Release note history¶
Anaconda Enterprise 5.2.2¶
Released: October 10, 2018
- Added ability to configure an external Git repository (instead of the internal Git repository) to store projects containing version-controlled notebooks, code, and other files. Supported external Git version control systems include Atlassian BitBucket, GitHub and GitHub Enterprise, and GitLab.
- Administrators can optionally configure GPU worker nodes to be used only for sessions and deployments that require a GPU (by preventing CPU-only sessions and deployments from accessing GPU resources).
- In-place upgrades can now be performed from AE 5.2.x to AE 5.2.2.
- Improved functionality in backup script related to backup location and disk capacity requirements.
- Implemented multiple security enhancements related to cache control headers, HTTP strict transport security, and default ciphers and protocols across all services.
- Administrators no longer need to generate separate TLS/SSL certificates for the Operations Center.
- Improved validation of custom TLS/SSL certificates in the Administrator Console.
- Administrators can now disable access to
sudo yumoperations in sessions across the platform.
- Fixed an issue related to orphaned clients for sessions and deployments not being removed from Authentication Center.
- Tokens for user notebook sessions and deployments are now stored in encrypted format.
- Renamed platform-wide conda settings to
ssl_verifysettings in the
condasection of configmap to be consistent with
- Administrators can now specify the channel priority order when creating environments/installers.
- Fixed an issue related to sorting of package versions when creating environments/installers.
- Fixed an issue with download links for custom Anaconda parcels.
- Improved behavior of package mirroring tool to only remove existing packages when clean mode is active.
- Fixed an issue related to mirroring pip packages from PyPI repository.
- Added support for
noarchpackages in package mirroring tool.
- Improved logging and error handling in package mirroring tool.
- Fixed an issue related to projects failing to be created due to special characters in usernames.
- Fixed an issue related to authorization center errors when syncing large number of users from external identity providers.
- Added logout functionality to
- Apache Zeppelin is now available as a notebook editor for projects (in addition to Jupyter Notebooks and JupyterLab). Apache Zeppelin is a web-based notebook that enables data-driven, interactive data analytics and collaborative documents with interpreters for Python, R, Spark, Hive, HDFS, SQL, and more.
- Conda channels in the repository can be made publicly available (default), or access can be restricted to specific authenticated users or groups.
- A single notebook kernel (associated with the active conda environment used within a project) is now displayed by default in Jupyter Notebooks and JupyterLab.
- Collaborators can now select a different default editor for projects that have been shared with them.
- Implemented various fixes to configuration parameters for scheduled jobs within a project.
- Improved input/form validation related to projects, deployments, packages, and settings across the platform.
- Improved error messaging/handling across the platform, along with the ability to view errors and logs from underlying services.
- Improved notifications for tasks such as uploading projects and copying sample projects.
- Users are now prompted to delete all related sessions, deployments, jobs, and runs (including those used by collaborators) when deleting a project.
- Fixed an issue that caused numerous erroneous job runs to be spawned based on the default job scheduling parameters.
