## Summary
Bumps the node machine type from e2-small to e2-standard-2 to provide
more CPU and memory headroom for the cluster.
Also disables PodDisruptionBudgets (PDBs) for single-instance PostgreSQL
clusters to prevent node upgrade operations from becoming blocked.
## Changes
- Increase GKE node machine type from e2-small to e2-standard-2
- Set `enablePDB: false` for registry and Grafana PostgreSQL clusters
## Context
The machine type increase addresses resource constraints causing
deployment failures.
The PDB change prevents a specific issue where GKE node upgrades get
stuck when trying to drain nodes containing single-instance PostgreSQL
pods. With `minAvailable: 1` PDBs, evicting the only database instance
violates the availability requirement, blocking the drain operation
indefinitely. Disabling PDBs for these development/staging
single-instance databases allows node maintenance to proceed smoothly.
For production deployments requiring high availability, the instances
count should be increased to 3 with PDBs enabled.
---------
Co-authored-by: Claude <noreply@anthropic.com>
## Motivation and Context
Logs will help in fixing issues quickly, thereby reducing the downtime
and MTTD.
## How Has This Been Tested?
End to end local setup is tested
## Breaking Changes
No
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [ ] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [x] My code follows the repository's style guidelines
- [x] New and existing tests pass locally
- [ ] I have added appropriate error handling
- [ ] I have added or updated documentation as needed
## Additional context
- It handles container logs for mcp-registry pods.
- It supports k8sattributes resources which helps in identifying from
where the logs are coming.
- Supports victorialogs and it's plugin in grafana.
<img width="1129" height="383" alt="Screenshot 2025-09-15 at 1 43 51 AM"
src="https://github.com/user-attachments/assets/a560c541-721d-415c-a0a8-8cbe008c3af6"
/>
<img width="1134" height="703" alt="Screenshot 2025-09-15 at 1 44 34 AM"
src="https://github.com/user-attachments/assets/8b5b4132-9fc3-4b8e-8027-27c7787070f1"
/>
<img width="1134" height="727" alt="Screenshot 2025-09-15 at 1 46 10 AM"
src="https://github.com/user-attachments/assets/bcdb4d9d-cea1-4d88-8dd5-fa4cdb51031f"
/>
---------
Co-authored-by: Radoslav Dimitrov <radoslav@stacklok.com>
<!-- Provide a brief summary of your changes -->
## Motivation and Context
<!-- Why is this change needed? What problem does it solve? -->
The following PR addresses the feedback comments from #366
## How Has This Been Tested?
<!-- Have you tested this in a real application? Which scenarios were
tested? -->
## Breaking Changes
<!-- Will users need to update their code or configurations? -->
No
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [x] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [ ] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [ ] My code follows the repository's style guidelines
- [ ] New and existing tests pass locally
- [ ] I have added appropriate error handling
- [ ] I have added or updated documentation as needed
## Additional context
<!-- Add any other context, implementation notes, or design decisions
-->
Signed-off-by: Radoslav Dimitrov <radoslav@stacklok.com>
## Summary
- Removed Azure deployment section and references from README
- Updated project structure to reflect current GCP prod/staging configs
- Removed Azure Load Balancer annotation from ingress controller
- Updated provider documentation to show GCP and local options only
- Added monitoring.go to project structure documentation
This cleans up outdated Azure/AKS deployment configuration that is no
longer used, leaving only the current GCP-based deployment structure.
## Motivation and Context
Ensures that the redirect url is set properly when logging in with
Google
## How Has This Been Tested?
In staging
## Breaking Changes
None
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Motivation and Context
Consistency with https://staging.registry.modelcontextprotocol.io/ URL
format (i.e. `<env>.<service>`, rather than `<service>.<env>`
## How Has This Been Tested?
Deployed in staging
## Breaking Changes
Grafana URL changes, but it's only just launched so fine.
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [x] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Motivation and Context
After #328, the monitoring stack was failing to deploy because we hit
resource limits. This PR reduces the resource requests to a level
compatible with the cluster.
