
Alexander is a writer, traveler, and serial digital entrepreneur. He’s the founder of the Tushi, the Gen X personal growth newsletter Further, and offers small business advice at Unemployable.

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Tim Schupp


I needed a PostgreSQL setup on Kubernetes that is:

- allows automatic creation of db instances
- allow configuration based pre-defining users, passwords and configurations
- can be included into other helm charts as depencency
- single configuration, one-install, full setup approach

For this, [CloudNativePG Helm Chart](TODO) is one of the cleanest approaches I've found so far ( after the [Bitnami Postgsql Helm Chart being moved closed source]() ).

So this is the exact setup I currently use as a base template.
Everything below is copy/paste-ready and end-to-end reproducible.

### What this creates

- namespace: `app-db`
- cluster: `app-postgres`
- database: `app`
- app user: `appuser`
- app password: `apppass`
- readonly user: `readonly`
- readonly password: `readonlypass`
- table: `public.items`

### 0) Move to your project and export kubeconfig

```bash
export KUBECONFIG=./kubeconfig.yaml
kubectl get nodes
```

### 1) Install the CloudNativePG operator

```bash
helm repo add cnpg https://cloudnative-pg.github.io/charts
helm repo update
helm upgrade --install cnpg cnpg/cloudnative-pg --namespace cnpg-system --create-namespace
kubectl get pods -n cnpg-system
```

Wait until the operator pod is `Running` before continuing.

### 2) Create a manifest folder

```bash
mkdir -p cnpg-app-db
```

### 3) Create namespace manifest

```bash
cat > cnpg-app-db/namespace.yaml <<'EOF'
apiVersion: v1
kind: Namespace
metadata:
  name: app-db
EOF
```

### 4) Create app credentials secret

```bash
cat > cnpg-app-db/db-secret.yaml <<'EOF'
apiVersion: v1
kind: Secret
metadata:
  name: app-db-user
  namespace: app-db
type: kubernetes.io/basic-auth
stringData:
  username: appuser
  password: apppass
EOF
```

### 5) Create PostgreSQL cluster manifest

```bash
cat > cnpg-app-db/postgres-cluster.yaml <<'EOF'
apiVersion: postgresql.cnpg.io/v1
kind: Cluster
metadata:
  name: app-postgres
  namespace: app-db
spec:
  instances: 2
  imageName: ghcr.io/cloudnative-pg/postgresql:17
  storage:
    size: 10Gi
  bootstrap:
    initdb:
      database: app
      owner: appuser
      secret:
        name: app-db-user
      postInitApplicationSQL:
        - CREATE USER readonly WITH PASSWORD 'readonlypass';
        - GRANT CONNECT ON DATABASE app TO readonly;
        - CREATE TABLE IF NOT EXISTS public.items (id SERIAL PRIMARY KEY, name TEXT NOT NULL, created_at TIMESTAMPTZ DEFAULT NOW());
        - ALTER TABLE public.items OWNER TO appuser;
        - GRANT ALL PRIVILEGES ON TABLE public.items TO appuser;
        - INSERT INTO public.items (name) VALUES ('seed-row-from-bootstrap');
        - GRANT USAGE ON SCHEMA public TO readonly;
        - GRANT SELECT ON ALL TABLES IN SCHEMA public TO readonly;
        - ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO readonly;
EOF
```

### 6) Create full Python test script

```bash
cat > cnpg-app-db/test_db_query.py <<'EOF'
#!/usr/bin/env python3
import argparse
import os
import sys
from urllib.parse import quote_plus

import psycopg


def build_dsn(args: argparse.Namespace) -> str:
    if args.dsn:
        return args.dsn

    user = quote_plus(args.user)
    password = quote_plus(args.password)
    host = args.host
    port = args.port
    dbname = args.database
    return f"postgresql://{user}:{password}@{host}:{port}/{dbname}"


def main() -> int:
    parser = argparse.ArgumentParser(description="Run a test query against CloudNativePG")
    parser.add_argument("--host", default=os.getenv("PGHOST", "127.0.0.1"), help="PostgreSQL host")
    parser.add_argument("--port", default=os.getenv("PGPORT", "5432"), help="PostgreSQL port")
    parser.add_argument("--database", default=os.getenv("PGDATABASE", "app"), help="Database name")
    parser.add_argument("--user", default=os.getenv("PGUSER", "appuser"), help="Database user")
    parser.add_argument(
        "--password",
        default=os.getenv("PGPASSWORD", "apppass"),
        help="Database password",
    )
    parser.add_argument(
        "--dsn",
        default=os.getenv("DATABASE_URL"),
        help="Full PostgreSQL DSN. Overrides host/user/password options when set.",
    )
    args = parser.parse_args()
    dsn = build_dsn(args)

    try:
        with psycopg.connect(dsn) as conn:
            with conn.cursor() as cur:
                cur.execute("SELECT current_user, current_database(), version()")
                user_name, db_name, version = cur.fetchone()
                print(f"connected_as={user_name}")
                print(f"database={db_name}")
                print(f"version={version}")

                cur.execute("SELECT id, name, created_at FROM public.items ORDER BY id")
                rows = cur.fetchall()
                print(f"items_count={len(rows)}")
                for row in rows:
                    print(f"item id={row[0]} name={row[1]} created_at={row[2]}")
    except Exception as exc:
        print(f"connection/query failed: {exc}", file=sys.stderr)
        return 1

    return 0


if __name__ == "__main__":
    raise SystemExit(main())
EOF
```

### 7) Fresh redeploy (safe reset for this cluster)

If you've tested a few times and want a clean restart, run the block below.
This recreates the setup from the manifests above.

```bash
kubectl delete cluster app-postgres -n app-db --ignore-not-found=true
kubectl delete pvc -n app-db --all --ignore-not-found=true
kubectl delete secret app-db-user -n app-db --ignore-not-found=true
kubectl apply -f cnpg-app-db/namespace.yaml
kubectl apply -f cnpg-app-db/db-secret.yaml
kubectl apply -f cnpg-app-db/postgres-cluster.yaml
```

### 8) Wait until cluster is ready

```bash
kubectl wait --for=condition=Ready cluster/app-postgres -n app-db --timeout=600s
kubectl get cluster -n app-db
kubectl get pods -n app-db
kubectl get svc -n app-db
```

Expected result:

- `app-postgres` shows healthy and ready instances
- Pods `app-postgres-1` and `app-postgres-2` are `Running`
- Services exist: `app-postgres-rw`, `app-postgres-ro`, `app-postgres-r`

### 9) Optional direct `psql` test in the pod

```bash
kubectl exec -it -n app-db app-postgres-1 -- psql -U appuser -d app
```

Then run:

```sql
SELECT current_user, current_database();
SELECT * FROM public.items;
\q
```

### 10) Install Python dependency (`psycopg`)

```bash
python3 -m venv .venv
source .venv/bin/activate
pip install psycopg[binary]
```

### 11) Test app user (`appuser`) via RW service

Terminal 1:

```bash
kubectl port-forward -n app-db svc/app-postgres-rw 5432:5432
```

Terminal 2:

```bash
source .venv/bin/activate
python cnpg-app-db/test_db_query.py --host 127.0.0.1 --port 5432 --database app --user appuser --password apppass
```

### 12) Test readonly user (`readonly`) via RO service

Terminal 1:

```bash
kubectl port-forward -n app-db svc/app-postgres-ro 5433:5432
```

Terminal 2:

```bash
source .venv/bin/activate
python cnpg-app-db/test_db_query.py --host 127.0.0.1 --port 5433 --database app --user readonly --password readonlypass
```

### 13) Useful connection strings

```text
postgresql://appuser:apppass@app-postgres-rw.app-db.svc.cluster.local:5432/app
postgresql://readonly:readonlypass@app-postgres-ro.app-db.svc.cluster.local:5432/app
postgresql://appuser:apppass@127.0.0.1:5432/app
postgresql://readonly:readonlypass@127.0.0.1:5433/app
```

### Notes from my side

- Keeping bootstrap SQL in the cluster manifest is very convenient for small/medium setups.
- Splitting `rw` and `ro` service usage early helps avoid accidental write paths later in app code.
- For production, definitely swap the demo passwords and move secrets handling to your preferred secret manager flow.

