Installing IBM Document Processing Extension
You can install Document Processing Extension.
Before you begin
Make sure that you have the necessary infrastructure and software before you install Document Processing Extension.
- Hardware
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- Supports x86_64 CPU architecture. (Other architectures are not supported, such as ARM, Power/ppc64, zLinux/s390x.)
- Minimum of 4 CPU cores and 16 GB memory. 8 or more CPU and 16 GB or more memory are recommended for production.
- Minimum 8 CPU cores and 32 GB or more memory are recommended if you plan to install the optional feature Optical Character Recognition Engine 2.
- Software
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- Linux operating system. Ubuntu 20.04 LTS and 22.04 LTS are recommended. You can use other Linux distributions that Docker supports.
- Docker 20.10 or later, with swarm mode enabled.
- Python 3.8 or later.
- OpenSSL 3.0 or later.
- A Linux user that has permission to run docker commands (that is, the user is added to the
dockergroup).Note: MacOS and Windows are not officially supported.
- Networking
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- Db2 and PostgreSQL SSL connections are not supported.
- Only IPv4 networking on the host machine is supported. IPv6 and dual stack are not supported.
- Remote database server
- If you plan to use User-provided remote Db2 server or User-provided remote PostgreSQL server
with
Manual DB managementoption, you must create the base database before you install the Document Processing Extension stack. For more information, see Creating base database on a remote Db2 server or Creating base database on a PostgreSQL server.Note: You can ignore this prerequisite if you plan to use Built-in PostgreSQL container or the User-provided remote PostgreSQL server withAutomated DB managementoption - FIPS compliance
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FIPS is not supported. Document Processing Extension cannot run on a FIPS enabled host machine. If you run Document Processing Extension on FIPS enabled environment, you see
TLSV1_ALERT_INSUFFICIENT_SECURITYin all celery pods and they cannot connect to RabbitMQ. dpedeploytool- The
dpedeploytool does not support Database HA/DR configuration.Note: It is possible to implement HADR but it needs many manual configurations - Deep learning object detection
- The deep-learning object detection feature is not supported.