Google Search Appliance Deployment Governance and Operational Models March 2014
© 2014 Google
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Deployment Governance and Operational Models This document discusses several strategies related to governance of a Google Search Appliance (GSA) solution.
About this document The recommendations and information in this document were gathered through our work with a variety of clients and environments in the field. We thank our customers and partners for sharing their experiences and insights. What’s covered
This guide covers publishing best practices, data governance strategies, content on-boarding processes, and solution ownership models.
Primary audience
Business architects, solution architects, technical architects, GSA administrators, and enterprise content management system administrators working on the design of an enterprise search solution using the Google Search Appliance
IT environment
GSA in a centralized, decentralized, or third-party IT environment
Deployment phases
GSA planning and deployment
Other resources
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All the GSA Notes from the Field are relevant to this particular manual as topics that are considered are explained more in depth in other documents. Learngsa.com provides educational resources for the GSA. GSA product documentation provides complete information about the GSA. Google for Work Support Portal provides access to Google support.
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Contents About this document Chapter 1 Content Publishing Governance and Best Practices Overview Determination of relevance and ranking Content creation and structure Relevancy tuning options User experience considerations Chapter 2 GSA Ownership and Chargeback Model Overview Ownership by a centralized IT organization Ownership by an individual business/functional unit Ownership by a third party in a hosted environment Ongoing operations and support Ongoing search governance Chapter 3 GSA Content On-boarding Models Overview Considering content sources for indexing Content repository/platform vs. business application on-boarding model Ongoing on-boarding and maintenance process Handling of sensitive data that is newly searchable on the GSA Chapter 4 GSA Environment Approach Overview Lab / Development environment Testing / QA environment (optional) Production environment Summary
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Chapter 1 Content Publishing Governance and Best Practices Overview The Google Search Appliance provides algorithms “out of the box“ that effectively index and rank common business documents. Users don't have to create documents catering to the GSA indexing and ranking algorithms as the GSA is effective in indexing unstructured content. There is always room for improvement by providing the GSA additional signals that might improve ranking. These signals include, but are not limited to, appropriate metadata such as title, authorship, published date, and compelling content in their documents. The more differentiating signals the GSA can consider in ranking the relevance of content, the better.
Determination of relevance and ranking The Google Search Appliance leverages multiple factors to rank search results, providing high relevancy right out of the box. Many algorithms used by the search appliance have been optimized for enterprise content, helping your users drive more value from your existing corpus of the most widely used business documents, including word processing, spreadsheet, and presentation content, by finding them more efficiently. Additionally, the Google Search Appliance offers intelligent yet intuitive tuning options, including node biasing, collection biasing, source biasing, date biasing, and metadata biasing. Also, the search appliance ranking framework enables administrators to use server logs and other enterprise-specific information to fine tune results rankings programmatically for an unlimited number of URLs. With billions of searches as a basis for research and thousands of engineers dedicated to search technology, Google constantly drives for leadership in search quality and innovation. Although not all Google Webmaster Tools are applicable to enterprise search and the GSA, the Google Webmaster Tools Help provides some good guidelines that affect how content is ranked by a Google search algorithm.
Content creation and structure There are many types of documents that the GSA indexes. Because the GSA supports a wide range of document types, you should consider various guidelines for best preparing a particular document type for indexing. This section provides guidelines for preparing the following document types for indexing: ● ● ●
Microsoft Office documents PDF documents HTML documents
Also included are guidelines for document feeds and data classification/taxonomy.
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These guidelines deal mostly with the indexing of additional metadata along with document content. Metadata can enrich content in the GSA’s index. For just one example of the type of metadata attributes that can be added to enrich document classification, refer to the Dublin Core of metadata elements, which provides standards for a base set of text fields that can describe a resource. Content owners can follow some document creation principles that will help effectively distinguish and uniquely identify their documents. This point is important, as enterprise documents have less of a defined URL structure that is useful for determining relationships on the world wide web. For this reason, unique document identifiers in an enterprise corpus of documents are significant.