That's it.
From here you have a reproducible CloudNativePG Postgres setup with:

- predefined users
- schema bootstrap
- seed data
- python connectivity test
- read/write and readonly validation paths

## Optional Add-On: DNS-01 cert flow

If you want to keep using your domain-based access (`test-db.<your-domain>.com`) with stronger trust setup across clients, a DNS-01 cert-manager flow is a good optional add-on.

At minimum:

1. install your DNS webhook solver
2. create a `ClusterIssuer`
3. issue certificate(s) and use them in your service exposure stack

I still keep this optional here, because CNPG already gives working Postgres TLS out of the box.

## Optional Add-On: tiny tailscale gimmick (cluster-to-cluster)

If you have tailscale operator on both clusters, you can expose this DB quickly via tailnet and consume it from another cluster using a simple `ExternalName` service.

High-level mini flow:

1. annotate exposed DB service with `tailscale.com/expose=true`
2. use tailnet hostname (`test-db.<tailnet>.ts.net`)
3. in cluster 2, create `ExternalName` -> that hostname

Useful when you just want quick private cross-cluster connectivity without extra public routing work.

Cheers Tim


A full copy/paste-ready walkthrough to install CloudNativePG, deploy PostgreSQL on Kubernetes, bootstrap users and tables, and verify with Python.

CloudNativePG PostgreSQL End-to-End Setup Guide


As privacy preserving communication options are vanishing rapidly, there remain only a few options for private secure communication.
While messaging services like Signal promise a good level of security and anonymity, its server is still managed by a corporate entity.

To truly control your own privacy and communication, you should consider joining a Matrix server hosted by a trusted party, or consider hosting one yourself.
This blog post will show how you can quickly setup and deploy a Matrix server on Kubernetes using [ananace's Helm charts](https://gitlab.com/ananace/charts).

### Performing the Helm Install

First, browse through the example values and the templates if required.
I managed to build a very minimal Matrix configuration via:

```bash
export KUBECONFIG=./kubeconfig.yaml 
helm repo add ananace-charts https://ananace.gitlab.io/charts
helm install matrix-synapse ananace-charts/matrix-synapse \
  --set serverName=example.com \
  --set publicServerName=matrix.example.com \
  --set wellknown.enabled=true
```

Or use a values file:

```yaml
serverName: example.com
publicServerName: matrix.example.com
wellknown:
  enabled: true
ingress:
  enabled: true
  tls:
    - secretName: matrix-synapse-crt
      hosts:
        - example.com
        - matrix.example.com
  hosts:
    - matrix.example.com
  className:
  annotations:
    kubernetes.io/ingress.class: "public"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
  includeServerName: true
```

Also **you should change the default postgresql credentials**:

```yaml
postgresql:
  enabled: true
  auth:
    password: <db-password>
    username: <db-username>
    database: <db-name>
```

Same things goes for the redis server:

```yaml
redis:
  enabled: true
  password: <new-redis-password>
```

### Configuring Upload and File Size Limits

```yaml
extraConfig:
  max_upload_size: 20M
ingress:
  enabled: true
  annotations:
    nginx.ingress.kubernetes.io/proxy-body-size: "20m"
    nginx.ingress.kubernetes.io/client-max-body-size: "20m"
```

### Creating First User

To be able to login to your Matrix server you'll have to actually register a first user.

##### 1. Retrieve the Main Matrix Pod

```bash
export KUBECONFIG=./kubeconfig.yaml
export NS=<matrix-namespace>
export POD_NAME=$(kubectl get pods --namespace "$NS" \
  -l "app.kubernetes.io/name=matrix-synapse,app.kubernetes.io/instance=matrix-synapse,app.kubernetes.io/component=synapse" \
  -o jsonpath="{.items[0].metadata.name}")
```

##### 2. Run the 'register_new_matrix_user' command

```bash
kubectl exec --namespace "$NS" "$POD_NAME" -- register_new_matrix_user \
  -c /synapse/config/homeserver.yaml \
  -c /synapse/config/conf.d/secrets.yaml \
  -u "<your-user-name>" \
  -p "<your-strong-admin-password>" \
  --admin http://localhost:8008
```

### Setting up Element as Matrix Web-UI

Now you have a Matrix server, [you may connect to it with any client](https://doc.matrix.tu-dresden.de/clients/).
But you might also want to be able to use it directly in the web.

Element Web is the official web client for Matrix and provides a user-friendly interface for accessing your Matrix server through a browser.

To deploy Element Web, you'll need to create a values file that configures the default server URL and ingress settings:

```bash
export KUBECONFIG=./kubeconfig.yaml
helm upgrade --install element-matrix ananace-charts/element-web \
  -f values_element_web.yaml
```

Here's an example `values_element_web.yaml` configuration:

```yaml
defaultServer:
  url: 'https://matrix.example.com'
  name: 'example.com'
ingress:
  enabled: true
  tls:
    - secretName: element-matrix-crt
      hosts:
        - element.example.com
  hosts:
    - element.example.com
  className: "public"
  annotations:
    kubernetes.io/ingress.class: "public"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
```

Make sure to replace `example.com` with your actual domain and adjust the `defaultServer.url` to point to your Matrix server's public URL.

### Backup Existing Matrix Server

```bash
export NS=default
export KUBECONFIG=./kubeconfig.yaml

# List PVCs
kubectl get pvc -n $NS

# Find PostgreSQL secret
kubectl get secret -n $NS -o name | grep -i postgres

# Get PostgreSQL pod name
export PG_POD=$(kubectl get pods -n $NS -l app.kubernetes.io/name=postgresql -o jsonpath='{.items[0].metadata.name}')

# Backup database (replace <db-password> with actual password from secret)
kubectl exec -n $NS "$PG_POD" -- sh -lc '
  export PGPASSWORD="<db-password>"
  /opt/bitnami/postgresql/bin/pg_dump -Fc -h 127.0.0.1 -U "<db-user>" "<db-name>"
' > postgres-FULL-$(date +%F).dump
```

### Backup All Matrix Media

```bash
export KUBECONFIG=./kubeconfig.yaml   # adjust path if needed
export NS=default
export RELEASE=matrix-synapse

# Get one synapse pod name
export SYNAPSE_POD=$(kubectl get pods -n $NS -l app.kubernetes.io/name=$RELEASE -o jsonpath='{.items[0].metadata.name}')

# Create tar.gz backup of media directory
kubectl exec -n $NS "$SYNAPSE_POD" -- sh -lc '
  set -e
  cd /synapse/data
  tar czf /tmp/matrix-media-backup.tar.gz media
  echo "Done."
'

# Copy backup from pod to local machine
kubectl cp $NS/$SYNAPSE_POD:/tmp/matrix-media-backup.tar.gz ./matrix-media-backup-$(date +%F).tar.gz
```

### Use Matrix bot to automate messaging

**1. Login a Matrix user**

```bash
curl -X POST "<YOUR-MATRIX-SERVER>/_matrix/client/v3/login" \
  -H "Content-Type: application/json" \
  -d "{
    \"type\": \"m.login.password\",
    \"identifier\": { \"type\": \"m.id.user\", \"user\": \"<user-name>\" },
    \"password\": \"<your-strong-admin-password>\"
  }" -o login-response.json -w "\nHTTP Status: %{http_code}\n" -s -S
```

Use the token to (2) list registered users (3) send a message to a registered user.


Secure Federated Chat: Self Host Matrix on Kubernetes


n8n is a flexible, open-source workflow automation tool that runs well on a small self-hosted cluster. Below is a lean, production-minded setup using a maintained Helm chart. This mirrors my usual pattern: keep it simple, make it reproducible, and put it behind ingress with TLS.

### Helm chart

Maintained chart: [`8gears/n8n-helm-chart`](https://github.com/8gears/n8n-helm-chart) — solid defaults, clear values, and active maintenance by the 8gears team. Kudos to the authors and maintainers for keeping queue mode, probes, lifecycle hooks, and ingress settings tidy and well-documented.