## How Has This Been Tested?
I've checked that everything still deploys happily in staging.
## Breaking Changes
None
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [x] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
This includes infra setup for metrics collection and visualisation
## Motivation and Context
It is important to have basic observability setup, so that common issues
can be identified quickly
## How Has This Been Tested?
- Tested on local
- Tested on one of the production setup
## Breaking Changes
No
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [X] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [X] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [X] My code follows the repository's style guidelines
- [X] New and existing tests pass locally
- [X] I have added appropriate error handling
- [ ] I have added or updated documentation as needed
## Additional context
- This includes set up of following components:
- Victoriametrics single node cluster for storing metrics data with
persistent storage configuration for local and production env.
- Vmagent with target discovery for mcp-registry pods with scrape
interval of 30s.
- Grafana for visualising metrics and setting alerts.
- Datasource of victoriametrics is pre-configured as config map
- Persistent volume for basic configuration
- Sqlite for local and Postgres for production setup for storing
dashboard, alerts etc details
## Metrics in action
<img width="1422" height="666" alt="Screenshot 2025-08-31 at 4 35 28 AM"
src="https://github.com/user-attachments/assets/e54ce846-653c-4fa3-aa7a-fe277f0810e6"
/>
---------
Co-authored-by: Adam Jones <adamj@anthropic.com>
Co-authored-by: adam jones <adamj+git@anthropic.com>
## Summary
This PR implements OIDC authentication support for admin users,
specifically configured for Google Cloud Identity. The implementation
includes:
- Configurable OIDC authentication endpoints and validation
- Google Cloud Identity integration for admin access
- JWT token validation and user session management
- Deployment configuration updates for OIDC provider settings
Fixes#283
<!-- Provide a brief summary of your changes -->
Implements automated database backup functionality with Google Cloud
Storage integration, including retention policies and MinIO support for
local development.
## Motivation and Context
<!-- Why is this change needed? What problem does it solve? -->
This change adds critical database backup capabilities to ensure data
durability and disaster recovery. The solution provides automated
backups with configurable retention policies and supports both
production (GCS) and development (MinIO) environments.
## How Has This Been Tested?
<!-- Have you tested this in a real application? Which scenarios were
tested? -->
- Tested backup creation and restoration with MinIO in local development
- Verified GCS bucket lifecycle policies for automatic deletion after 60
days
- Tested backup retention and cleanup logic
## Breaking Changes
<!-- Will users need to update their code or configurations? -->
No breaking changes. This is an additive feature that doesn't affect
existing functionality.
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [x] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [x] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [x] My code follows the repository's style guidelines
- [x] New and existing tests pass locally
- [x] I have added appropriate error handling
- [x] I have added or updated documentation as needed
## Additional context
<!-- Add any other context, implementation notes, or design decisions
-->
- Implements 60-day retention period for backups as a safety net
- Uses GCS lifecycle rules for automatic cleanup
- Includes MinIO setup instructions for local development testing
- Port-forwarding commands updated for consistency across documentation
- Fixes#184
Fixes#228
## Motivation and Context
See #19
## How Has This Been Tested?
- Run locally
- Run in docker compose
- Run infra in minikube
- Unit and integration tests all passing :)
## Breaking Changes
Yes: users will not be able to access any data they used to have in
custom mongodb. We are accepting this breaking change, given the
registry is in experimental development status.
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [x] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [x] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [x] My code follows the repository's style guidelines
- [x] New and existing tests pass locally
- [x] I have added appropriate error handling
- [x] I have added or updated documentation as needed
## Additional context
I have not implemented connection pooling support for simplicity, and
because cloudnative-pg already provides built-in connection pooling with
pgBouncer so if we want it later we can switch to this endpoint easily.
## Motivation and Context
In staging (and prod, for now) we pull the `:latest` mcp-registry image.
But K8s won't actually change anything unless we recreate the pods.
This change ensures the workflow goes from docker -> staging -> prod,
and changes the annotation so that the pods are recreated each deploy.
This ensures they actually pull the latest version.
