To access a Kubernetes cluster, an endpoint and some credentials are needed.
They are usually taken either from the environment (environment variables),
or from the
~/.kube/config file, or from external authentication services.
Kopf provides rudimentary authentication out of the box: it can authenticate with the Kubernetes API either via the service account or raw kubeconfig data (with no additional interpretation or parsing of those).
But this can be not enough in some setups and environments. Kopf does not try to maintain all the authentication methods possible. Instead, it allows the operator developers to implement their custom authentication methods and “piggybacks” the existing Kubernetes clients.
The latter ones can implement some advanced authentication techniques, such as the temporary token retrieval via the authentication services, token rotation, etc.
In most setups, the normal authentication from one of the API client libraries is enough — it works out of the box if those clients are installed (see Piggybacking below). Custom authentication is only needed if the normal authentication methods do not work for some reason, such as if you have a specific and unusual cluster setup (e.g. your own auth tokens).
To implement a custom authentication method, one or a few login-handlers
can be added. The login handlers should either return nothing (
or an instance of
import datetime import kopf @kopf.on.login() def login_fn(**kwargs): return kopf.ConnectionInfo( server='https://localhost', ca_path='/etc/ssl/ca.crt', ca_data=b'...', insecure=True, username='...', password='...', scheme='Bearer', token='...', certificate_path='~/.minikube/client.crt', private_key_path='~/.minikube/client.key', certificate_data=b'...', private_key_data=b'...', expiration=datetime.datetime(2099, 12, 31, 23, 59, 59), )
As with any other handlers, the login handler can be async if the network communication is needed and async mode is supported:
import kopf @kopf.on.login() async def login_fn(**kwargs): pass
kopf.ConnectionInfo is a container to bring the parameters necessary
for making the API calls, but not the ways of retrieving them. Specifically:
TCP server host & port.
SSL verification/ignorance flag.
SSL certificate authority.
SSL client certificate and its private key.
Authorization: Basic username:password.
Authorization: Bearer token(or other schemes: Bearer, Digest, etc).
URL’s default namespace for the cases when this is implied.
No matter how the endpoints or credentials are retrieved, they are directly mapped to TCP/SSL/HTTPS protocols in the API clients. It is the responsibility of the authentication handlers to ensure that the values are consistent and valid (e.g. via internal verification calls). It is in theory possible to mix all authentication methods at once or to have none of them at all. If the credentials are inconsistent or invalid, there will be permanent re-authentication happening.
Multiple handlers can be declared to retrieve different credentials or the same credentials via different libraries. All of the retrieved credentials will be used in random order with no specific priority.
In case no handlers are explicitly declared, Kopf attempts to authenticate with the existing Kubernetes libraries if they are installed. At the moment: pykube-ng and kubernetes. In the future, more libraries can be added for authentication piggybacking.
pykube-ng is not pre-installed implicitly.
If needed, install it explicitly as a dependency of the operator,
kopf[full-auth] (see Installation).
Piggybacking means that the config parsing and authentication methods of these libraries are used, and only the information needed for API calls is extracted.
If a few of the piggybacked libraries are installed, all of them will be attempted (as if multiple handlers are installed), and all the credentials will be utilised in random order.
If that is not the desired case, and only one of the libraries is needed, declare a custom login handler explicitly, and use only the preferred library by calling one of the piggybacking functions:
import kopf @kopf.on.login() def login_fn(**kwargs): return kopf.login_via_pykube(**kwargs)
import kopf @kopf.on.login() def login_fn(**kwargs): return kopf.login_via_client(**kwargs)
The same trick is also useful to limit the authentication attempts by time or by number of retries (by default, it tries forever until succeeded, returned nothing, or explicitly failed):
import kopf @kopf.on.login(retries=3) def login_fn(**kwargs): return kopf.login_via_pykube(**kwargs)
Similarly, if the libraries are installed and needed, but their credentials are not desired, the rudimentary login functions can be used directly:
import kopf @kopf.on.login() def login_fn(**kwargs): return kopf.login_with_service_account(**kwargs) or kopf.login_with_kubeconfig(**kwargs)
Internally, all the credentials are gathered from all the active handlers (either the declared ones or all the fallback piggybacking ones) in no particular order, and are fed into a vault.
The Kubernetes API calls then use random credentials from that vault. The credentials that have reached their expiration are ignored and removed. If the API call fails with an HTTP 401 error, these credentials are marked invalid, excluded from further use, and the next random credentials are tried.
When the vault is fully depleted, it freezes all the API calls and triggers the login handlers for re-authentication. Only the new credentials are used. The credentials, which previously were known to be invalid, are ignored to prevent a permanent never-ending re-authentication loop.
There is no validation of credentials by making fake API calls. Instead, the real API calls validate the credentials by using them and reporting them back to the vault as invalid (or keeping them as valid), potentially causing new re-authentication activities.
In case the vault is depleted and no new credentials are provided by the login handlers, the API calls fail, and so does the operator.
This internal logic is hidden from the operator developers, but it is worth
knowing how it works internally. See
If the expiration is intended to be often (e.g. every few minutes), you might want to disable the logging of re-authenication (whether this is a good idea or not, you decide using the information about your system):
import logging logging.getLogger('kopf.activities.authentication').disabled = True logging.getLogger('kopf._core.engines.activities').disabled = True