Microsoft Office documents In the properties of a Microsoft Office document, populate the following fields: ● ● ●
Author Title Comments
If there is a tendency to create a large number of documents that originate from templates, the importance of changing default document properties should be heavily stressed.
PDF documents In the properties of a PDF document, populate the following fields: ● ● ●
Author Title Creator
If the document is not authored directly by a PDF publishing tool, make sure these properties are populated in the source document before it is converted to a PDF.
HTML documents In an HTML document, include the following information: ●
content<br />
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description (handwritten or programmatically generated)—be sure to write quality descriptions, even though they won’t be displayed on the page itself<br />
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Be sure to differentiate descriptions of different pages. To restrict indexing of certain page content, use googleoff tags.<br />
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Document feeds The GSA feed protocol allows for indexing of metadata along with the underlying content. Include in the document feed any other metadata that are otherwise not present in the content, which can enrich the indexed content.<br />
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Data classification/taxonomy If documents that are to be indexed by the GSA are associated with an enterprise data classification scheme and/or taxonomy, make sure that ontological information is being indexed by the GSA. Feeding of ontological information along with the content is not mandatory, but it can enhance the search solution. The taxonomy can be used in combination with metadata filters to restrict document searches at certain levels in the overall hierarchy. Depending on the document type and its source, indexing taxonomy information might require an integration process that can associate the document classification with the actual document in the index. A detailed investigation will be needed to see how to associate this information at GSA indexing time.<br />
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Entity Recognition The Entity Recognition feature of the GSA can be used to automatically tag documents with metadata at index time according to predefined rules contained in text dictionaries or via an XML structure that allows matches based on terms or regular expressions. Common or standard business terms for your organization would be great candidates for defining entities. If an enterprise taxonomy has been identified, this would also be a great candidate for including in Entity Recognition rules. That way, even though some documents may not be tagged with these terms, the GSA can provide the association at index time via these rules.<br />
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Relevancy tuning options The Google Search Appliance contains features that empower a search administrator to tweak result biasing for the entire organization or select search users. Search result ranking can be biased on date, metadata, source, collections, and feed source. For example, if you have multiple content sources feeding the GSA, with SharePoint being one of them, and you notice that SharePoint results are undesirably not being ranked high enough in the result set, you may choose to bias the SharePoint content source to improve the ranking of the content. For details on how to configure a result biasing policy, see the Serving > Result Biasing help page.<br />
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The following table provides an overview of features that may affect how results are displayed to users. Feature<br />
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Source Biasing<br />
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Via pattern matching, bias one source over another.<br />
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Date Biasing<br />
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Assign more or less importance to document creation date.<br />
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Metadata Biasing<br />
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Bias documents that have specific metadata attached.<br />
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KeyMatches<br />
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Although KeyMatches are technically a suggestion feature and not part of organic search results, you can use them to promote documents for certain queries.<br />
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Query Expansion<br />
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Use a query expansion policy to expand search queries terms into other terms (synonyms).<br />
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Self-Learning Scorer<br />
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When Advanced Search Reporting is enabled, the GSA uses the Self-Learning Scorer to analyze clickstream data and promote certain search results over time. As an example, for a given search query, if users consistently click the second result on the page instead of the first, that result will eventually move up to overtake the first position on the page.<br />
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Host Crowding/Filtering<br />
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Enable the GSA to filter out any combination of: ● ●<br />
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Results from the same path Results with duplicate titles and snippets<br />
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Ranking Framework<br />
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Specify a per-URL biasing. Take note that this is a very complex solution to manage and should only be tried as a last resort.<br />
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Stopwords<br />
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Use stopwords to remove certain terms in the query from being used when performing search. Take care when using this feature as this can have wide ranging implications if used as a solution to a particular problem.<br />
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Collections<br />