## How Has This Been Tested?
Deployed locally to minikube
## Breaking Changes
None
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [x] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [x] My code follows the repository's style guidelines
- [x] New and existing tests pass locally
- [x] I have added appropriate error handling
- [x] I have added or updated documentation as needed
Fixes#264. Adds endpoints:
```
/v0/auth/github # exchange a github token for a registry token that gives you access to namespaces io.github.username and io.github.org for your orgs
/v0/auth/none # get a registry token for namespace io.modelcontextprotocol.anonymous (only for testing/local dev purposes)
```
Updates `/v0/publish` to accept one of these registry tokens.
## Motivation and Context
See #264
## How Has This Been Tested?
- Running locally and getting a token from `/v0/auth/none` and then
publishing to `/v0/publish`
- Updating the integration tests that get a token and then publish, and
them passing
## Breaking Changes
This is a breaking change to the auth API. This is fine for registry
given it's not deployed yet.
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [x] Breaking change (fix or feature that would cause existing
functionality to change)
- [x] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [x] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [x] My code follows the repository's style guidelines
- [x] New and existing tests pass locally
- [x] I have added appropriate error handling
- [x] I have added or updated documentation as needed
## Additional context
<!-- Add any other context, implementation notes, or design decisions
-->
---------
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: adam jones <domdomegg@users.noreply.github.com>
The Always pull policy is needed for the latest tag to force Kubernetes
to pull the newest image on every pod creation, even if an image with
that tag already exists locally. Without this, pods might use outdated
cached versions since the latest tag is mutable and can point to
different images over time.
Adds the Pulumi code to:
- Deploy the registry (and associated services e.g. mongodb) to Google
Cloud Platform (GCP), on top of Google Kubernetes Engine (GKE)
- Sets up proper environments and secrets management
- Uses the real container image, now that it's published in #225. At the
moment attached to latest, we might want to pin the version later (or
perhaps always use `latest` in staging, and pin prod)
- Uses real domains (`staging.registry.modelcontextprotocol.io`) rather
than examples (``)
## Motivation and Context
Setting up infrastructure to deploy it. I set something up in Azure in
#227, although not super robust (e.g. no service accounts etc.). Think
we will use GCP as:
- the maintainers have experience with GCP, but none with Azure
- costs are quite low, and Anthropic is happy to cover them in the short
term
- means we only have to maintain one login system (just Google Cloud
Identity), not two (Google Workspace + Azure)
## How Has This Been Tested?
Deployed this to a staging and production cluster. Try it yourself at:
```bash
curl -H "Host: staging.registry.modelcontextprotocol.io" -k https://35.222.36.75/v0/ping
```
(will be sorting out domains very soon)
## Breaking Changes
NA - just adds support for GCP deployment
## Types of changes
<!-- What types of changes does your code introduce? Put an `x` in all
the boxes that apply: -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
## Checklist
<!-- Go over all the following points, and put an `x` in all the boxes
that apply. -->
- [x] I have read the [MCP
Documentation](https://modelcontextprotocol.io)
- [x] My code follows the repository's style guidelines
- [ ] New and existing tests pass locally
- [x] I have added appropriate error handling
- [x] I have added or updated documentation as needed
## Additional context
<!-- Add any other context, implementation notes, or design decisions
-->
Expected follow-ups:
- GitHub Action setup to deploy things to the cluster from GitHub, to
avoid gatekeeping to just the people with the secrets.
Original PR: #227
- Add Pulumi-based infrastructure as code for deploying MCP Registry to
Kubernetes
- Support for both local development (minikube) and Azure Kubernetes
Service (AKS)
- Complete deployment orchestration including:
- cluster setup: e.g. you point this at an Azure account, and it can set
up and manage the cluster for you. e.g. K8s version, number of nodes,
type of nodes, ...
- cloud agnostic K8s services: cert-manager, nginx-ingress
- app services: MongoDB, and registry application (currently using nginx
as a placeholder, blocked on #225 (as is #190). but should be a 1 line
change)
## How is this different to #190
- Supports cluster setup and management. This enables:
- Non-hosting maintainers managing many devops workflows (e.g. scaling
up the cluster, or bumping K8s versions). Without this, we'd need to
bug/page the organisation hosting the registry when we need these things
changed.
