Kerberos
This documentation is for an out-of-date version of Apache Flink. We recommend you use the latest stable version.

Kerberos Authentication Setup and Configuration #

This document briefly describes how Flink security works in the context of various deployment mechanisms (Standalone, native Kubernetes, YARN), filesystems, connectors, and state backends.

Objective #

The primary goals of the Flink Kerberos security infrastructure are:

  • to enable secure data access for jobs within a cluster via connectors (e.g. Kafka)
  • to authenticate to ZooKeeper (if configured to use SASL)
  • to authenticate to Hadoop components (e.g. HDFS, HBase)

In a production deployment scenario, streaming jobs are understood to run for long periods of time (days/weeks/months) and be able to authenticate to secure data sources throughout the life of the job. Kerberos keytab do not expire in that timeframe, unlike credential cache or Hadoop delegation token.

The current implementation supports running Flink clusters (JobManager / TaskManager / jobs) with:

  • Keytab file (preferred)
  • Credential cache (for example credential cache file created by kinit)
  • Hadoop delegation tokens (the user provided tokens are not renewed and may be overwritten by Flink)

Keep in mind that all jobs share the credential configured for a given cluster.
To use a different keytab for a certain job, simply launch a separate Flink cluster with a different configuration.
Numerous Flink clusters may run side-by-side in a Kubernetes or YARN environment.

Conceptually, a Flink program may use first- or third-party connectors (Kafka, HDFS, Cassandra, Flume, Kinesis etc.) necessitating arbitrary authentication methods (Kerberos, SSL/TLS, username/password, etc.). While satisfying the security requirements for all connectors is an ongoing effort, Flink provides first-class support for Kerberos authentication only. The following services and connectors are supported for Kerberos authentication:

  • Kafka (0.9+)
  • HDFS
  • HBase
  • ZooKeeper

Note that it is possible to enable the use of Kerberos independently for each service or connector. For example, the user may enable Hadoop security without necessitating the use of Kerberos for ZooKeeper, or vice versa. The shared element is the configuration of Kerberos credentials, which is then explicitly used by each component.

The internal architecture is based on security modules (implementing org.apache.flink.runtime.security.modules.SecurityModule) which are installed at startup. The following sections describes each security module.

Hadoop Security Module #

This module uses the Hadoop UserGroupInformation (UGI) class to establish a process-wide login user context. The login user is then used for all interactions with Hadoop, including HDFS, HBase, and YARN.

If Hadoop security is enabled (in core-site.xml), the login user will have whatever Kerberos credential is configured. Otherwise, the login user conveys only the user identity of the OS account that launched the cluster. In order to be specific the login process has the following order of precedence:

  • When hadoop.security.authentication is set to kerberos
    • When security.kerberos.login.keytab and security.kerberos.login.principal configured then keytab login performed
    • When security.kerberos.login.use-ticket-cache configured then credential cache login performed
  • All other cases user identity of the OS account used

JAAS Security Module #

This module provides a dynamic JAAS configuration to the cluster, making available the configured Kerberos credential to ZooKeeper, Kafka, and other such components that rely on JAAS.

Note that the user may also provide a static JAAS configuration file using the mechanisms described in the Java SE Documentation. Static entries override any dynamic entries provided by this module.

ZooKeeper Security Module #

This module configures certain process-wide ZooKeeper security-related settings, namely the ZooKeeper service name (default: zookeeper) and the JAAS login context name (default: Client).

Deployment Modes #

Here is some information specific to each deployment mode.

Standalone Mode #

Steps to run a secure Flink cluster in standalone/cluster mode:

  1. Add security-related configuration options to the Flink configuration file (on all cluster nodes) (see here).
  2. Ensure that the keytab file exists at the path indicated by security.kerberos.login.keytab on all cluster nodes.
  3. Deploy Flink cluster as normal.

Native Kubernetes and YARN Mode #

Steps to run a secure Flink cluster in native Kubernetes and YARN mode:

  1. Add security-related configuration options to the Flink configuration file on the client (see here).
  2. Ensure that the keytab file exists at the path as indicated by security.kerberos.login.keytab on the client node.
  3. Deploy Flink cluster as normal.

In YARN and native Kubernetes mode, the keytab is automatically copied from the client to the Flink containers.

To enable Kerberos authentication, the Kerberos configuration file is also required. This file can be either fetched from the cluster environment or uploaded by Flink. In the latter case, you need to configure the security.kerberos.krb5-conf.path to indicate the path of the Kerberos configuration file and Flink will copy this file to its containers/pods.

For more information, see YARN security documentation.

Using user credential cache (kinit) #

Before we go on the usage some important things to know:

  • Credential cache can be represented in many forms, the most common form is FILE. For further information please read Kerberos ccache types. Ensure that the credential cache is available on all cluster nodes where Kerberos authentication is performed.
  • Credential cache can be generated mainly with executing kinit command
  • Important difference compared to keytab that keytab can be generated in a way that it never expires but credential cache has an expiry date. Keeping the credential cache up-to-date is fully user responsibility.

It is possible to deploy a secure Flink cluster without a keytab, using only the credential cache.

Steps to run a secure Flink cluster using kinit:

  1. Add security-related configuration options to the Flink configuration file on the client (see here).
  2. Login using the kinit command.
  3. Optional: Make the credential cache available on all cluster nodes where Kerberos authentication is performed.
  4. Deploy Flink cluster as normal.

Further Details #

TGT Renewal #

Each component that uses Kerberos is independently responsible for renewing the Kerberos ticket-granting-ticket (TGT). All components renew the TGT automatically when keytab provided however it’s the user responsibility when credential cache used.

Using delegation tokens #

In Flink 1.17 delegation token support added as an experimental feature. This is quite a heavyweight topic so there is a general delegation token information page.

When talking to Hadoop-based services, Flink can obtain delegation tokens so that non-local processes can authenticate. There is support for:

  • HDFS and other Hadoop file systems
  • HBase

When using a Hadoop filesystem (such HDFS or WebHDFS), Flink can obtain the relevant tokens for the following directories:

  • Hadoop default filesystem
  • Filesystems configured in: security.kerberos.access.hadoopFileSystems
  • YARN staging directory

An HBase token will be obtained if HBase is in the application’s classpath, and the HBase configuration has Kerberos authentication turned (hbase.security.authentication=kerberos).

Flink also supports custom delegation token providers using the Java Services mechanism (see java.util.ServiceLoader). Implementations of org.apache.flink.runtime.security.token.DelegationTokenProvider can be made available to Flink by listing their names in the corresponding file in the jar’s META-INF/services directory.

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