> If you’re new to Kubernetes on a VPS, see my Microk8s setup first: [/blog/microk8s-on-vps](/blog/microk8s-on-vps)

### Example values

Sanitize hosts and secrets for your environment. This example uses `ClusterIP` with `nginx` and `cert-manager`.

```yaml
persistence:
  enabled: true

image:
  repository: n8nio/n8n
  pullPolicy: IfNotPresent
ingress:
  enabled: true
  className: "nginx"
  annotations:
    kubernetes.io/ingress.class: "nginx"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
    nginx.ingress.kubernetes.io/proxy-body-size: "50m"
    nginx.ingress.kubernetes.io/backend-protocol: "HTTP"
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
  hosts:
    - host: n8n.t1m.me
      paths:
        - "/"
  tls:
    - hosts:
        - n8n.t1m.me
      secretName: n8n-example-com-tls
main:
  replicaCount: 1
  deploymentStrategy:
    type: Recreate
  persistence:
    enabled: true
    type: "dynamic"
    mountPath: "/home/node/.n8n"
    storageClass: "<your-default-storage-class>"
    size: 8Gi
    accessModes:
      - ReadWriteOnce
    annotations:
      helm.sh/resource-policy: keep
  nodes:
    builtin:
      enabled: true
      modules:
        - ws
      reinstallMissingPackages: true
  service:
    type: ClusterIP
    port: 5678
  config:
    n8n:
      host: "n8s.<your-domain>"
      protocol: "https"
      port: 5678
      editor_base_url: "https://n8s.<your-domain>"
      webhook_url: "https://n8s.<your-domain>"
      secure_cookie: "true"
      proxy_hops: 1
      log_level: "info"
      diagnostics_enabled: "false"
    db:
      type: "sqlite"
  secret:
    n8n:
      encryption_key: "CENSORED"
scaling:
  enabled: false
  worker:
    replicaCount: 0
  webhook:
    enabled: false
    replicaCount: 0
```

Notes:
- For quick single-node or hobby deployments, `sqlite` is fine. For multi-node or longevity, pick Postgres.
- Set `encryption_key` to a long, random value. Rotating it will invalidate existing encrypted credentials.
- If you want queue mode, enable `scaling.enabled` and configure Redis (internal `valkey` or external Redis) as per the chart docs.
- The `persistence` block ensures your workflows and credentials survive pod restarts.
- `helm.sh/resource-policy: keep` prevents accidental data loss during Helm uninstalls.

### Install/upgrade commands

Run with your `kubeconfig.yaml` and a dedicated namespace:

```bash
KUBECONFIG=./kubeconfig.yaml kubectl create ns n8n
KUBECONFIG=./kubeconfig.yaml helm uninstall n8n -n n8n
KUBECONFIG=./kubeconfig.yaml helm upgrade --install n8n oci://8gears.container-registry.com/library/n8n --namespace n8n -f n8n-values.yaml
```

After the release becomes `READY`, n8n should be reachable at `https://n8n.t1m.me` (or your configured host).

### Verify persistence before going live

**Critical**: Before creating workflows or adding credentials, verify that the persistent volume is working correctly. A failed volume mount means data loss on pod restarts.

Check the pod status and volume mount:

```bash
KUBECONFIG=./kubeconfig.yaml kubectl get pods -n n8n
KUBECONFIG=./kubeconfig.yaml kubectl describe pod -n n8n -l app.kubernetes.io/name=n8n
```

Look for:
- Pod status: `Running`
- Volume mount: `/home/node/.n8n` should be mounted from your PVC
- No volume-related errors in events

Test persistence by creating a simple workflow, restarting the pod, and verifying it still exists:

```bash
# Restart the pod to test persistence
KUBECONFIG=./kubeconfig.yaml kubectl delete pod -n n8n -l app.kubernetes.io/name=n8n
```

If your workflows disappear after the restart, the volume mount failed. Check your storage class and PVC status:

```bash
KUBECONFIG=./kubeconfig.yaml kubectl get pvc -n n8n
KUBECONFIG=./kubeconfig.yaml kubectl describe pvc -n n8n
```

### Credential management via CLI

n8n includes a CLI for bulk credential operations. Access the container and use these commands:

```bash
# Get into the running pod
KUBECONFIG=./kubeconfig.yaml kubectl exec -it -n n8n deployment/n8n -- /bin/sh

# Export all credentials (decrypted)
n8n export:credentials --all --decrypted --output=credentials.json

# Import credentials from file
n8n import:credentials --input=credentials.json
```

This is useful for:
- Backing up credentials before major updates
- Migrating between n8n instances
- Disaster recovery scenarios

**Security note**: The `--decrypted` flag exports credentials in plain text. Handle these files with extreme care and delete them immediately after use.

### Bulk restore / import n8n json workflows

For migrating workflows from another n8n instance or restoring from backups, you can bulk import JSON workflow files directly into your Kubernetes deployment.

Download and run the restoration script:

```bash
curl -fsSL https://raw.githubusercontent.com/tbscode/tims-blog-posts/refs/heads/main/assets/restore_workflow_json_files.sh -o restore_workflow_json_files.sh
chmod +x restore_workflow_json_files.sh
export KUBECONFIG=<your-kubeconfig>
SRC_DIR=<local-dir-containing-workflows>
./restore_workflow_json_files.sh $SRC_DIR
```

The script will:
- Find your running n8n pod automatically
- Upload all `.json` files from the specified directory
- Import each workflow using the n8n CLI
- Provide a summary of successful/failed imports
- Clean up temporary files

This makes it trivial to migrate workflows between n8n instances or restore from backups. The script handles all the Kubernetes complexity, so you just point it at a folder of JSON files.

> For automatic workflow and credential synchronization to GitHub, see my post on [synchronizing n8n workflows to GitHub](/blog/n8n-auto-saving-workflows-community-edition).

### Hardening checklist

- Switch to Postgres for production and enable persistent volumes.
- Keep `secure_cookie: true` and TLS on end-to-end; n8n stores credentials for integrations.
- Limit ingress access (e.g., IP allowlists) if you only need the editor from trusted networks.
- Set `N8N_USER_MANAGEMENT_DISABLED=false` and create dedicated users; enable 2FA on your IdP if applicable.
- Regularly backup your persistent volume and test restore procedures.
- Monitor PVC usage to avoid running out of storage space.

### About the chart authors

The chart is maintained by the 8gears team and contributors. The repository is here: [`8gears/n8n-helm-chart`](https://github.com/8gears/n8n-helm-chart). They’ve done a great job exposing n8n’s core options (readiness/liveness probes, deployment strategies, webhook and worker modes, and Redis/Valkey integration) in a clean values structure.

That’s it—small, clean, and easy to back up. Perfect fit for a self-hosted automation hub.

### Installing community nodes

Enable them once and you’re done:

1) Set the env var so the UI shows the Community Nodes menu: `N8N_ENABLE_COMMUNITY_NODES=true` (in the chart, add to `extraEnv`).  
2) Keep a short allowlist if you want: `N8N_COMMUNITY_PACKAGES_ALLOWLIST=["n8n-nodes-<package>"]`.  
3) Restart the pod, then in n8n go to *Settings → Community nodes → Install*. Paste the package name (e.g., `n8n-nodes-openai`), install, and reload the canvas.  
4) If your cluster egress is locked down, allow outbound HTTPS to `registry.npmjs.org` so installs don’t hang.


Minimal, repeatable setup to run n8n with TLS behind nginx ingress using the 8gears Helm chart.

Self-Hosted n8n on Kubernetes (Helm chart)


A quick, repeatable way to run WordPress on Kubernetes using the maintained TrueCharts chart. Small footprint, TLS via cert-manager, and a clean ingress.

### Chart

The TrueCharts WordPress chart ships via OCI and builds on the TrueCharts common library for consistent values and sane defaults.

