Ask any CIO for their thoughts on multi-cloud \u2013 where data and applications flit seamlessly across all the public clouds, private cloud and on premise, for lowest cost and best performance \u2013 and you\u2019re likely to get one of two distinctly divergent responses.\nOne typically comes from the uninitiated, who haven\u2019t yet moved computing to a public cloud like AWS, Microsoft Azure or Google Cloud. They are wholly unimpressed with the concept. Because they were under the impression that that\u2019s how the cloud is supposed to work anyway.\nAnd the other? It\u2019s from those who once had the same impression as the others. Then they moved data and workloads to public platforms. Now, they are left wondering if true multi-cloud is even possible.\nActually, it is possible. In fact, we\u2019re now starting to see a new stable of products crop up to address today\u2019s multi-cloud shortcomings. In January, Gartner coined the term \u201cCloud Data Ecosystems\u201d for this emerging class of products. Analyst firm 451 Research late last year knighted them \u201cEnterprise Intelligence Platforms.\u201d And Cloudera, which boasts arguably the most comprehensive platform in the category, last summer dubbed the category \u201cEnterprise Data Cloud.\u201d\nI call it Cloud 2.0. And when all is said and done, it will turn out to be everything Cloud 1.0 was supposed to be.\nWhat goes up\u2026\nLured by the promise of seemingly boundless on-demand storage and compute capability, many early adopters anxious to shed datacenter capitalization decisions jumped into the cloud model with both feet. But many soon found their feet stuck where they\u2019d landed.\nThat\u2019s for two reasons. First, they were locked into long-term contracts, which they signed to secure preferential pricing without knowing how much capability they\u2019d actually need. So even though they were paying a fixed rate, in practice they ended up paying more. Some only ended up using a fraction of the capability they reserved. And those who underestimated how much storage and compute they\u2019d need ended up facing eye-opening overage charges.\nThe second reason is they learned how difficult it can be to bring data home from cloud services with all associated metadata intact. Abandoning historical records and other descriptive, contextual associations dramatically diminishes data\u2019s value for future analysis.\nIn part as an effort to wriggle free, enterprises increasingly invested in their own private-cloud capability, building out either by outsourcing to a third-party datacenter, or by investing in good old-fashioned, back-down-to-earth, on-site capitalization. The goal was to max out their own resources, and then burst up to the cloud only when absolutely necessary.\n\u201cThere\u2019s definitely a lot of repatriation activity going on,\u201d Henry Vail, Technical Director for the Software-Defined Infrastructure business in at Lenovo\u2019s Data Center Group, told me. \u201cCustomers really like the concept of hybrid cloud. So, they\u2019re building or outsourcing their own private cloud.\u201d\nIt\u2019s important to understand that enterprises that have ventured into the cloud are just as enthusiastic as ever about the cloud model and remain committed to it. Even some that haven\u2019t yet taken the plunge into the actual cloud are investing in \u2013 and benefiting from \u2013 the flexibility and efficiency of virtual machines, containers and microservices.\nCloud providers are all responding with hybrid-cloud options of their own. Late last year, in fact, the big three public cloud providers each unveiled or enhanced programs to extend their services to private cloud deployments:\n\nAWS announced its own infrastructure-as-a-service offering, AWS Outposts\nMicrosoft, which first introduced Azure Stack to extend its cloud services into customers\u2019 datacenter in 2017, released Azure Arc, which extended Azure Stack\u2019s umbrella to include a wider range of hardware and services, and\nGoogle disclosed its own hybrid-cloud platform, Google Anthos.\n\nEnter multi-cloud\nThe services are all welcome extensions, as far as they go. That is to say that while they\u2019re all extending their platforms from their own public clouds down to hosted private clouds and on-premises datacenters, none are doing much to help their customers wander outside their own domain and into competitors\u2019 cloud infrastructures.\nYou\u2019ll encounter much the same with other cloud providers, whether it be IBM and Redhat, HPE or Oracle. Platforms like Nutanix and Dell\u2019s VMware are unique in that they support multiple cloud platforms. But first you must pick a horse. Sliding from one to the other can still be challenging.\nIt is hard to blame public cloud providers for not wanting to pave the way out the door for paying customers, though they may have to someday. Because customers do want multi-cloud.\nIndeed, the ability to move left and right between the cloud platforms as well as up and down from the public cloud to privately owned or leased assets is what we all hear when we listen to cloud pitches. Unfortunately, it\u2019s not what the cloud providers are actually saying. At least, not yet.\n\u201cCustomers really want that single pane of glass to manage it all,\u201d Cindy Maike, Vice President of Industry Solutions at Cloudera. \u201cThey want the flexibility to access data and place workloads where they make the most sense, either for cost or capability reasons. Today, customers want to know how quickly they can move.\u201d\nThe answer, of course, is that it depends \u2013 mostly on how well you developed your cloud architecture. If you\u2019ve prepared your data and workloads from the start, you\u2019ll have a much easier time.\nAnd there\u2019s more help on the way.\nOn the business analytics and machine-learning side, for example, companies like Databricks, Looker and Rancher help orchestrate ML projects across diverse deployments. And firms like Panoply, Qubole and Snowflake coordinate data across hybrid cloud and multi-cloud deployments. Cloudera is unique in that it provides both data and ML management with its new Cloudera Data Platform, the result of pooling capabilities with Hortonworks, which it acquired a little over a year ago.\nA key piece of Cloudera\u2019s platform is its governance capabilities, which help operators set and maintain metadata parameters for security, regulatory compliance and data analytics \u2013 even across cloud platforms. Naturally, other independent data management platforms are chasing multi-cloud governance as well. Ultimately, everyone will need to. Because we can\u2019t achieve true multi-cloud data without effortless data and application portability.\nAnd that\u2019s the heart and soul of Cloud 2.0: exactly what we wanted from Cloud 1.0.