Landscaper takes a set of Helm Chart references with values (a desired state), and realizes this in a Kubernetes cluster. The intended use case is to have this desired state under version control, and let Landscaper first test and then apply the state as part of the CI/CD stages.

The Landscaper project is an ongoing project in an early stage, opened due to demand in the community. Contributions and feedback are more than welcome!

• Introduction
• Usage
• Example
• Example Use Case
• Contributing

• The set of applications in the Kubernetes cluster is potentially large and complex;
• Manually inspecting and administering them, and keeping different environments (e.g. production, acceptance) in sync is laborious and difficult;
• Cooperating with multiple tenants in this shared cluster increases the complexity.

• Have a blue print of what the landscape (apps in the cluster) looks like;
• Keep track of changes: when, what, why and by who;
• Allow others to review changes before applying them;
• Let the changes be promoted to specific environments.

• A Git repository contains a desired state description of the landscape, with CI/CD and a review before merge regime;
• Landscaper, an app that eliminates difference between desired and actual state of Helm releases in a Kubernetes cluster.

You must have a working Go environment with glide and Make installed.

From a terminal:

  cd $GOPATH
  mkdir -p src/github.com/eneco/
  cd !$
  git clone https://github.com/Eneco/landscaper.git
  cd landscaper
  make bootstrap build

Outputs the landscaper binary in ./build/landscaper.

Landscaper consists of a core API and a command line interface (CLI) that consumes this API. It takes as input a set of files that constitute the desired state. The CLI assumes that kubectl and helm have been setup!

These files contain (a) reference(s) to a Helm Chart and its configuration (Values). Additionally, Landscaper receives settings (tokens, credentials) needed to query and modify a Kubernetes cluster via Helm/Tiller. Typically these settings are provided by the CI/CD system.

The CLI uses a command structure in the spirit of git et al. The main command is landscaper apply to apply a desired state. The apply command accepts the following arguments:

Usage:
  landscaper apply [flags]

Flags:
      --chart-dir string         where the charts are stored (default "$HOME/.helm")
      --context string           the kube context to use. defaults to the current context
      --dir string               path to a folder that contains all the landscape desired state files; overrides LANDSCAPE_DIR (default ".")
      --dry-run                  simulate the applying of the landscape. useful in merge requests
      --loop                     keep landscape in sync forever
      --loop-interval duration   when running in a loop the interval between invocations (default 5m0s)
      --namespace string         namespace to apply the landscape to; overrides LANDSCAPE_NAMESPACE (default "default")
      --no-cronjob-update        replaces CronJob updates with a create+delete; k8s #35149 work around
      --no-prefix                disable prefixing release names
      --prefix string            prefix release names with this string instead of <namespace>; overrides LANDSCAPE_PREFIX
  -v, --verbose                  be verbose

Instead of using arguments, environment variables can be used. When arguments are present, they override environment variables. --namespace is used to isolate landscapes through Kubernetes namespaces. Unless otherwise specified, Helm releases are prefixed with the same namespace string to avoid collisions, since Helm release names aren't namespaced.

Input desired state files are in YAML and contain the name that identifies the "component", a reference to a chart, configuration and optionally secrets. Currently, secrets are handled by specifying the name in the YAML, e.g. my-secret, and having a matching environment variable available with the secret, e.g. export MY_SECRET=Rumpelstiltskin

Landscaper can also be run as a control loop that constantly watches the desired landscape and applies it to the cluster. With this you can deploy landscaper once in your cluster, pass it a reference to a landscape description and have Landscaper apply it whenever the landscape changes.

An example is provided here.

We, at Eneco, have setup a git repository with the inputs to the landscaper. During CI, non-master branches are Landscaped --dry-run to validate the inputs. After a pull request is reviewed, the changes are merged into master after which the Landscaper applies the new desired state.

We'd love to accept your contributions! Please use GitHub pull requests: fork the repo, develop and test your code, semantically commit (as of April 2017) and submit a pull request. Thanks!