- Chart page: [truecharts.org/charts/stable/wordpress](https://truecharts.org/charts/stable/wordpress/)

```bash
helm install wp oci://oci.trueforge.org/truecharts/wordpress \
  --namespace blogging \
  --create-namespace \
  -f values.wordpress.yaml
```

### Example values

Sanitize domains, credentials, and secret names for the target setup.

```yaml
ingress:
  main:
    enabled: true
    ingressClassName: public
    annotations:
      cert-manager.io/cluster-issuer: letsencrypt-prod
      nginx.ingress.kubernetes.io/proxy-body-size: "0"
    hosts:
      - host: wp.<your-domain>
        paths:
          - path: /
            pathType: Prefix
    tls:
      - hosts: [wp.<your-domain>]
        secretName: wp-<your-domain>-tls

wordpress:
  user: "<admin-username>"
  pass: "<strong-password>"

workload:
  main:
    replicas: 1
    podSpec:
      containers:
        main:
          env:
            WORDPRESS_EXTRA_WP_CONFIG_CONTENT: |
              define('WP_HOME','https://wp.<your-domain>');
              define('WP_SITEURL','https://wp.<your-domain>');

resources:
  requests:
    cpu: "500m"
    memory: "1Gi"
  limits:
    cpu: "4"
    memory: "8Gi"
```

Notes:

- Ensure `ingress` and `cert-manager` are installed and a `ClusterIssuer` named `letsencrypt-prod` exists.
- Set DNS for `wp.<your-domain>` to the ingress IP. After install, visit `https://wp.<your-domain>`.
- TrueCharts maintains a broad catalog and a shared common chart, providing consistent configuration across apps; the WordPress chart is kept up-to-date and is straightforward to automate.




Set up WordPress on a self-hosted Kubernetes cluster using the TrueCharts Helm chart.

WordPress on Kubernetes with TrueCharts (short guide)


Uptime-Kuma is a lightweight status and monitoring dashboard suited for homelabs or lean production clusters. Below is a minimal, repeatable setup to run it behind an ingress with TLS.

### Helm Chart

A maintained chart is available: [dirsigler/uptime-kuma-helm](https://github.com/dirsigler/uptime-kuma-helm), from [`@dirsigler`](https://github.com/dirsigler/uptime-kuma-helm).

```bash
helm repo add uptime-kuma https://helm.irsigler.cloud
helm repo update
helm upgrade my-uptime-kuma uptime-kuma/uptime-kuma \
  --install \
  --namespace monitoring \
  --create-namespace \
  -f values.uptime-kuma.yaml
```

### Preview

The following screenshot shows how Uptime-Kuma presents monitoring data for this blog (`blog.t1m.me`).

![Uptime-Kuma dashboard for blog.t1m.me](/static/assets/uptime-kuma-dashboard.png)

### Example values

Sanitize hosts/secrets for the target environment. This example runs as a `ClusterIP` behind `nginx` and cert-manager.

```yaml
ingress:
  enabled: true
  ingressClassName: public
  annotations:
    cert-manager.io/cluster-issuer: letsencrypt-prod
    kubernetes.io/ingress.class: public
    nginx.ingress.kubernetes.io/enable-cors: "true"
    nginx.ingress.kubernetes.io/cors-allow-origin: "https://<your-domain>"
    nginx.ingress.kubernetes.io/cors-allow-methods: "GET, OPTIONS"
    nginx.ingress.kubernetes.io/cors-allow-headers: "Content-Type"
    nginx.ingress.kubernetes.io/cors-allow-credentials: "false"
    nginx.ingress.kubernetes.io/proxy-read-timeout: "3600"
    nginx.ingress.kubernetes.io/proxy-send-timeout: "3600"
    nginx.ingress.kubernetes.io/server-snippets: |
      proxy_buffering off;
      proxy_cache off;
  hosts:
    - host: status.<your-domain>
      paths:
        - path: /
          pathType: Prefix
  tls:
    - secretName: uptime-kuma-tls
      hosts:
        - status.<your-domain>

persistence:
  enabled: true
  size: 5Gi

service:
  type: ClusterIP
  port: 3001

env:
  TZ: Europe/Berlin
```

A helper script is available for quick install and values generation:

- Download: [`setup_uptime_kuma.sh`](https://github.com/tbscode/tims-blog-posts/blob/main/assets/setup_uptime_kuma.sh)
- Make executable and run with env vars:

```bash
curl -fsSL https://raw.githubusercontent.com/tbscode/tims-blog-posts/refs/heads/main/assets/setup_uptime_kuma.sh -o setup_uptime_kuma.sh
chmod +x setup_uptime_kuma.sh
KUBECONFIG=./kubeconfig.yaml HOST="status.<your-domain>" ./setup_uptime_kuma.sh
```

Notes:

- Keep persistence on; monitors would otherwise need reconfiguration after pod restarts.
- On Microk8s, ensure `ingress` and `cert-manager` are enabled and a `ClusterIssuer` named `letsencrypt-prod` exists.
- The app becomes reachable at `https://status.<your-domain>` after DNS is set.

That’s it—small, stable, and easy to back up. Perfect for keeping a quiet eye on your stack.


### Alerts and hardening

- Enable certificate expiration notifications. Even with cert-manager in place (see the Kubernetes setup post), missed renewals often indicate underlying cluster health issues.
- Configure Twilio SMS alerts to receive notifications when an endpoint goes down and when it recovers. The following screenshot shows a brief incident where a page returned 503 and then back to 200 (minimal downtime during a controlled server migration):

![Incident timeline 503→200](/static/assets/kuma-uptime-incident-503-200.png)

- Enable 2FA for the admin account.

![Uptime-Kuma 2FA](/static/assets/2fa-uptime-kuma.png)

- Set up automated backups. Creating a daily full copy of `/app/data` and keeping a sensible retention schedule is recommended.




Tiny guide to deploy Uptime-Kuma on a self-hosted Kubernetes cluster using a maintained Helm chart.

Uptime Monitoring on Kubernetes by self-hosting Uptime-Kuma


## Intro 

Sentry is an incredibly nice error tracking tool; it can significantly increase the speed of bug fixing and debugging. It also offers a bunch of other features. You should also check out [their service](https://sentry.io)

Since I like to know how the stuff works and willing to take it appart; I would always prefer to self-host if I can. This also gives me more comfort about controlling my own data which by the way also aids GDPR compliance (though this is also possible using Sentry's service directly).

Fortunately, there [still is a Helm chart](https://github.com/sentry-kubernetes/charts/tree/develop). 
'Still', because for example: [the deprecated Posthog chart](https://github.com/PostHog/charts-clickhouse), but also the originally (officially maintained?) [sentry chart](https://github.com/helm/charts/tree/master/stable/sentry) seems deprecated now.

## Setup

I prepared a script that will:

1. Configure an ingress with a cluster issuer annotation to serve under a specific `$HOSTNAME`
2. Configure a Postgres password
3. Enable session recordings and its interface

## Installation

Use the following script to install Sentry:

```bash
./install_sentry_microk8s.sh \
  K8_NAMESPACE="<installation-namespace>" \
  RELEASE_NAME="<release-name>" \
  SENTRY_HOSTNAME="<...>" \
  SENTRY_HOSTNAME="<...>" \
  POSTGRES_PASSWORD="<...>" \
  SMTP_USERNAME="<...>" \
  SMTP_PASSWORD="<...>" \
  SMTP_PORT="<...>" \
  SMTP_FROM_EMAIL="<...>" \
  SENTRY_ADMIN_EMAIL="<...>" \
  SENTRY_ADMIN_PASSWORD="<...>"
```

I found out about having to set and update the admin Postgres password using a secret; [in this Github issue](https://github.com/sentry-kubernetes/charts/issues/554).
That's why we create a simple secret for the Postgres-password here:

```bash
apiVersion: v1
kind: Secret
metadata:
  name: postgres
  namespace: $K8_NAMESPACE
stringData:
  postgres-password: "$POSTGRES_PASSWORD"
```

For enabling the session feature and directly setting the Python config, I read [over here](https://github.com/getsentry/self-hosted/issues/2057) and [here](https://github.com/getsentry/self-hosted/blob/master/sentry/sentry.conf.example.py) and [here](https://github.com/sentry-kubernetes/charts/issues/918), ending up with:

```yaml
config:
  sentryConfPy: |
    SENTRY_FEATURES["organizations:session-replay"] = True
    SENTRY_FEATURES["organizations:session-replay-ui"] = True
```

Ingress setup follows a pretty standard procedure:

```yaml
nginx:
  ingress:
    annotations:
      cert-manager.io/cluster-issuer: "letsencrypt-prod"
    enabled: true
    hostname: $SENTRY_HOSTNAME
    ingressClassName: "public"
    tls: true
    extraTls:
      - hosts:
          - $SENTRY_HOSTNAME
        secretName: sentry-tls
```

As in some of my other scripts, I like to assume the cluster issuer is named `"letsencrypt-prod"`. To me, that's a reasonable sacrifice for adding fewer inputs ;).