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Break content into different collections to restrict the document corpus available to a search query.<br />
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User experience considerations Modifications to the search experience can also go a long way in how your users perceive your search deployment. For information about some best practices for options relating to improving users' search experience, see Search Experience Best Practices. For detailed information about user experience options, see GSA Notes from the Field: User Experience Guide.<br />
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Chapter 2 GSA Ownership and Chargeback Model Overview There are three main search solution ownership models that apply to GSA deployments: ● ● ●<br />
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Ownership by a centralized IT organization Ownership by an individual business/functional unit Ownership by a third part in a hosted environment<br />
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Each model has specific characteristics and might have certain advantages or disadvantages based on the landscape at your organization. When choosing a model that suits you, take into account the following considerations: ● ● ● ● ● ●<br />
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Funding and charge model Process definition Accountability Metrics being used to report on usage and/or value Reporting model Existing third-party vendor agreements for hosting and/or services<br />
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Ownership by a centralized IT organization In organizations that have a centralized IT model, It is common for a centralized IT shared service organization to own the GSA Search Solution. In this model, there is a core group of resources that have knowledge of GSA functionality and business impacts of feature realization and content source ingestion. This group also has scope of the context of the entire enterprise, not specific to an individual business/functional unit. The group would have responsibility for the following functions: ●<br />
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Identifying and planning a phased approach to roll out search across the organization<br />
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Considering the requests of individual business units and content owners, who would want their content indexed on the GSA and exposed to search users across the enterprise<br />
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Ownership by a single group within an organization should also streamline provisioning and procuring search.<br />
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Cost and charge models There are a number of ways to calculate how to fund and support the search solution: ●<br />
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Provide blanket IT funds to the shared service search organization and don’t charge business units for GSA usage<br />
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Recoup the cost of deploying and supporting the GSA by charging individual business units for their usage: 1. Figure out the base GSA costs to operate, including, but not limited to license cost, data center, racking, support, and so on. 2. Figure out a percentage of the GSA that a Business Unit is utilizing in order to come up with a value to charge by multiplying the percentage by the total cost of the GSA. Utilization can be some factor depending on percentage of document license utilized or search query utilization and/or volume. 3. Charge for GSA configuration/customization based on a time and materials basis, where each hour worked would have to be covered. For customization, especially front end XSLT changes, a hybrid model might be most efficient, as the business unit might have a good idea of how they want their search experience to look.<br />
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Ownership by an individual business/functional unit In organizations where the IT model is decentralized, it is common for individual business/functional units to drive the GSA search solution based on their individual needs. Because business units know their system, processes, and user usage patterns best, they are in a great position to deploy a search solution that would be most valuable to their users. To another degree, having end users shape the end state solution can be valuable as their needs are put front and center. Having individual business units own the search solution may also have the potential to usurp commonplace IT governance processes and get to market faster. In the ideal case, deployment of the GSA by a business unit may become a model for how the GSA is extended to the entire enterprise. Even though individual business/functional units may not be following standard IT processes, it is still important to focus and put thought into the following consideration to be able to gauge the success of the search deployment: ● ● ● ● ●<br />
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Funding Some basic process definition Support model moving forward Metrics being used to report on usage and/or value Reporting model<br />
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Even though search may not be deployed according to standard IT practices, having data and a baseline that can shape future search improvements is very important.<br />
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Depending on the IT landscape at your organization, this model might imply that the GSA deployment may not be in compliance with all IT governance policies in place, in areas such as audit, branding, platform, architecture, and so on. Search deployed within such a model might have the implicit restriction of not being able to expand to repositories controlled outside of the business unit. This model is very good for special-purpose search applications that are serving to a particular set of users that may not be representative of the entire enterprise.<br />
