erwin Data Modeler by Quest is a data modeling tool used to find, visualize, design, deploy and standardize high-quality enterprise data assets. It can discover and document any data from anywhere for consistency, clarity and artifact reuse across large-scale data integration, master data management, metadata management, Big Data, business intelligence and analytics initiatives, accomplishing this whil esupporting data governance and intelligence efforts.
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Ansible
Score 9.2 out of 10
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The Red Hat Ansible Automation Platform (acquired by Red Hat in 2015) is a foundation for building and operating automation across an organization. The platform includes tools needed to implement enterprise-wide automation, and can automate resource provisioning, and IT environments and configuration of systems and devices. It can be used in a CI/CD process to provision the target environment and to then deploy the application on it.
I have had a chance to use few other data modeling tools from Quest and Oracle, but I am most comfortable using erwin Data Modeler. They understand your data modeling needs and have designed the software to give you a feeling of completeness when you are designing a data model.
I'm going to say it is best suited for configuration management. Like I said, patching even with security, things of that nature. Probably less suited is hardware management, but Red Hat IBM/IBM has Terraform for that. So it's a trade off.
Reverse Engineering: I love the way we can import an SQL file containing schema meta data and generate ER diagram out of it. This is specifically useful if you are implementing erwin Data Modeler for an existing database.
Forward Engineering: We use this feature very frequently. Where we do database changes in our physical and logical data models and then generate deployment scripts for the changes made.
Physical vs Logical Models: I like to have my database model split into physical and logical models and at the same time still linked to each other. Any changes you make to logical model or physical model shows up in the other.
Debugging is easy, as it tells you exactly within your job where the job failed, even when jumping around several playbooks.
Ansible seems to integrate with everything, and the community is big enough that if you are unsure how to approach converting a process into a playbook, you can usually find something similar to what you are trying to do.
Security in AAP seems to be pretty straightforward. Easy to organize and identify who has what permissions or can only see the content based on the organization they belong to.
Better documentation of how all the options/parameters are meant to be used (when creating things like jobs, templates, inventories, etc)
More recommendations of best practices as far as the best way to organize job templates, workflows, roles. Much can be found on how to organize pure Ansible, but not so much for AAP specifically.
I have found some things that seem like they should be easy but are not possible. Things like moving a host from one inventory to a different inventory. As far as I know this is not possible and requires deletion and recreation. Maybe I just don't know how this could be done or don't understand the design decisions behind this?
Even is if it's a great tool, we are looking to renew our licence for our production servers only. The product is very expensive to use, so we might look for a cheaper solution for our non-production servers. One of the solution we are looking, is AWX, free, and similar to AAP. This is be perfect for our non-production servers.
I had a lot of experience using erwin Data Modeler for designing data models. I think it's pretty intuitive and easy to use. It has enough features to represent your database requirements in form of a model.
It's overall pretty easy to use foe all the applications I've mentioned before: configuring hosts, installing packages through tools like apt, applying yaml, making changes across wide groups of hosts, etc. Its not a 10 because of the inconveinience of the yaml setup, and the time to write is not worth it for something applied one time to only a few hosts
Great in almost every way compared to any other configuration management software. The only thing I wish for is python3 support. Other than that, YAML is much improved compared to the Ruby of Chef. The agentless nature is incredibly convenient for managing systems quickly, and if a member of your term has no terminal experience whatsoever they can still use the UI.
CA customer support and our account manager have been able to support us with any issues that we have had, from managing our serial keys to issues we logged tickets to resolve. There are aspects of key management that have made it difficult over the years but support usually has worked with us.
There is a lot of good documentation that Ansible and Red Hat provide which should help get someone started with making Ansible useful. But once you get to more complicated scenarios, you will benefit from learning from others. I have not used Red Hat support for work with Ansible, but many of the online resources are helpful.
Not listed, but I've only used alternatives built into something like the Squirrel SQL editor. That one is semi-functional but lacking many features and, in some instances, just plain wrong. The only pro there is that it's freely available and works over ODBC. I've tried some of the other free ones like Creately but didn't have much success.
I used puppet prior to moving to open source Ansible and eventually to Red Hat Ansible Automation Platform. I appreciate the agentless approach of Red Hat Ansible Automation Platform and feel that its deterministic approach to applying code is superior to puppet
POSITIVE: currently used by the IT department and some others, but we want others to use it.
NEGATIVE: We need less technical output for the non-technical. It should be controllable or a setting within playbooks. We also need more graphical responses (non-technical).
POSITIVE: Always being updated and expanded (CaC, EDA, Policy as Code, execution environments, AI, etc..)