Also, **to get the install to succeed** I needed to increase the `hooks.activeDeadlineSeconds`; otherwise, it would time out and the installation would fail.

```yaml
hooks:
  activeDeadlineSeconds: 3500
```

## Open Issues

Currently, I still experience one of the metrics services failing. I'm not sure about the impact yet, but tracking seems to work just fine:

```bash
microk8s kubectl logs sentry-snuba-metrics-consumer -n sentry
snuba.clickhouse.errors.ClickhouseWriterError: Method write is not supported by storage Distributed with more than one shard and no sharding key provided (version 21.8.13.6 (official build))
```

seems like an issue with my storage provisioning possibly; no impact seen so-far.


Self Hosted Error Tracking and Reporting using Sentry Kubernetes and Helm

Self Host Sentry using Helm


This guide illustrates the steps required to build, push, and deploy a Next.js app on Kubernetes using docker files for defining development and production Next.js images. These docker compose files allow for the building and pushing of images, with a Next.js config able to export static files. A simple helm chart will create deployment, service, and ingress for exposing our app.

> Template repo containing all the required code and configs can be [found on my github](https://github.com/tbscode/nextjs-helm-template).

### Prerequisites

This tutorial can also be adapted to work with any managed cluster as I've been using similar setups to quickly deploy Next.js apps for a while.

For your cluster you'll need:

- `cert-manger` cluster issuer with name `letsencrypt-prod` setup.
- `nginx-ingress` installed.
- `helm` installed.
- Public IP and Host Url connected.

Further, a private container registry is required.

> If you don't have a Kubernetes cluster ready follow [My Blog Post on Microk8s Private Cluster Setup](/blog/microk8s-on-vps).

### 1. Start a Next.js App

Begin by creating a simple Next.js app:

```
npx create-next-app@latest
What is your project named?  frontend
Would you like to use TypeScript? Yes
Would you like to use ESLint?  Yes
Would you like to use Tailwind CSS?  Yes
Would you like to use `src/` directory?  No
Would you like to use App Router? (recommended)  Yes
Would you like to customize the default import alias (@/*)?  No
```

We named the app `./frontend` so the respective folder is created.

### 2. Dockerize the Application

Two docker files can be created:

1. [`./frontend/Dockerfile`](https://github.com/tbscode/nextjs-helm-template/blob/main/frontend/Dockerfile): A development docker file that mounts frontend `./frontend` into the container for hot-reload.
2. [`./frontend/pro.dockerfile`](https://github.com/tbscode/nextjs-helm-template/blob/main/frontend/prod.dockerfile): A production docker file that statically builds the entire application and Next.js in a container.

The development docker file is straightforward:

```Dockerfile
FROM node:16-alpine

WORKDIR /frontend
COPY ./package.json .

RUN apk add curl

RUN npm i --save-dev

ENTRYPOINT ["npm", "run", "dev"]
```

Here, we execute `npm i` and then `npm run dev`. When mounted to the host, the `./node_modules` directory will also be present on the host.

The production docker file, which is based on the Next.js example docker file, can be found [here.](https://nextjs.org/docs/pages/building-your-application/deploying#docker-image)

```dockerfile
FROM node:16-alpine AS deps
RUN apk add --no-cache libc6-compat curl
WORKDIR /app

COPY package.json yarn.lock* package-lock.json* pnpm-lock.yaml* ./
RUN \
    if [ -f yarn.lock ]; then yarn --frozen-lockfile; \
    elif [ -f package-lock.json ]; then npm i; \
    elif [ -f pnpm-lock.yaml ]; then yarn global add pnpm && pnpm i --frozen-lockfile; \
    else echo "Lockfile not found." && exit 1; \
    fi

FROM node:16-alpine AS builder
WORKDIR /app
COPY . .
RUN apk add --no-cache curl
RUN npm i
RUN npm install --unsafe-perm -g sharp

ENV NEXT_TELEMETRY_DISABLED 1

RUN yarn build

FROM node:16-alpine AS runner
WORKDIR /app

ENV NODE_ENV production
ENV NEXT_TELEMETRY_DISABLED 1

RUN addgroup --system --gid 1001 nodejs
RUN adduser --system --uid 1001 nextjs

COPY --from=builder /app/styles ./styles
COPY --from=builder /app/public ./public

COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./
COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static

USER nextjs

EXPOSE 3000

ENV PORT 3000

CMD ["node", "server.js"]
```

### 3. Compose Files for Development

Creating two compose files can pave the way for convenience:

1. [`docker-compose.yaml`](https://github.com/tbscode/nextjs-helm-template/blob/main/docker-compose.yaml): A development compose file.
2. [`docker-compose.pro.yaml`](https://github.com/tbscode/nextjs-helm-template/blob/main/docker-compose.pro.yaml): A production/ Local Infrastructure compose file.

Development is now always as straightforward as executing `docker-compose up`.

### 4. Creating a Helm Chart

To effectively manage the deployments and services we require, we prefer to create a simple Helm chart that can easily be adapted, installed, and updated. Our Helm chart will need the following components:

1. Frontend Deployment
2. Registry Image Pull Secrets
3. Frontend Service
4. Ingress

```
microk8s helm create ./helm
cd ./helm/template && rm -rf *
```

Everything will be deployed to a `rootNamespace`.

We have reset the template and created a simple setup for now [`./helm/template/frontend.yaml`](https://github.com/tbscode/nextjs-helm-template/blob/main/helm/templates/frontend.yaml).

```yaml
{{- if .Values.registryAuth.use }}
kind: Secret
type: kubernetes.io/dockerconfigjson
apiVersion: v1
metadata:
  name: dockerconfigjson-github-com
  namespace: {{ .Values.rootNamespace }}
stringData:
  .dockerconfigjson: >
    {{
      (
        dict "auths"
        (
          dict {{ .Values.registryAuth.registry }}
          (
            dict "auth" .Values.registryAuth.token
          )
        )
      )
      |
      toJson
    }}
{{- end }}
```

We've created a simple flag `.Values.registryAuth.use` to check if registry authentication should be used (as we wouldn't need it for local microk8s deployment).
We use `.Values.registryAuth.use` to define the registry that should be used.