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Cost model Deployment of the GSA by an individual business unit can be funded by calculating the cost to procure the GSA as well as the effort it would take to craft the solution. A support model would also have to be developed. Even though the search solution would be deployed and owned by a business unit, it may be most efficient to document certain processes and outsource ongoing support to a third party according to any outsourcing precedents within the company (either in-house or third-party).<br />
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Ownership by a third party in a hosted environment It might make sense for an organization to outsource the GSA search solution completely to a third-party hosting provider. This model can be defined by the following two general approaches: ●<br />
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Define and develop the solution in house, and transition operations to a third party.<br />
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Procure services from a third party to help define and develop the solution as well as host it going forward or choose from a third party’s plain GSA search hosted offering.<br />
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Such an agreement with a third party should be pursued according to existing vendor procurement guidelines and precedents. This model is advantageous because a third party provider that specializes in GSA search will already have resources and infrastructure to develop and provide search. This approach also has the advantage of keeping costs down. A downside can be flexibility and ease of deep integration with existing systems. This may not be a fit in highly secure environments with requirements for the on-premise storage of sensitive data.<br />
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Cost model You should consider the cost models of ownership by individual business units and ownership by a centralized IT organization and evaluate them against the proposed cost for a hosting solution by a third party. As this model is governed by the terms and conditions of a provider agreement, all aspects should be negotiated and settled up front. An important aspect to the agreement would be the support model as well as applicable service level agreements. Depending on the agreement in place, this model may be more attractive in terms of up front costs, but may offer less solution flexibility going forward.<br />
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Ongoing operations and support As touched on briefly in the preceding sections, the GSA search solution must be maintained to a certain degree moving forward. First and foremost, help on issues from Google for Work Support is available for the duration of your GSA license. That being said, there needs to be a person or a group familiar with and responsible for the search within your organization. This person or group should: ●<br />
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Have an understanding of the GSA search architecture, as deployed within your organization<br />
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Have an understanding of the GSA features and how they are configured as part of GSA Admin functionality (either through the Admin Console or Admin APIs)<br />
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Be a guardian of any processes/standards put forth for on-boarding new content onto the GSA<br />
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Coordinate and plan any front end or user experience enhancements proposed<br />
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Run GSA search reports or provide assistance to anyone requesting a GSA search report<br />
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Stay up to date with new GSA releases and plan for regular GSA version updates (for example, yearly)<br />
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Be the point of contact for any GSA issues and raise any Google Support tickets when required<br />
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Ongoing search governance Regardless of the type of search ownership model, it is important that a core team responsible for search meet regularly to assess the effectiveness of search, and review outstanding priorities. For example, a core team of the GSA business sponsors, system owners, administrators, and end-user stakeholders might meet quarterly (or sooner if search is a high priority business area) to review user feedback, search statistics, and the prioritization of improvement activities or upcoming areas to be “on-boarded” into the search solution. Analytics and metrics, and the way they shape solution refinement, are other important aspects in continuing search governance. Search can be an important business indicator for an organization, with intelligence gathered from search analytics and metrics. The integration with an analytics service, such as Google Analytics, or a custom-built solution can provide such insights as: user sentiment, pain points, hot topics, guidance on product development, and so on. Having a strategy for gathering and analyzing search metrics will drive more value from the search solution in areas that may not be immediately visible.<br />
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Chapter 3 GSA Content On-boarding Models Overview This chapter addresses strategies and approaches for on-boarding content sources available in your enterprise to the GSA. Even though the GSA, in a lot of cases, should be able to discover, crawl, and index content without much effort, it is best to plan for and have a strategy of how the integration of different content sources and/or applications will commence. Items such as security, integration type, metadata available, entity definition for Entity Recognition, and the impact on the user interface, are important considerations for a successful integration.<br />
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Considering content sources for indexing When deciding which platforms to on-board to the GSA, think about the considerations in the following table and prioritize platforms based on them.<br />
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Consideration<br />
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Comments<br />
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Users and user types affected by the content integration<br />
