The early 2000s were milestone moments for the cloud. Amazon Web Services
(AWS) entered the market in 2006, while Google revealed its first cloud service in 2007. Fast forward to 2020, when the pandemic boosted digital transformation efforts by around seven years (according to McKinsey), and the cloud has become a commercial necessity today. It not only facilitated the swift transition to remote work, but it also remains critical in maintaining company sustainability and creativity. Many can argue that the large-scale transition to the cloud in the 2010s was necessary to enable the digital-first experiences that remote workers and decentralized businesses need today.
Multi-cloud and hybrid cloud setups are now the norm. According to Gartner, most businesses today use a multi-cloud approach to reduce vendor lock-in or to take advantage of more flexible, best-of-breed solutions.
However, managing multi-cloud systems increases cloud complexity, and IT concerns, frequently slowing rather than accelerating innovation. According to 2022 research done by IntelligentCIO, the average multi-cloud system includes five platforms, including AWS, Microsoft Azure, Google Cloud, and IBM Red Hat, among others.
Managing Multi-Cloud Complexities Like a Pro
Your multi-cloud strategy should satisfy your company's requirements
while also laying the groundwork for managing various cloud deployments. Creating a proactive plan for managing multi-cloud setups is one of the finest features that can distinguish your company. The five strategies for handling multi-cloud complexity are outlined below.
Managing Data with AI and ML
AI and machine learning can help manage enormous quantities of data in multi-cloud environments. AI simulates human decision-making and performs tasks as well as humans or even better at times. Machine learning is a type of artificial intelligence that learns from data, recognizes patterns, and makes decisions with minimum human interaction.
AI and ML to help discover the most important data, reducing big data and multi-cloud complexity. AI and machine learning enable more simplicity and better data control.
Integrated Management Structure
Keeping up with the growing number of cloud services from several providers requires a unified management structure. Multiple cloud management requires IT time, resources, and technology to juggle and correlate infrastructure alternatives.
Routinely monitor your cloud resources and service settings. It's important to manage apps, clouds, and people globally. Ensure you have the technology and infrastructure to handle several clouds.
Developing Security Strategy
Operating multiple clouds requires a security strategy and seamless integration of security capabilities. There's no single right answer since vendors have varied policies and cybersecurity methods. Storing data on many cloud deployments prevents data loss.
Handling backups and safety copies of your data are crucial. Regularly examine your multi-cloud network's security. The cyber threat environment will vary as infrastructure and software do. Multi-cloud strategies must safeguard data and applications.
requires skilled operators. Do you have the appropriate IT personnel to handle multi-cloud? If not, can you use managed or cloud services? These individuals or people are in charge of teaching the organization about how each cloud deployment helps the company accomplish its goals. This specialist ensures all cloud entities work properly by utilizing cloud technologies.
Traditional cloud monitoring solutions are incapable of dealing with dynamic multi-cloud setups, but automated intelligence is the best at getting to the heart of cloud performance and security concerns. To begin with, businesses require end-to-end observability in order to see the overall picture. Add automation and causal AI to this capacity, and teams can obtain the accurate answers they require to better optimize their environments, freeing them up to concentrate on increasing innovation and generating better business results.