Now we define a simple deployment for our nextjs backend:

```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: frontend-container
  namespace: {{ .Values.rootNamespace }}
spec:
  replicas: 1
  selector:
    matchLabels:
      app: frontend-container
  template:
    metadata:
      labels:
        app: frontend-container
    spec:
      containers:
        - name: frontend-container
          image: {{ .Values.frontend.imageURL }}
          ports:
            - containerPort: 8000
          envFrom:
            - secretRef:
                name: frontend-secrets
      {{- if .Values.registryAuth.use }}
      imagePullSecrets:
        - name: dockerconfigjson-github-com
      {{- end }}
```

Note that we inject the `imageURL` and the registry pull secret if required. We go on to expose the port `3000` to the cluster through a simple service.

```yaml
apiVersion: v1
kind: Service
metadata:
  name: frontend-service
  namespace: {{ .Values.rootNamespace }}
  labels:
    app: frontend-container
spec:
  type: ClusterIP
  ports:
    - port: 3000
      targetPort: 3000
  selector:
    app: frontend-container

```

It's also advisable to create a secret that injects some general environment variables listed in `values.yaml:frontend.env.*`

```yaml
apiVersion: v1
kind: Secret
metadata:
  name: frontend-secrets
  namespace: {{ .Values.rootNamespace }}
type: Opaque
data:
{{- range $key, $value := .Values.frontend.env }}
  {{ $key }}: {{ $value | b64enc }}
{{- end }}
```

Finally, we set up an ingress:

```yaml
{{- if .Values.ingress.use }}
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: frontend-ingress
  namespace: {{ .Values.rootNamespace }}
  annotations:
    nginx.ingress.kubernetes.io/proxy-connect-timeout: '3600'
    nginx.ingress.kubernetes.io/proxy-read-timeout: '3600'
    nginx.ingress.kubernetes.io/proxy-send-timeout: '3600'
    nginx.ingress.kubernetes.io/server-snippets: |
      location /ws/ {
        proxy_http_version 1.1;
        proxy_redirect off;
        proxy_buffering off;
      } 
    {{- if .Values.ingress.certManager }}
    cert-manager.io/cluster-issuer: letsencrypt-prod
    {{- end }}
    kubernetes.io/ingress.class: public
spec:
  {{- if .Values.ingress.certManager }}
  tls:
    - hosts:
      - {{ .Values.ingress.host }}
    secretName: frontend-ingress-tls
  {{- end }}
  rules:
  - host: {{ .Values.ingress.host }}
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: frontend-service
            port:
              number: 3000
{{- end }}
```

We've introduced some flags to set up `tls` if required and some annotations to facilitate websocket forwards.

#### Configuration via `Values.yaml`

Finally, to tie this all together, we create some default [`values.yaml`](https://github.com/tbscode/nextjs-helm-template/blob/main/helm/values.yaml)

```yaml
rootNamespace: "default"
registryAuth:
  registry: "localhost:32000"
  use: false
  token: ""
ingress:
  use: true
  certManager: false
  host: "localhost"
frontend:
  imageURL: "localhost:32000/frontend:registry"
  env:
    HOSTNAME: "localhost"
```

This can be used to control all the configuration options we just created.

### 5. Testing on Local Microk8s

It's always good to ensure that we can also deploy the entire infrastructure locally. For this, we can use a simple local `microk8s` installation.

```
microk8s enable ingress dns registry
docker-compose -f docker-compose.pro.yaml build
docker-compose -f docker-compose.pro.yaml push
```

Since we set up the template `.env` earlier, we're already configured to push and pull the image from `localhost:32000/frontend:registry`.
So now, all we need to do is install our newly created chart:

```
microk8s helm install next-js-frontend ./helm/ --set rootNamespace="nextjsfront"
```

Since we also set up `$ROOT_URL="http://localhost"`, the ingress will be configured to route to `http://localhost`. Now let's check the browser:

![Next page on localhost via microk8s](/static/assets/nextjs-page.jpg)

### 6. Deploy to Private Cluster

For the capability to deploy to a private cluster, you'll need a package registry available.

> If you quickly want a cheap registry, you can [check out my blog post](/blog/microk8s-gittea) on deploying Gitea in a private k8s cluster.

#### Modify Environment for Production

Firstly, we need to modify the environment to push to our private registry with a modified tag.

```bash
rm .env
echo "FRONTEND_IMAGE=\"<your-frontend-image-url>\"" >> .env
echo "ROOT_URL=\"<your-host-url>\"" >> .env
```

An example of an image URL is `my-gitea.example.com/gitea-private-user/package:latest`.
A `ROOT_URL` could be something like `nextjs.example.com`.

Note that you can restore the old default `.env` at any time using `git checkout .env`.

We also need to encode access credentials to our registry so we can inject them into our secret.

```bash
echo "<your-registry-user>:<your-registry-password>" | base64
```

```bash
docker-compose -f docker-compose.pro.yaml build
docker-compose -f docker-compose.pro.yaml push
KUBECONFIG="./kubeconfig.yaml" microk8s helm install next-js-frontend ./helm/ \
  --set rootNamespace="nextjsfront" \
  --set ingress.use=true \
  --set frontend.imageURL="<your-frontend-image-url>" \
  --set certManager.use=true \
  --set registryAuth.use=true \
  --set registryAuth.registry="<your-registry-host>" \
  --set registryAuth.token="<base64-encoded-token>"
```

> It works perfectly! In fact, this blog was deployed using this exact technique. 

### 7. Repository Automations

Now, we have a simple process to deploy the repository using GitHub Actions. 
These actions can also run on your own runners using Gitea Actions.

We create one simple workflow [`.github/workflow/deploy.yaml`](https://github.com/tbscode/nextjs-helm-template/blob/main/.github/workflow/deploy.yaml)

```yaml
name: Deploy NextJs App
    
on:
  workflow_dispatch:

permissions:
  contents: read
  pages: write
  id-token: write

jobs:
  deploy:
    runs-on: ubuntu-latest
    name: Deploy NextJS App
    steps:
      - uses: actions/checkout@master
        with:
          token: ${{ secrets.BOT_PAT }}
          submodules: recursive
          ref: ${{ github.event.pull_request.head.sha }}
      - name: Setup Kubeconfig
        id: setup_kubeconfig
        run: |
          touch .env; rm .env
          echo "${{ secrets.KUBE_CONFIG_BASE64 }}" | base64 -d > kubeconfig.yaml
      - name: Setup Environment
        id: setup_env
        run: |
          touch .env; rm .env; touch .env
          RANDOM_STRING="$( openssl rand -hex 3 )"
          FRONTEND_IMAGE="${{ secrets.CONTAINER_REGISTRY }}/${{ secrets.GITTEA_USER }}/nextjs-app:build-$RANDOM_STRING"
          echo "FRONTEND_IMAGE=\"$FRONTEND_IMAGE\"" >> .env
          echo "frontend_image=$FRONTEND_IMAGE" >> $GITHUB_OUTPUT
      - name: Build And Push Image
        run: |
          echo ${{ secrets.GITTEA_PASSWORD }} | docker login ${{ secrets.CONTAINER_REGISTRY }} -u ${{ secrets.GITTEA_USER }} --password-stdin
          DOCKER_BUILDKIT=1 docker-compose -f docker-compose.pro.yaml build
          DOCKER_BUILDKIT=1 docker-compose -f docker-compose.pro.yaml push
      - uses: azure/setup-helm@v3
        with:
           version: 'latest'
           token: ${{ secrets.BOT_PAT }}
        id: install-helm
      - uses: azure/setup-kubectl@v3
        with:
           version: 'latest'
        id: install-kubectl
      - name: Setup Cluster Connection
        id: cluster_connection
        run: |
          echo "Test"
          REGISTRY_AUTH=$(echo -n "${{ secrets.GITTEA_USER }}:${{ secrets.GITTEA_PASSWORD }}" | base64)
          KUBECONFIG=./kubeconfig.yaml kubectl create namespace nextjsnamespace || true
          cat << EOF | while read eval_command; do yq -i eval "$eval_command" ./helm/values.yaml; done
            .rootNamespace = "nextjsnamespace"
            .ingress.host = "${{ secrets.BOT_PAT }}"
            .frontend.imageURL = "${{ steps.setup_env.outputs.frontend_image }}"
            .ingress.certManager = true
            .registryAuth.token = "$REGISTRY_AUTH"
            .registryAuth.use = true
          EOF
          KUBECONFIG=./kubeconfig.yaml helm upgrade next-js-app ./helm/ --set rootNamespace="nextjsnamespace" --install
```

Using the following secrets configured in your GitHub account:

- `BOT_PAT`: GitHub bot access token
- `GITTEA_USER`: Private registry user
- `GITTEA_PASSWORD`: Private registry password or auth token
- `CONTAINER_REGISTRY`: Container registry host address
- `KUBE_CONFIG_BASE64`: Base64 encoded kubeconfig to connect to the k8s cluster

#### Automation Steps

1. Clone the repo and its sub-repos using `actions/checkout@master`.
2. Setup the `.env` with a random image tag
3. Build and push the production image using the generated tag
4. Setup Helm and kubectl using the Azure actions `azure/setup-helm@v3`, `azure/setup-kubectl@v3`
5. Modify `values.yaml` with our new configuration and update the Helm installation

> Opportunities from here are limitless; you can easily have any pull to the main deploy a feature environment or connect a backend to your Next.js app.