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Aim for platforms that have the highest impact first.<br />
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Ease of integration<br />
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In order of increasing difficulty of integration: direct crawl, connector available, crawl through proxy, feed needs to be developed, connector needs to be developed.<br />
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Security authentication and authorization mechanism required<br />
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Systems that integrate with security mechanisms that are directly supported by the GSA provide the easiest integration. Systems that require custom auth integration are more difficult to integrate.<br />
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Search front end customization required to provide the most value to the search experience of the platform<br />
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There are times when providing the most value out of content integration with the GSA requires some front end modifications to expose such things as: ● ● ● ●<br />
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filters categories metadata in search results custom navigation processes<br />
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In order of increasing difficulty of integration: default XSLT, minor XSLT modifications, major XSLT modifications, custom application parsing and displaying the XML provided by the GSA. Maturity of metadata available in the content source<br />
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Although metadata is not required for indexing, it can help in terms of enriching the content in the index and by giving you more options for shaping the search experience. Some content sources, by their nature, have metadata available “out-of-the-box,” while other sources require adhering to a process at publish time. Also consider augmenting documents with metadata at index time programmatically through a custom process, if desired.<br />
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Augmenting document metadata through Entity Recognition<br />
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The Entity Recognition feature of the GSA can be used to enrich content with entities extracted through the definition of entity rules based on dictionaries or regular expressions. These rules, when defined, will tag the documents with metadata at index time. This feature can be used to assign metadata to documents, which may otherwise not be tagged with metadata.<br />
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Content repository/platform vs. business application on-boarding model There are two high-level approaches to consider in selecting content for on-boarding onto the GSA: ● ●<br />
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Content ingestion by platform Content ingestion by business application<br />
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There are different considerations to make based on these two models. Some of these considerations are discussed in the next sections.<br />
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Content ingestion by platform With content ingestion by platform, most or all of the documents within a content repository will be indexed, regardless of which applications it is driving. Deciding to move forward with a content ingestion by platform model might be fitting for an organization where search is centrally funded and owned by a centralized search team. In this model, on-boarding of content will be done for one repository or platform at a time, regardless which applications or business units have content in the platform. This approach may also make it easier to roll out the concept of “universal search” across the organization because the solution will be considered holistically and not application by application. One example of this approach is indexing content from Livelink ECM. In this approach, the entire Livelink platform would be indexed on the GSA during the course of single deployment project, regardless of which business units or applications store documents in the system. You should prioritize the content sources that you are considering for integration by thinking carefully about the factors listed in Considering content sources for indexing.<br />
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Content ingestion by business application With content ingestion by business application, most or all the documents from within a specific business application are indexed, regardless of which platform(s) are the source of the content. Proceeding with a GSA deployment where specific business applications are chosen for integration might be fitting for an organization where search is centrally managed, but charged back to the business units they are serving. It is also a fitting model when a business functional unit, and not a shared services team, owns the GSA search implementation. In this approach, specific business applications would be targeted and prioritized for indexing on the GSA. One example of this approach is indexing content from an HR Hiring Candidate Application Management System, whose applications are stored in an Enterprise Content Management System. When on-boarding by application and not by platform, the goal would be to index just these specific hiring applications and not the entire content management system. Application candidates for indexing should be prioritized similar to platforms, using the factors in the section Considering content sources for Indexing.<br />
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A primary goal of indexing application content on the GSA should be to increase user productivity with that application. When thinking about use cases or end user workflow, identify areas where the GSA could simplify the process. For example, in an application where documents can be edited, in addition to displaying the document in search results, also include a link to the edit mode of the document, so if users want to edit content, they can be taken directly to the edit mode instead of having to click through an intermediate step. Any optimization or simplification of user processes provided by the GSA will be a benefit.<br />