Anaconda Enterprise 5.2.1¶
Released: August 30, 2018
- Fixed issue with loading spinner appearing on top of notebook sessions
- Fixed issue related to missing projects and copying sample projects when upgrading from AE 5.1.x
- Improved visual feedback when loading notebook sessions/deployments and performing actions such as creating/copying projects
Anaconda Enterprise 5.2.0¶
Released: July 27, 2018
- New administrative console with workflows for managing channels and packages, creating installers, and other distinct administrator tasks
- Added ability to mirror pip packages from PyPI repository
- Added ability to define custom hardware resource profiles based on CPU, RAM, and GPU for user sessions and deployments
- Added support for GPU worker nodes that can be defined in resource profiles
- Added ability to explicitly install different types of master nodes for high availability
- Added ability to specify NFS file shares that users can access within sessions and deployments
- Significantly reduced the amount of time required for backup/restore operations
- Added channel and package management tasks to UI, including downloading/uploading packages, creating/sharing channels, and more
- Anaconda Livy is now included in the Anaconda Enterprise installer to enable remote Spark connectivity
- All network traffic for services is now routed on standard HTTPS port 443, which reduces the number of external ports that need to be configured and accessed by end users
- Notebook/editor sessions are now accessed via subdomains for security and isolation
- Reworked documentation for administrator workflows, including managing cluster resources, configuring authentication, generating custom installers, and more
- Reduced verbosity of console output from anaconda-enterprise-cli
- Suppressed superfluous database errors/warnings
- Added support for selecting GPU hardware in project sessions and deployments, to accelerate model training and other computations with GPU-enabled packages
- Added ability to select custom hardware resource profiles based on CPU, RAM, and GPU for individual sessions and deployments
- Added support for scheduled and batch jobs, which can be used for recurring tasks such as model training or ETL pipelines
- Added support for connecting to external Git repositories in a project session or deployment using account-wide credentials (SSH keys or API tokens)
- New, responsive user interface, redesigned for data science workflows
- Added ability to share deployments with unauthenticated users outside of Anaconda Enterprise
- Changed the default editor in project sessions to Jupyter Notebooks (formerly JupyterLab)
- Added ability to specify default editor on a per-project basis, including Jupyter Notebooks and JupyterLab
- Added ability to work with data in mounted NFS file shares within sessions and deployments
- Added ability to export/download projects from Anaconda Enterprise to local machine
- Added package and channel management tasks to UI, including uploading/downloading packages, creating/sharing channels, and more
- Reworked documentation for data science workflows, including working with projects/deployments/packages, using project templates, machine learning workflows, and more
- Added ability to force delete a project with running sessions, shared collaborators, etc.
- Improved messaging when a session or deployment cannot be scheduled due to limited cluster resources
- The last modified date/time for projects now accounts for commits to the project
- Unique names are now enforced for projects and deployments
- Fixed bug in which project creator role was not being enforced
Backend improvements (non-visible changes)
- Updated to Kubernetes 1.9.6
- Added RHEL/CentOS 7.5 to supported platforms
- Added support for SELinux passive mode
- Anaconda Enterprise now uses the Helm package manager to manage and upgrade releases
- New version (v2) of backend APIs with more comprehensive information around projects, deployments, packages, channels, credentials and more
- Fixed various bugs related to custom Anaconda installer builds
- Fixed issue with
Anaconda Enterprise 5.1.3¶
Released: June 4, 2018
Backend improvements (non-visible changes)
- Fixed issue when generating custom Anaconda installers that contain packages with duplicate files
- Fixed multiple issues related to memory errors, file size limits, and network transfer limits that affected the generation of large custom Anaconda installers
- Improved logging when generating custom Anaconda installers
Anaconda Enterprise 5.1.2¶
Released: March 16, 2018
- Fixed issue with image/version tags when upgrading AE
Backend improvements (non-visible changes)
- Updated to Kubernetes 1.7.14
Anaconda Enterprise 5.1.1¶
Released: March 12, 2018
- Ability to specify custom UID for service account at install-time (default UID: 1000)
- Added pre-flight checks for kernel modules, kernel settings, and filesystem options when installing or adding nodes
- Improved initial startup time of project creation, sessions, and deployments
after installation. Note that all services will be in the
ContainerCreatingstate for 5 to 10 minutes while all AE images are being pre-pulled, after which the AE user interface will become available.
- Improved upgrade process to automatically handle upgrading AE core services
- Improved consistency between GUI- and CLI-based installation paths
- Improved security and isolation between internal database from user sessions and deployments
- Added capability to configure a custom trust store and LDAPS certificate validation
- Simplified installer packaging using a single tarball and consistent naming
- Updated documentation for system requirements, including XFS filesystem requirements and kernel modules/settings
- Updated documentation for mirroring packages from channels
- Added documentation for configuring AE to point to online Anaconda repositories
- Added documentation for securing the internal database
- Added documentation for configuring RBAC, role mapping, and access control
- Added documentation for LDAP federation and identity management
- Improved documentation for backup/restore process
- Fixed issue when deleting related versions of custom Anaconda parcels
- Added command to remove channel permissions
- Fixed issue related to Ops Center user creation in post-install configuration
- Silenced warnings when using
- Fixed issue related to default admin role (
- Fixed issue when generating TLS/SSL certificates with FQDNs greater than 64 characters
- Fixed issue when using special characters with AE Ops Center accounts/passwords
- Fixed bug related to Administrator Console link in menu
- Improvements to collaborative workflow: Added notification when collaborators make changes to a project, ability to pull changes into a project, and ability to resolve conflicting changes when saving or pulling changes into a project.