- Makes it easy to spin up things like staging/temporary clusters, as
well as enables contributors to replicate the stack exactly on their own
Azure accounts.
- Sets up cloud-agnostic services. For example, rather than using the
Azure-managed ingresses and CA, we install nginx-ingress and
cert-manager. This enables:
- Running the entire infra stack can also run locally (e.g. in minikube,
k3s, orbstack, colima) - making it much easier for contributors to test
changes to infra stuff.
- Moving between cloud providers much more easily, e.g. we could shift
from Azure to GCP/AWS/other with minimal hassle.
- Everything stays written in Go, rather than Helm templates. This means
we get things like type-checking etc. for free (which from my experience
makes AI tools wayyy better at editing K8s stuff), and contributors
don't need to learn a new language if they're already using Go.
## Testing
I've got this running well:
- locally in minikube
- on cloud in Azure (my personal Azure account)
<details><summary>Claude written architecture and security
review</summary>
<p>
## Deployment Review & Assessment
### Current Architecture Strengths
**Pulumi IaC Approach**
- Well-structured infrastructure as code using Pulumi
- Multi-provider support (AKS, local) with clean abstraction
- Good separation of concerns in `pkg/` directory
**Security Fundamentals**
- Non-root container execution (`appuser` with UID 10001)
- Secrets properly managed via Kubernetes secrets
- TLS/SSL certificate management with cert-manager and Let's Encrypt
### Critical Issues & High-Priority Improvements
**1. Production Deployment Not Ready** 🚨
The registry deployment uses `nginx:alpine` placeholder image instead of
the actual MCP registry:
- `deploy/pkg/k8s/registry.go:67` - TODO comments indicate incomplete
setup
- Health probes are commented out
- Port mapping doesn't match actual application (80 vs 8080)
**Fix:** Build and publish actual registry container image to GHCR,
update deployment
**2. Database Security Considerations** 🔒
- MongoDB deployed without authentication
- No backup/disaster recovery strategy
- Database credentials hardcoded
*Note: MongoDB is not exposed externally (ClusterIP service), so this is
not a critical security risk but should be addressed for production.*
**3. Monitoring & Observability Gaps** 📊
- No Prometheus/Grafana monitoring stack
- No log aggregation (ELK/Loki)
- No application metrics/health dashboards
- No alerting configured
**4. High Availability & Reliability** ⚠️
- Single MongoDB instance (no replication)
- No persistent volume backup strategy
- Fixed 10Gi storage without growth planning
- Only 2 replicas for registry service
- No pod disruption budgets
- No horizontal pod autoscaling
### Recommended Improvements
**Immediate (High Priority)**
1. Complete Registry Deployment - Build proper container image pipeline,
enable health checks
2. Secure MongoDB - Add authentication credentials, implement backup
strategy
**Medium Priority**
3. Add Monitoring Stack - Prometheus, Grafana deployment
4. Security Hardening (Nice to Have) - RBAC policies, Network Policies,
Pod Security Standards
5. CI/CD Pipeline Enhancement - Container image building/publishing,
automated deployment
**Lower Priority**
6. High Availability - MongoDB replica set, HPA for registry pods
7. Operational Excellence - Kubernetes dashboard, cost optimization
### Configuration Issues
- Production config has test credentials: `deploy/Pulumi.prod.yaml:4-5`
- Missing environment-specific resource sizing
- Hardcoded domain names (`example.com`)
The deployment setup shows good architectural foundations but needs
significant work before production readiness. The most critical issue is
the placeholder nginx container - priority should be completing the
actual registry application deployment before addressing the other
improvements. Security measures like RBAC and Network Policies are nice
to have but not strictly necessary given that MongoDB is not exposed
externally.
🤖 Generated with [Claude Code](https://claude.ai/code)
</p>
</details>
## Metadata
Working towards #91
---------
Co-authored-by: Claude <noreply@anthropic.com>