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Ongoing on-boarding and maintenance process The GSA search solution will continue to evolve as your business evolves and more content is created across the enterprise. An organization should be prepared for handling future requests for on-boarding content onto the GSA after the first or initial deployment phases. The first deployment will teach you a lot and will continue to serve as a framework for adding to or adjusting the solution going forward. An elaborate process is not necessary, but we recommend having some template of a search specification available that can be used to guide the design and implementation of the content integration. The specification document should contain functional and technical information about the integration. Without some guiding document, the scope of the implementation may become unmanageable or requirements may get lost and end up not implemented. Google recommends the process phases described in the following sections: 1. Initial content analysis 2. Development/Configuration 3. Testing and roll-out Please take note that the recommended process doesn’t take into account resourcing and project management tasks that should be considered when taking up such an effort.<br />
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Initial content analysis Initial investigation of content integration with the GSA would be triggered by a request that comes in or an area being identified, which contains content that is not integrated with the GSA and is not being returned in search results. In this phase, conduct the following analysis: 1. Analyze the on-boarding factors identified in Considering content sources for indexing. 2. Document requirements and populate the “search spec” for this particular system. a. Consider requirements for shaping the user experience. b. Be sure to determine how the newly acquired content and UI specifications will integrate with the existing content and UI. 3. Analyze what metadata is available in the identified system and how it can shape or enhance the search solution. a. Consider any effort needed to clean up metadata or augment content with metadata if desired b. Define entities for Entity Recognition to augment metadata that otherwise may not be available 4. Identify the points of contact that will act as SMEs going forward.<br />
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Development/Configuration In the development/configuration phase, perform the following steps: 1. Integrate content—This includes the deployment of any off-GSA components needed like connectors, SAML Bridge, and so on. 2. Develop the UI components that are needed.<br />
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Testing and roll-out In the testing and roll-out phase, perform the following steps: 1. Conduct a System/Integration Test—Is the content being indexed and displayed correctly? 2. Conduct a Relevancy Test—How does the newly acquired content mix with the existing content in the “default” or “universal” collection, which contains content from many sources? 3. Conduct a Performance/Load test or analysis—How is the additional search user load going to affect performance of the existing solution?<br />
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Handling of sensitive data that is newly searchable on the GSA The GSA is a powerful search tool, which allows users to find documents that they previously may have had no means to find. There are cases where shortly after deployment, users start finding documents in their search results that they should not have access to. These are cases where the GSA correctly respects permissions on the documents, but the permissions in the source system are too open in the first place. These documents must have their permission set to restricted to keep them from showing up in search results. When deploying the GSA, a best practice is to move forward with a mitigation plan for breaches of sensitive data. This will allow planning and mitigating through process development, communication, and user training in your organization. Often times, HR content may be at the most risk for this type of issue. Consider a simple audit of a sample set of HR data to inspect current permissions. Consider keeping sensitive content out of the first deployment phase to ensure users and admins become familiar with the GSA. This allows the admins to be better prepared to deal with unintentional data leaks due to unrestricted permissions on documents. The following is a sample process for dealing with incidents where the GSA seems to return sensitive search results, which should have their permissions restricted: ●<br />
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Setup an email alias that will handle users reporting cases where documents should be restricted.<br />
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Designate a Business Analyst (BA) type role for being the point resource for handling each case that comes in.<br />
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This person should be able to map the document in question to the content source in which it lives.<br />
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This person should be able to communicate effectively with the owners of the content source to determine the optimal permission setting for the document in question.<br />
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Just before Go-Live, the process for dealing with documents that should be restricted should be clearly communicated.<br />
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Users should be given the email alias where they can send incidents.<br />
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Users should be provided with a sample set of information that they should provide when reporting an incident.<br />
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For any report that comes in, the BA can determine severity, with the option of temporarily or permanently removing the document from the front end of the GSA immediately. This can be a temporary removal until the content owners can confirm access levels.<br />
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Incident tracking can be done in a ticketing system of choice.<br />