- Additional documentation and examples for connecting to remote data and compute sources: Spark, Hive, Impala, and HDFS
- Optimized startup time for Spark and SAS project templates
- Improved initial startup time of project creation, sessions, and deployments by pre-pulling images after installation.
- Increased upload limit of projects from 100 MB to 1 GB
- Added capability to
sudo yum installsystem packages from within project sessions
- Fixed issue when uploading projects that caused them to fail during partial import
- Fixed R kernel in R project template
- Fixed issue when loading
sparklyrin Spark Project
- Fixed issue related to displaying kernel names and Spark project icons
- Improved performance when rendering large number of projects, packages, etc.
- Improved rendering of long version names in environments and projects
- Render full names when sharing projects and deployments with collaborators
- Fixed issue when sorting collaborators and package versions
- Fixed issue when saving new environments
- Fixed issues when viewing installer logs in IE 11 and Safari
Anaconda Enterprise 5.1.0¶
Released: January 19, 2018
- New post-installation administration GUI with automated configuration of TLS/SSL certificates, administrator account, and DNS/FQDN settings; significantly reduces manual steps required during post-installation configuration process
- New functionality for administrators to generate custom Anaconda installers, parcels for Cloudera CDH, and management packs for Hortonworks HDP
- Improved backup and restore process with included scripts
- Switched from groups to roles for role-based access control (RBAC) for Administrator and superuser access to AE services
- Clarified system requirements related to system modules and IOPS in documentation
- Added ability to specify fractional CPUs/cores in global container resource limits
- Fixed consistency of TLS/SSL certificate names in configuration and during creation of self-signed certificates
- Changed use of
ssl_verifythroughout AE CLI for consistency with
- Fixed configuration issue with licenses, including field names and online/offline licensing documentation
- Updated default project environments to Anaconda Distribution 5.0.1
- Improved configuration and documentation on using Sparkmagic and Livy with Kerberos to connect to remote Spark clusters
- Fixed R environment used in sample projects and project template
- Fixed UI rendering issue on package detail view of channels, downloads, and versions
- Fix multiple browser compatiblity issues with Microsoft Edge and Internet Explorer 11
- Fixed multiple UI issues with Anaconda Project JupyterLab extension
Backend improvements (non-visible changes)
- Updated to Kubernetes 1.7.12
- Updated to conda 4.3.32
- Added SUSE 12 SP2/SP3, and RHEL/CentOS 7.4 to supported platform matrix
- Implemented TLS 1.2 as default TLS protocol; added support for configurable TLS protocol versions and ciphers
- Fixed default superuser roles for repository service, which is used for initial/internal package configuration step
- Implemented secure flag attribute on all session cookies containing session tokens
- Fixed issue during upgrade process that failed to vendor updated images
DiskNodeUnderPressureand cluster stability issues
- Fixed Quality of Service (QoS) issue with core AE services on under-resourced nodes
- Fixed issue when using access token instead of ID token when fetching roles from authentication service
- Fixed issue with authentication proxy and session cookies
- IE 11 compatibility issue when using Bokeh in notebooks (including sample projects)
- IE 11 compatibility issue when downloading custom installers
Anaconda Enterprise 5.0.6¶
Released: November 9, 2017
Anaconda Enterprise 5.0.5¶
Released: November 7, 2017
Anaconda Enterprise 5.0.4¶
Released: September 12, 2017
Anaconda Enterprise 5.0.3¶
Released: August 31, 2017 (General Availability Release)
Anaconda Enterprise 5.0.2¶
Released: August 15, 2017 (Early Adopter Release)
Anaconda Enterprise 5.0.1¶
Released: March 8, 2017 (Early Adopter Release)
- Simplified, one-click deployment of data science projects and deployments, including live Python and R notebooks, interactive data visualizations and REST APIs.
- End-to-end secure workflows with SSL/TLS encryption.
- Seamlessly managed scalability of the entire platform
- Industry-grade productionization, encapsulation, and containerization of data science projects and applications.