Simple steps to build, push, and deploy a Next.js app on Kubernetes

Quickly Deploy Any Next Js App On Kubernetes


Deploying Postgres on Kubernetes need not be complex. With automation in place, you can deploy a secure and isolated instance of PostgreSQL within your Microk8s cluster using Bitnami's Helm chart. The updated script covers everything from provisioning TLS certificates to configuring the database for secure connections.

### Preparing the Environment

The process starts with some initial setup tasks. We create a Kubernetes namespace for the PostgreSQL instance and establish the baseline for our commands:

```bash
#!/bin/bash

KUBECMD_PREFIX="${KUBECMD_PREFIX:=microk8s}"
CERT_MANAGER_NAMESPACE="cert-manager"

$KUBECMD_PREFIX kubectl create namespace $K8_NAMESPACE || true
```

### Configuring SSL/TLS Encryption

With cert-manager installed in our cluster, we can automatically provision and manage TLS certificates. This is a crucial step in ensuring that our database communication is encrypted:

```bash
cat <<EOF | $KUBECMD_PREFIX kubectl apply -f -
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: $RELEASE_NAME-postgresql-tls
  namespace: $K8_NAMESPACE
spec:
  secretName: $RELEASE_NAME-postgresql-tls
  issuerRef:
    kind: ClusterIssuer
    name: letsencrypt-prod
  dnsNames:
  - $DB_HOSTNAME
EOF
```

It's imperative to wait for the certificate to become ready. This script assures that by incorporating a timeout for the process:

```bash
$KUBECMD_PREFIX kubectl -n $K8_NAMESPACE wait --for=condition=ready certificate $RELEASE_NAME-postgresql-tls --timeout=300s
```

### Installing PostgreSQL with Helm

Having confirmed that the TLS certificate is in place, we proceed with the Helm chart installation:

```bash
$KUBECMD_PREFIX helm install $RELEASE_NAME oci://registry-1.docker.io/bitnamicharts/postgresql \
    -n $K8_NAMESPACE \
    --set global.postgresql.auth.username="$DB_USERNAME" \
    --set global.postgresql.auth.password="$DB_PASSWORD" \
    ...
    --set tls.certificatesSecret="$RELEASE_NAME-postgresql-tls" \
    --set tls.certFilename="tls.crt" \
    --set tls.certKeyFilename="tls.key"
```

The script passes the appropriate values to Helm, signaling it to deploy Postgres with TLS enabled.

### Networking Configuration

The `ConfigMap` and `Service` definitions are applied to route external traffic to the Postgres instance:

```bash
read -r -d '' INGRESS_CONFIG << EOM
apiVersion: v1
kind: ConfigMap
metadata:
  namespace: ingress
  name: nginx-ingress-tcp-microk8s-conf
data:
  5432: "$K8_NAMESPACE/$RELEASE_NAME-postgresql:5432"
---
apiVersion: v1
kind: Service
metadata:
  name: $RELEASE_NAME-nodeport
  namespace: $K8_NAMESPACE
spec:
  type: NodePort
  ...
  nodePort: $TARGET_PORT
  ...
EOM

$KUBECMD_PREFIX kubectl apply -f - <<< "$INGRESS_CONFIG"
```

### Testing the Database Connection

Once deployed, verify the secure connection using Python and the `psycopg2` library. The script aims to establish a connection, execute a command, and then gracefully terminate the connection:

```python
import psycopg2

conn = None
try:
    conn = psycopg2.connect(
        dbname='...',
        user='...',
        password='...',
        host='...',
        port='...',
        sslmode='require'
    )

    print("Success: Connected to the database!")
    cur = conn.cursor()
    cur.execute("SELECT version();")
    record = cur.fetchone()
    print("You are connected to - ", record, "\n")
    cur.close()
except (Exception, psycopg2.DatabaseError) as error:
    print("Error: ", error)
finally:
    if conn is not None:
        conn.close()
        print("Database connection closed.")
```

By requiring `sslmode='require'`, the script confirms that the connection is not only secure but also compliant with best practices.

### Wrapping Up

The combination of Microk8s's simplicity and Helm's power simplifies the deployment of a robust PostgreSQL database. TLS encryption, managed by cert-manager, makes sure the data remains secure in transit. For developers and administrators looking to setup PostgreSQL on Kubernetes, the process is now streamlined, automated, and immeasurably more secure than before.

Do check out the full deployment script and accompanying resources on the [GitHub repository](https://github.com/tbscode/tims-blog-posts/blob/main/assets/postgress_create_dynamic_k8s.sh) and ensure your databases are secure from setup to daily operations.

This guide provides a step-by-step approach to installing a PostgreSQL database using Bitnami's Helm chart on a Microk8s cluster, including TLS configuration for enhanced security.

Setting Up a Secure Bitnami PostgreSQL Instance on Microk8s


Every now and then, when setting up a simple staging environment, the need for a quick-setup database that retains state consistently arises. In such situations, I often lean towards MariaDB, specifically utilizing the [Bitnami Helm Chart](https://github.com/bitnami/charts/tree/main/bitnami/mariadb), with slight tweaks to achieve the following:

- An auto-set, namespace setup
- Accessibility through a single host subdomain + port
- Easy hourly backups to a specified host path
- Exposure through TCP to the cluster host

### Prerequisites

This post is operating under the assumption that you have a `microk8s` Kubernetes cluster already set up, complete with `cert-manager`, `ingress`, `dns` and an active and configured `letsencrypt-prod` cluster issuer.

> Note: To jumpstart your setup, you might find [this Blog Post on Microk8s Private Cluster Setup](/blog/microk8s-on-vps) quite helpful.

### TL;DR 

For a swift deployment of this configuration:

1. [Grab this script](https://github.com/tbscode/tims-blog-posts/blob/main/assets/create_mariadb.sh)
2. Then run it as follows:

```bash
./create_mariadb.sh \
  RELEASE_NAME="<release-name>" \
  K8_NAMESPACE="<installation-namespace>" \
  DB_USERNAME="<db-username>" \
  DB_PASSWORD="<your-super-secure-password>" \
  DB_NAME="<db-name>" \
  TARGET_PORT="<desired-port>" \
  HOST_BACKUP_PATH="<your host backup volume>"
```


> Remember to expose the desired port through your firewall with a `sudo ufw allow $TARGET_PORT` command.
  
#### Uninstallation Process:

Execute the following command: 

```
microk8s helm uninstall $RELEASE_NAME
```

#### Connecting to the Database

Use this command to establish a connection to the database:

```bash
docker run -it --rm  mysql mysql --host <your-host-domain> --port <your-port> --user <your-user> --password --protocol=TCP
```

Or use this with `--network="host"` if your testing a local server.
Remember to enter the admin password when prompted.

#### Backing up the Database

Here's a simple docker command for accomplishing this:

```bash
docker run --network="host" --rm mysql:5.7 mysqldump -h localhost -P 30004 -u <your-user> -p<your-admin-password> --protocol=TCP <your-db-name> > backup.sql
```

#### Host Backup Strategy

A straightforward example of a cron job that allows your database to be backed up regularly is created as follows:

1. First, create a secret to hold your MariaDB credentials:

```bash
microk8s kubectl create secret generic mariadb-creds --from-literal=password='$DB_PASSWORD' --from-literal=username='$DB_USER' -n $K8_NAMESPACE
```

2. Then, define a CronJob in a yaml file:

```yaml
apiVersion: batch/v1beta1
kind: CronJob
metadata:
  name: backup-job
spec:
  schedule: "0 * * * *"
  jobTemplate:
    spec:
      template:
        spec:
          volumes:
            - name: backup-volume
              hostPath:
                path: "$HOST_BACKUP_PATH"
          containers:
            - name: backup-container
              image: mysql:5.7
              volumeMounts:
                - name: backup-volume
                  mountPath: /backup
              env:
                - name: MYSQL_PWD
                  valueFrom:
                    secretKeyRef:
                      name: mariadb-creds
                      key: password
                - name: MYSQL_USER
                  valueFrom:
                    secretKeyRef:
                      name: mariadb-creds
                      key: username
              command: ["sh", "-c", 'mysqldump -h database-host -P 30004 -u $MYSQL_USER --protocol=TCP database-name > /backup/backup-$(date +%Y%m%d-%H%M%S).sql']
          restartPolicy: OnFailure
```

With this configuration in place, you would have a CronJob that executes hourly backups of the database.



