{"slug": "lucidity-adds-support-for-object-storage-to-cloud-optimization-platform", "title": "Lucidity Adds Support for Object Storage to Cloud Optimization Platform", "summary": "Lucidity has expanded its cloud storage optimization platform to support object storage alongside block storage, starting with Microsoft Azure, as AI workloads drive storage costs to 20-30% of the average cloud bill. The platform analyzes storage inventories and access patterns to recommend retention and tiering policies, with plans to add file storage support soon.", "body_md": "TL;DR — Key Takeaways\n\n- Lucidity has expanded its cloud storage optimization platform to support object storage alongside block storage, starting with Microsoft Azure.\n- The platform analyzes storage inventories and access patterns to recommend retention and tiering policies that can reduce wasted capacity and costs.\n- Lucidity says storage now accounts for 20% to 30% of the average cloud bill, making optimization more important as AI workloads generate more data.\n\nLucidity today extended the reach of its cloud storage optimization platform to now include support for both object and block storage at a time when costs are starting to spiral beyond the control of many IT teams.\n\nNitin Bhadauria, cofounder at Lucidity, said [adding support for object storage optimization to the Lucidity Platform](https://www.prnewswire.com/news-releases/lucidity-extends-into-object-storage-bringing-new-visibility-and-savings-to-enterprises-302853339.html) has become critical at a time when artificial intelligence (AI) applications are exponentially increasing the amount of data stored in this format.\n\nAvailable today for Microsoft Azure cloud, Lucidity plans to extend the reach of its support for object storage to other cloud services, said Bhadauria. Additionally, the company also plans to soon add support for file storage, he added.\n\nAs the overall cost of storage continues to climb, IT teams need to focus more time and effort on reducing the amount of storage space that is often wasted because data isn’t being efficiently managed, noted Bhadauria.\n\nThe Lucidity Platform synthesizes weekly inventory reports to create a heat map that surfaces where costs are highest. It then analyzes access patterns at the prefix level to generate recommendations for retention and tiering policies. Additionally, IT teams can simulate a policy change to preview its impact on cost and security posture, then apply it at scale with a single click.\n\nIn general, wastage of cloud storage resources is often difficult to detect because while organizations typically create thousands of containers and folders and millions of blobs, all of that usage of cloud resources is consolidated into a single line item on the cloud bill. In the absence of any meaningful analytics, IT teams have little to no visibility into how storage resources are consumed.\n\nThe challenge many organizations have is that unlike in an on-premises IT environment there is often no one that has been specifically charged with managing cloud storage. In most cases, storage is managed by a larger cloud operations team that is trying to manage everything from the number of virtual machines that might be running to securing each workload deployed. As such, it’s easy to overlook the cost of storage when the aggregate bill for cloud computing services is passed straight through to finance.\n\nCloud service providers, meanwhile, have little incentive to highlight where IT infrastructure resources are being wasted to help IT organizations reduce their total costs. In total, 20 to 30% of the average cloud bill is now made up of storage costs, said Bhadauria. As the amount of data being stored continues to increase, so too does the overall amount of sprawl, he added.\n\nEach organization will need to determine for itself to what degree it may be worth adding cloud storage specialists to their IT teams, but in the AI era it’s not a question of whether storage costs will increase but rather by how much. The challenge and the opportunity now is to determine how best to optimize cloud storage to enable budget dollars to be reallocated to building and deploying more applications. Otherwise, IT teams will soon discover that the amount of data being generated is, paradoxically, also limiting the number of AI applications they can actually afford to deploy.", "url": "https://wpnews.pro/news/lucidity-adds-support-for-object-storage-to-cloud-optimization-platform", "canonical_source": "https://techstrong.it/featured/lucidity-adds-support-for-object-storage-to-cloud-optimization-platform/", "published_at": "2026-08-18 13:54:17+00:00", "updated_at": "2026-08-18 14:14:01.303792+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-infrastructure", "ai-tools"], "entities": ["Lucidity", "Nitin Bhadauria", "Microsoft Azure"], "alternates": {"html": "https://wpnews.pro/news/lucidity-adds-support-for-object-storage-to-cloud-optimization-platform", "markdown": "https://wpnews.pro/news/lucidity-adds-support-for-object-storage-to-cloud-optimization-platform.md", "text": "https://wpnews.pro/news/lucidity-adds-support-for-object-storage-to-cloud-optimization-platform.txt", "jsonld": "https://wpnews.pro/news/lucidity-adds-support-for-object-storage-to-cloud-optimization-platform.jsonld"}}