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How to provide single-pane visibility across the business multicloud

You can’t manage anything effectively without a clear line of sight to all its moving parts. That’s why, as multiclouds grow more complex, you absolutely need a strong visibility layer to monitor and control it all.

Should you implement the proverbial “single pane of glass” for viewing your multicloud? How you address this imperative depends on the multicloud role you have in mind.

Different visibility platforms support the distinct requirements of different roles:

  • Multicloud platform administrators: Multicloud monitoring consoles provide continuous visibility into all platform, infrastructure, network, runtime and container components of across the multicloud. They support discovery, mapping, monitoring, security, diagnostics and troubleshooting of routing, traffic, workloads, apps and costs across disparate cloud platform, infrastructure and application domains. They also enable automation of deployment guardrails, role-based access controls, configuration and capacity management, and other policies at scale across cloud deployments. Examples include the consoles in IBM Services for Multicloud Management, Google Cloud Anthos and Cisco Systems Inc.’s CloudCenter Suite.
  • Multicloud application developers: Source-control repositories provide developers with visibility into all the models, code, APIs, business rules and other multicloud app pipeline artifacts through every step of the DevOps lifecycle. It serves as the hub for collaboration, reuse and sharing of all pipeline artifacts by all involved development and operations professionals. They also help information technology administrators maintain compliance, governance and change management policies, while simplifying internal solution discovery and ensuring that developers only use approved and compatible apps. Examples include the source-control repositories in Bitbucket, CloudForge, GitHub, GitLab and SourceForge. as well in public clouds such as Amazon Web Services, Microsoft Azure and Google Cloud Platform, as well in diverse private cloud platforms.
  • Multicloud data management professionals: Big-data catalogs support the needs of chief data officers, data analysts, data stewards and data engineers. The catalogs enable intelligent query and visualization of the data and metadata resources that are deployed across the multicloud. More enterprises are embracing cataloging solutions to reveal insights that would otherwise stay buried in their big-data portfolios. As noted recently by Alation Inc., today’s business analysts and information stewards can’t do their jobs effectively without the ability to search, query and share data-driven insights rapidly. Most catalogs use AI to intelligently scan data assets from across the enterprise, automatically add business context metadata, automate data tagging and domain/entity recognition, and drive curation and classification. Visibility of the underlying data structures may rely on such artificial intelligence technologies as genetic algorithms (to identify complex data substructures), natural language processing (to drive semantics-based modifications to data models) and machine learning (to parse clickstream, log, system, JSON and other “internet of things” data). Providers of big-data catalogs include Alation, Cambridge Semantics Inc., Cloudera Inc., Collibra NV, IBM Corp., Infogix Inc., Informatica LLC, Oracle Corp., Reltio Inc., Unifi Software Inc. and Waterline Data Inc..

In 2019 and beyond, Wikibon expects to see more multicloud solution providers incorporating AI to drive unified visibility across all three levels. The principal driver for this unified “single pane of glass” will be the democratization of AI development within self-service data analytics business cultures. As more development of AI apps is done by knowledge workers, rather than data scientists, they will demand a single, integrated view of:

  • distributed data assets to support agile exploration, modeling and training of AI models;
  • versioned, cleansed and sanctioned reference data and machine learning models to reuse in their AI apps;
  • compute, storage and networking resources for preparing, modeling, training, serving and optimizing their AI apps throughout the multicloud.

The next-generation business visibility infrastructure will converge platform monitoring, source-control repositories and big-data catalogs. It will provide a unified experience and control plane for users to connect, manage, monitor, secure and administer policy governing enterprise data and applications in clouds of all types. It will also embed AI-driven “intelligent recommendations” to automate the “next best actions” that accelerate task-specific productivity of all technical and business roles.

As Alation’s Stephanie McReynolds noted late last year in a Cube Conversation on SiliconANGLE Media’s video studio theCUBE, a unified view of enterprise data and other resources can be a powerful enabler for business transformation:

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