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  • Converged Infrastructure Solution

  • Optilyze offers a single, unified and converged Infrastructure solution for achieving an optimized end state within the client’s data centers. This converged Infrastructure solution addresses the Server, Storage, Networking and Application profiles of the client’s environment, and provides a highly efficient and dynamic Infrastructure in order to derive maximum business value from the IT investments.

    Optilyze’s syzygy methodology offers a unique 3-dimensional value proposition, where we align the business, technology and solution along with bringing industry perspectives to this converged Infrastructure solution.

  • Converged Infrastructure Solution

  • Optilyze offers five different automation tools to automate the effort in different stages of an IT transformation engagement. The swim lanes in this picture map to the 3 major stages in the lifecycle.

    Phase 1 (Feasibility Analysis) :- Prior to making commitments to this Capex intense effort if IT Transformation, most business would like to clearly define the goals of such effort, define criteria for success that are tangible, estimate the Return on Investment (ROI), Total Cost of Ownership (TCO) Savings, identify the risks and develop mitigation strategies.

    • Optilyze’s Value Modeler Engine serves a major role in this stage. Essentially, this tool is - "powerful infrastructure intelligence coupled with strong analytics". It consumes raw data provided by the client (usually high level at this early stage of the engagement), and within minutes, cleanses and maps the data, and will run analytics to come up with multiple options with optimization possibilities within the client IT footprint.

    • The deliverables of this tool include:
          • A rapid Assessment Report – with customized solution alternatives based on industry averages and historical information (from real projects)
          • Customized solution mapping with multiple optimization solution alternatives
          • A financial model to depict the solution’s impact to client’s cash flow, and other performance metrics such as ROI and payback
          • A detailed “what-if” and breakeven analysis

    Phase 2 (Assessment & Design):- Once the business case is established and there financial and technical benefits identified, the next stage of the engagement lifecycle is to perform an Assessment and develop a blueprint design for the effort. Typically, this effort is preceded by a data collection and true up phase. During this phase:

    • Digital scans are run to get an accurate read on the current inventory (both Infrastructure and Software) – Optilyze’s Analytics Engine will consume the data feeds coming from commercial tools such as HP MaM, BMC Atrium etc.

    • However, in some situations, it is not feasible to deploy tools to validate the inventory information. Instead, the only means to collecting actual data is to conduct interviews and validate this data. Optilyze’s Analytics Engine is flexible enough to consume the manually validated data as well.

    • At Optilyze, we offer our own Data Collector Appliance that has a rich feature set of discovering assets (including topology of applications, software, host infrastructure, network & storage devices, etc.), perform application dependency mapping and provides a robust visualization capability (i.e. Dashboards and Reports).

    • Clearly, Optilyze’s products have flexible architecture that can easily leverage the client's current investments and integrate with a data collection tool of their choice.

    Phase 3 (Build and Implement):- Once the target architecture is defined and finalized, it is time to transition the assets into more agile and optimized end state.

    • Optilyze’s Transition & Transformation Analytics Engine has a major role in this phase. This tool will indeed leverage the solution developed during the 1st and the 2nd phases, but also consumes incremental data (e.g. usually application dependency mapping, ownership of software/applications etc. are not available until this phase). The engine will take this additional information and develops an implementable transition/transformation plan (which includes details such as Wave definitions, Wave groupings, Wave sequencing, a project plan with all dependencies, a bill of materials to help with procurement etc.)

    • Detailed dashboards and comparative analytics are available to users to automatically look at the gaps between the predictive analytics and the actual implementation.

    • Eclipse Transition and Transformation Governance Tool:- This tool will be active throughout the lifecycle and will help measure and monitor the progress of the transition/transformation activities. In addition, it can be used as a perpetual tool that will constantly provide health-check monitors and deep analytics to visualize the steady state (as it compares to predictive analytics during the earlier stages of the engagement).

    • This Governance tool will have predictive analytics to monitor the usage trends, new workload consumption etc. and make continual optimization recommendations proactively.