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How A Multi-Cloud Strategy Drives Greater Business Resiliency

By David Drai
January 24, 2022
in Artificial Intelligence, Emerging Payments, Industry Opinions
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How A Multi-Cloud Strategy Drives Greater Business Resiliency

How A Multi-Cloud Strategy Drives Greater Business Resiliency

Despite the built-in redundancies and reliability of the cloud, recent events have shown yet again that it’s not prudent for payments companies to rely on a single cloud platform provider.  In this era of major cloud computing outages, companies cannot put too much trust in the robustness of a single provider.

Outages will happen but the fallout for companies doesn’t have to result in extended downtimes, significant revenue losses and damaged reputations among customers. A multi-cloud strategy, supported by AI-driven monitoring and data analytics, will reduce the downtime caused by outages from multiple hours to mere minutes. It will keep businesses in business, regardless of failures in the cloud.

No provider or customer is immune from cloud outages. Amazon, for example, suffered three outages in December alone, the most significant occurring Dec. 8, when popular websites, retailers and third-party services were knocked offline for hours, causing sizable revenue losses in the middle of the critical holiday shopping season.

A multi-cloud strategy can help payments companies deflect the impact of outages by enabling them to quickly switch between different clouds when a downtime occurs in one of them. That strategy also improves cost management of cloud computing, giving organizations the option of shifting specific services to less expensive clouds.

But being prepared requires more than just subscribing to different clouds; organizations must recognize the signs of an impending outage and be ready to react swiftly. That is why many are turning to multi-cloud strategies that leverage artificial intelligence to assure real-time success in the event of eventual outages.

A vendor-agnostic, AI-driven data analytics and business monitoring approach can provide early detection of potential outages many hours before they occur. AI and machine learning (ML) detect anomalies in the business in real time, well before internal monitoring systems—or even the cloud itself—catch on. That allows organizations to adjust quickly, moving to another cloud when an outage strikes one cloud, keeping their own downtime to a minimum.

How should organizations prepare to take a proactive approach to multi-cloud? Here are four key steps:

  1. Adopt agnostic APIs and DNS protocols. Many big data service providers allow organizations to use one of the cloud services without accessing a unique API, but instead seamlessly using an API in a very short process. The service from this API can come from different clouds. For example, an organization that uses Amazon S3 cloud object storage can also use Cloudflare’s new R2 service that is fully API-compliant with Amazon S3. The Domain Name Systems (DNS) protocol – already built for a multi-cloud approach — is a standard protocol that allows organizations to leverage multiple DNS services seamlessly.
  • Focus on cost efficiencies. Several cloud cost monitoring services give organizations visibility into how and where they are spending their cloud resources, which lets them forecast and plan different scenarios to yield greater cost efficiencies, such as shifting to less expensive clouds. Kubernetes is another key technology that can drive multi-cloud cost management because it allows organizations to run containers in multiple clouds and achieve full redundancy. This also helps users combine all cloud cost management data into one dashboard or report that spans their entire enterprise.
  • Adopt CDN services. A content delivery network (CDN), consisting of a group of geographically distributed servers that speed delivery of internet content, provides full redundancy for the cloud while avoiding cloud stickiness. The CDN can cache the data from multiple clouds without being affected by downtime in one of the clouds.
  • Invest in agnostic AI and ML-driven business monitoring. This allows payment companies to detect outages several hours before they occur, letting IT teams take real-time actions to mitigate any damage, or migrate to another cloud without experiencing any downtime. And because the monitoring and analytics are agnostic, it lets them work from the same monitoring platform even if they move between clouds.

At a time when outages have become common occurrences, payment organizations must move to multi-cloud strategies buttressed by AI and machine-driven analytics. By implementing that strategy, they can create more resilient, productive, and enjoyable web experiences for their organizations and relevant audiences.

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Tags: Artificial IntelligenceCloudCloud Computingcloud migrationData AnalyticsIndustry Opinionsmulti-cloud approach

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