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Chapter 4 GSA Environment Approach Overview It is advantageous to test changes in a separate environment before releasing them to end users. As with any type of server or application, a small change to a configuration could have unintended consequences, so a proper testing strategy and staging environment is recommended for changes to any search application. The following environments are recommended for successfully developing, testing, staging, and rolling out the solution to production: ● ● ●<br />
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Lab/Development environment Testing/QA environment (optional) Production environment<br />
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Although ideal, physical environments are not necessary. For example, Lab/Development and Testing/QA can be built out on the same GSA by using a combination of different front ends and collections.<br />
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Lab / Development environment A development environment for the Google Search Appliance simply means replicating the production environment to provide a separate area for developing and integrating configuration changes and new enhancements. The development environment should include access to the same content types and sources as the production environment, but it might include a restricted or reduced set of documents. All integration components being deployed, such as the SAML Bridge or connectors, should have matching development instances. The development environment does not have to be sized according to production standards. It can be downsized accordingly as it doesn’t have to take into account the document size or performance requirements of a production system. A common development setup includes a non-production search appliance that does not serve results to most end-users. All configuration changes, updates, and enhancements are tested on this search appliance, and then pushed to the next environment stage when ready. Where possible, avoid using hard-coded naming conventions that might complicate migrating configurations. For example, dev_collection or test_frontend would need to be renamed to move to production. The Google Search Appliance Admin APIs, introduced in software release 6.0, enable you to export and import fine-grained configurations (for example, individual KeyMatches) or coarse-grained configurations (the entire configuration for a search appliance). For information about the Admin APIs, see the Administrative API Developer Guides, which are linked to the public GSA documentation page. The development environment can also be used as a testing environment before the production release of realized requirements.<br />
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Testing / QA environment (optional) The Testing/QA environment is similar to the development environment, as it is a replicated, nonproduction environment. This environment should be kept stable for any testers accessing the system. Pushes for deployment components, configuration changes, or front end changes should be done in phases according to a configuration management process. The testing team should be notified of any changes to this environment that could impact their testing. Because the GSA is a product that indexes and doesn’t modify sources of content, the GSA QA environment can point to either QA or production sources of content, with different considerations for both approaches. Performance testing can be executed in this environment to develop a baseline, taking into account that the production environment will still outsize this environment in terms of hardware specs.<br />
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Production environment The production environment is a live user environment that should be sized according to requirements for index size and performance. Changes to the production environment should be introduced under a strict configuration management process. All changes being migrated into production should be tested and signed off while in the QA environment. Operational outages should be taken into account when migrating into production. Any changes should be made at an optimal time, with the least amount of business impact.<br />
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Production backup / disaster recovery environment In most cases, particularly where search is a business critical application for users, it is important to have a backup/disaster recovery environment as part of the production environment. A backup/disaster recovery environment replicates the production environment and can be used for situations of planned or unplanned outages. This environment will typically be an exact copy of the production environment, with similar infrastructure and capacity.<br />
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Production environment capacity planning considerations Replicated production environments are not always used just for backup/disaster recovery capabilities; they can also be used for capacity planning. If one GSA cannot handle all the serve-time search load coming to it, a GSA replica can be used in a load balanced configuration for capacity planning purposes. That way, the serving load will be distributed between multiple GSAs serving the same content. It is important to note that due to the mirroring feature of the GSA, only one GSA will normally acquire new content, while pushing and syncing changes to replica GSAs in the configuration.<br />
<br />
19<br />
<br />
Summary The topic of governance is not universal and will differ from organization to organization. The sections in this document present some concepts you can adopt when you establish governance around your newly deployed GSA search solution. Keep in mind that these concepts can integrate with your existing processes in a number of ways. As always, just like the architecture around the GSA, try to keep governance processes as simple as possible so deployments can be quick and iterative. Try to use the GSA to usurp certain existing IT processes in place that will allow you to quickly deploy and iterate the search built upon the GSA.<br />
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20<br />
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