Significant part of the infrastructure spend in either private or public cloud is wasted due to various reasons such as (i) wrongly sized infrastructure owing to lack of performance data or sized purely based on peak considerations (ii) unused VMs or zombie VMs (iii) wrong over-provisioning ratios (iv) wrong choice of storage etc. MapleLabs suite of solutions helps users get a better visibility into their workloads, right-size the infrastructure and optimize their data centers and hybrid cloud environments

Features

Profiler
  • Monitors & characterizes an individual workload or a large datacenter
  • Simple workflow to install within your datacenter & setup monitoring
  • Support for wide range of infrastructure and applications
    • vCenter, SCVMM, AWS, Linux Server, Windows Server
    • MS-SQL Servers, Oracle, MySQL, Postgres, MongoDB
    • Storage arrays
  • Support for both agent and agentless monitoring
  • Downloadable reports in JSON and CSV formats
  • Pre-packaged charts, analysis & reports:
    • Overall utilization analysis of all hosts and datastores
    • Analysis of overprovisioning ratios and identification of hotspots
    • Identification of dark or unused VMs
    • Mismatched storage types
Sizer
  • Identifies optimal node configurations for workloads based on constraints such as compute performance,
    storage performance, storage capacity and Price
  • Advanced features for sizing Hyperconverged clusters
    • Support for wide variety of workloads including VDI, Generic VM, Databases, Exchange & others
    • Model based inputs or ingest profiler outputs
    • Design homogenous or heterogeneous clusters
    • Automatic partitioning of workloads to clusters
    • Easily consumable reports on sizing analysis and recommendations
    • Support for CPU translations required for workload migrations across multiple processor generations
  • Recommendations for optimal node choice in public clouds
    • Support for AWS, Azure & GCP
    • Uses profiler data to recommend optimal node based on compute, storage and network characteristics of workload
    • Recommendations on choice of cloud and optimal nodes based on price comparisons
    • Evaluate suitability of a workload for public or private cloud