An EA repository is a collection of artifacts that describes an organization's current and target IT landscape. It is intended to provide a centralized place for the storage and retrieval of architecture artifacts. An EA repository should have the key logical components to the architecture metamodel, domains, principles, capabilities, governance documents, and reference library.
Organizations benefit from having a clear and documented approach or framework in which to conduct enterprise architecture projects including artifact templates, capability maps, and more. It stores the “as-is” architecture so gap analyses can be done to build “to-be” architectures and help identify opportunities to shorten time-to-market, reduce costs, and identify operational and technology improvements.
With all of these components, it’s no small undertaking to get the right information into the EA repository – as well as keeping it updated (critical for EA success). Enterprise architects are drowning trying to keep up with data accuracy, unable to reach the finish line as companies are dynamic and ever-evolving, and thus the finish line keeps moving further. This frustration is what architects mean when they talk about “death-by-repository.” In this scenario, EAs spend all their time trying to keep an "as-is" architecture up-to-date, and thus, do not have the bandwidth to practice "to-be" architecture that is focused on business outcomes.
As architects build and maintain an EA repository they may be doing this manually by importing spreadsheets from Excel, CMDB, etc. Of course, manual takes a lot of time and is prone to error. While it’s possible to begin building a common repository from scratch, this can become time-consuming, and EAs run the risk of falling behind. Further to this point, the design of the repository needs specific consideration, given many of the people using the repository won't have the everyday knowledge of where and how to find information. With proper tooling, however, there are easier ways EAs can begin to populate and design the EA repository.
With discovery and connectors that reach across technologies creating a common language, death-by-repository fears are eliminated. At its very core, the purpose of an EA repository is to drive connectedness to enable common insights, and overviews of relationships and interdependencies. Reducing the friction of keeping an EA repository updated benefits the entire company not only with more accurate data for stakeholder decision-making, but it also allows EA to do other more value-oriented projects that support business outcomes. Further, consider that on average, developers spend only 5% of their time writing new code, 20% modifying the legacy code and up to 60% understanding the existing code. Reducing time and manual work will free up time for developers and architects to focus on “to-be” future scenarios.
Enterprise Architecture deals with many concepts including applications, technologies, processes, and data. To facilitate the population of an EA repository, there are four types of discovery to build, manage, and optimize information that can save considerable time and costs – and increase the quality of data and decision-making.
There are two ways to connect access points and thus share data, through: 1) Application Programming Interfaces (APIs); and 2) Connectors.
An EA tool with a dynamic connected repository provides the ability to browse and drill down on relevant details to enable architects and developers to conduct impact analyses and plan migration projects. Tools that use APIs and Connectors to conduct discovery are especially useful as they allow enterprise architects the ability to start providing value on Day One.
Third-party integrations or connections with ServiceNow, CMDBs, Flexera, SAP, Salesforce, Minit, structured and unstructured databases such as MongoDB, and many other technologies help EAs build a repository instantaneously and maintain it with quality information.
When an EA tool uses APIs and Connectors to connect and build upon data, the possibilities are almost endless.
Discovery is the population and maintenance of applications, processes, and data, so companies can manage and optimize their EA repository and feel confident about its accuracy and quality. It uses open APIs, integrations, and connectors that fetch the right data. Discovery can also be associated with artificial intelligence to detect patterns and perform advanced analyses.
The benefits are real:
To summarize, discovery not only speeds up the population of the EA repository, it frees up enterprise architects to focus on business outcomes that can support agile delivery and digitization. And ultimately, it ensures the EA repository is a single-source-of-truth for IT standards that can be relied upon by users and stakeholders to make smarter, faster decisions.
For more information, view MEGA’s eBook detailing the ROI of Business-Outcome-Driven Enterprise Architecture.