future Slack discussions.
Roxane, Julien, Pierre, Mawen and Stephane!
- estellebotbol 2y agoAmazing product addressing a truly real pain point—such a game-changer. The team is also stellar. Been hoping to see something like this for a while. Excited to see the impact, this will definitely be big!
- fasten 2y agoThanks for your kind words!!
- PampelDee 2y agoSo cool!
- emmtold 2y agoCool post, thank you for sharing, it could be a useful use case indeed. You mention AI-generated code causing dependency issues. Are there plans to integrate AI-driven recommendations?
- fasten 2y agoThanks for the feedback! We already use AI in the PR to explain whats happening and the best practices to adopt. As for the code remediation part: most LLMs fail to generate the right IaC code thats adapted to your infra because they miss its general context (config, dependencies..). We are building first the deterministic part (the context) and once we have the context our plan is to add the fix/recommendation in the change.
- emmtold 2y agoOk focusing on context makes sense but I’d challenge the idea that LLMs inherently fail without it. Some teams have used fine-tuned models or hybrid workflows with partial context to generate useful IaC snippets
- fasten 2y agoAgreed 100%. LLMs are doing solid job at generating IaC but in a context where the person who use them knows what he/she's doing. In our case, remediaiton means an extra level of trust, where your infra is already super sensitive.