This straightforward guide will walk you through deploying and exposing a basic MariaDB database on your microk8s Kubernetes cluster.

MariaDB on Kubernetes with Backup Cron-job


> Are you tired of overpriced package registries? Rapidly deploy your own git and package registry - with [Gitea](https://about.gitea.com/) - using [their helm chart](https://gitea.com/gitea/helm-chart).

### Prerequisites

This post assumes that you have a `microk8s` cluster set up with `cert-manager`, `ingress`, and `dns` configured, and a cluster issuer `letsencrypt-prod` ready.

> To get started, feel free to follow my [Blog Post on Microk8s Private Cluster Setup](/blog/microk8s-on-vps).

## Setting it Up

> **Please note** - This is meant for a quick temporary private package. There is **no persistence intended.**

For easy installation, you can use [this simple script](https://github.com/tbscode/tims-blog-posts/blob/main/assets/install_gitea_microk8s.sh)

```bash
./install_gitea_microk8s.sh \
  K8_NAMESPACE="<installation-namespace>" \
  RELEASE_NAME="<release-name>" \
  ADMIN_USERNAME="<...>" \
  ADMIN_PASSWORD="<...>" \ 
  INGRESS_HOST="<host-url>"
```

In the above script, `$INGRESS_HOST` represents a subdomain you've configured a DNS entry for, pointing to your server, for instance: `my-git.example.com`.

### Configuration

First, to ensure that this doesn't consume too many resources, we disable the high-availability database and use the default one instead.

```bash
microk8s helm install $RELEASE_NAME gitea-charts/gitea \
    -n $K8_NAMESPACE \
    --set postgresql-ha.enabled=false \
    --set postgresql.enabled=true \
```

Next, we establish some credentials for our default admin user:

```bash
    --set gitea.admin.username="$ADMIN_USERNAME" \
    --set gitea.admin.password="$ADMIN_PASSWORD" \
```

We then enable and configure the ingress. Please note we are increasing the `proxy-body-size` to 1GB to allow us to push larger packages.
```bash
    --set ingress.enabled=true \
    --set "ingress.annotations.kubernetes\.io/ingress\.class=public" \
    --set "ingress.annotations.cert-manager\.io/cluster-issuer=letsencrypt-prod" \
    --set "ingress.annotations.nginx\.ingress\.kubernetes\.io/proxy-body-size=1g" \
    --set ingress.hosts[0].host="$INGRESS_HOST" \
    --set ingress.hosts[0].paths[0].path=/ \
    --set ingress.hosts[0].paths[0].pathType=Prefix \
    --set ingress.tls[0].secretName="git.$RELEASE_NAME-tls" \
    --set ingress.tls[0].hosts[0]="$INGRESS_HOST" \
```

> To make packages of the admin user private, sign in at `$INGRESS_HOST`, navigate to Settings > Profile > Visibility, and set it to Private.

### Uploading a Package

You can push a package to a path under your Gitea user as follows:

```bash
echo "<your-admin-password" | docker login $INGRESS_HOST -u <your-gitea-admin> --password-stdin
docker tag <image-id> $INGRESS_HOST/<your-gitea-admin>/<some-package-name>
```
### Authenticating Deployments for Pulling Images

It's essential to authorize your deployments to pull your private container images. You can create a simple image pull secret in your Helm chart as outlined below.

```yaml
kind: Secret
type: kubernetes.io/dockerconfigjson
apiVersion: v1
metadata:
  name: dockerconfigjson-github-com
  namespace: {{ .Values.rootNamespace }}
stringData:
  .dockerconfigjson: >
    {{
      (
        dict "auths"
        (
          dict "$INGRESS_HOST"
          (
            dict "auth" .Values.registryAuth.token
          )
        )
      )
      |
      toJson
    }}
{{- end }}
```

> If you're using Github packages, for instance, `$INGRESS_HOST` would be `ghcr.io`

Create a token by Base64 encoding the `user:password` string:

```bash
echo "<gitea-admin>:<gitea-admin-password" | base64
```
This will allow you to pull from your private repositories.

### Setting up gitea action runners via helm



This guide will demonstrate how you can effortlessly host Gitea on a private Kubernetes cluster and utilize it as a package registry.

Self-Hosted Git Server with Gitea on Kubernetes


> UPDATE: We made 2. Place! 🥳 Checkout [the hackathon page](https://devpost.com/software/tim-s-stack-anystack).

<iframe width="560" height="315" src="https://www.youtube.com/embed/_06vvSltvvY?si=ZMTgD9l2TFNTTa_2" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>

> Checkout the [full stack code](https://github.com/tbscode/tims-stack-anystack) on my repo

## Introduction

I recently participated in the Bunnyshell hackathon, where I successfully orchestrated a dynamic cross-platform web app stack. I want to share with you in detail my development process, core features, and the benefits of this stack.

This stack is primarily designed for dynamic, real-time web apps, with a specific inclination towards mobile clients. One of the prominent features is that any changes made in the backend can be directly and instantly transmitted to the clients via a WebSocket connection, thanks to Redux for smooth state management.

## Architecture

I used a Docker container-based architecture using Helm for my application. Docker simplifies the process of managing my application's lifecycle, while Helm assists in deploying my Docker images into a Kubernetes cluster.

Here is an image representation of my stack's architecture:

![stack overview](/static/assets/overview_graph.png)

## Building the Stack

The stack incorporates:

- **Django Backend**: Django is utilised for the backend due to its simplicity and rapid development capabilities. Features like Celery for task management and DRF Spectacular for API documentation are added advantages.

- **Next.js + React Frontend**: Next.js powers the frontend, providing performance benefits, SEO capabilities, and better developer experience.

- **Postgresql & Redis**: They act as primary databases for data and celery respectively.

- **Documentation**: Pdoc3 was used to generate code documentation from backend code.

## Configuring the Stack on Bunnyshell

Bunnyshell significantly simplifies cloud management and deployment automation making it a breeze to set up a Kubernetes cluster and to deploy my application there.

In addition to this, I also exemplify setting up a private Microk8s cluster. Microk8s serves as a lightweight, lean, and efficient Kubernetes distribution, enabling quick and easy deployment of Kubernetes resources even on a low-end VPS.

I hope you find this stack setup helpful and efficient for your next big project. The GitHub repository contains all the code with appropriate comments and READMEs for further exploration.

Happy Coding!

## Technologies

The following table provides a quick overview of the key technologies integrated into the stack:

| Component | Technology | Purpose |
|-----------|------------|---------|
| Frontend  | Next.js + React | Rich UI |
|           | Tailwind CSS + DaisyUI | Styling |
|           | Redux | State Management |
|           | Capacitor | Native integrations and iOS/Android PWA export |
| Backend   | Django | Application Framework |
|           | Celery | Task Management |
|           | Django REST Framework + django_rest_dataclasses | REST API Development |
|           | DRF Spectacular | API Documentation |
|           | Django Channels | Managing WebSockets |
| Documentation | Pdoc3 | Code Documentation |
| Database  | PostgreSQL | Primary Backend Database |
|           | Redis | Broker for Celery and Django Channels |
| Containerization | Docker | Container Creation and Management |
| Deployment and Orchestration | Helm + Bunnyshell | Simplified deployment, Scaling and Management |

Each of these technologies has been selected for its specific capabilities that contribute to the efficient operation of the entire web application stack.

This article showcases a high-performing web app stack I created for a recent Bunnyshell hackathon, using Docker, Kubernetes, Microk8s, Django and Next.js.