Cloudera Security Overview
A brief introduction to Cloudera security features.
As a system designed to support vast amounts and types of data, Cloudera clusters must meet ever-evolving security requirements imposed by regulating agencies, governments, industries, and the general public. Cloudera clusters comprise both Hadoop core and ecosystem components, all of which must be protected from a variety of threats to ensure the confidentiality, integrity, and availability of all the cluster's services and data. This overview provides introductions to:
- Perimeter Access to the cluster must be protected from a variety of threats coming from internal and external networks and from a variety of actors. Network isolation can be provided by proper configuration of firewalls, routers, subnets, and the proper use of public and private IP addresses, for example. Authentication mechanisms ensure that people, processes, and applications properly identify themselves to the cluster and prove they are who they say they are, before gaining access to the cluster.
- Data Data in the cluster must always be protected from unauthorized exposure. Similarly, communications between the nodes in the cluster must be protected. Encryption mechanisms ensure that even if network packets are intercepted or hard-disk drives are physically removed from the system by bad actors, the contents are not usable.
- Access Access to any specific service or item of data within the cluster must be specifically granted. Authorization mechanisms ensure that once users have authenticated themselves to the cluster, they can only see the data and use the processes to which they have been granted specific permission.
- Visibility Visibility means that the history of data changes is transparent and capable of meeting data governance policies. Auditing mechanisms ensure that all actions on data and its lineage—source, changes over time, and so on—are documented as they occur.
Securing the cluster to meet specific organizational goals involves using security features inherent to the Hadoop ecosystem as well as using external security infrastructure. The various security mechanisms can be applied in a range of levels.
|0||Non-secure||No security configured. Non-secure clusters should never be used in production environments because they are vulnerable to any and all attacks and exploits. Recommended only for proof of concept, demo, and disposable platforms.|
|1||Basic security||Configured for authentication, authorization, and auditing. Authentication is first configured to ensure that users and services can access the cluster only after proving their identities. Next, authorization mechanisms are applied to assign privileges to users and user groups. Auditing procedures keep track of who accesses the cluster (and how). Recommended for development platforms.|
|2||Data Security and Governance||Sensitive data is encrypted. Key management systems handle encryption keys. Auditing has been setup for data in meta stores. System metadata is reviewed and updated regularly. Ideally, cluster has been setup so that lineage for any data object can be traced (data governance). Recommended for staging and production.|
|3||Compliance Ready||The secure CDP cluster is one in which all data, both data-at-rest and data-in-transit, is encrypted and the key management system is fault-tolerant. Auditing mechanisms comply with industry, government, and regulatory standards (PCI, HIPAA, NIST, for example), and extend from CDP to the other systems that integrate with it. Cluster administrators are well-trained, security procedures have been certified by an expert, and the cluster can pass technical review. Recommended for all production platforms.|
Hadoop Security Architecture
- External data streams are authenticated by mechanisms in place for Flume and Kafka. Data from legacy databases is ingested using Sqoop. Data scientists and BI analysts can use interfaces such as Hue to work with data on Impala or Hive, for example, to create and submit jobs. Kerberos authentication can be leveraged to protect all these interactions.
- Encryption can be applied to data at-rest using transparent HDFS encryption with an enterprise-grade Key Trustee Server.
- Authorization policies can be enforced using Ranger (for services such as Hive, Impala, and Search) as well as HDFS Access Control Lists.
- Auditing capabilities can be provided by using Apache Ranger.