The volume of data being generated today brings both opportunity and massive operational complexity. Most teams that operate at scale don't discover issues until they appear on an invoice — and by the time an unusual access pattern shows up as a line item, it has often been running for weeks. Understanding what happened means exporting inventory, joining it against access logs, and hoping someone still remembers which service account belongs to which job.
That workflow was manageable in the past, but today’s AI training and inference pipelines create data faster than governance systems can classify it, and read data in patterns that shift from week to week. Today we're announcing two new features for Google Cloud Storage: the general availability of Storage Intelligence advisor along with expanded capabilities in storage batch operations . Advisor tells you what changed in your storage estate and what to do about it. Batch operations can carry that decision out across millions of objects. These features are available now to all Storage Intelligence customers.
For the last decade, answering "what’s in my buckets? " has been a data engineering project. Export your inventory, load it somewhere queryable, join it against usage, build dashboards, and then maintain them. Storage Intelligence delivers visibility without the engineering overhead. Teams are voting with their workloads: the number of customers using Storage Intelligence to analyze datasets of over 1 billion objects has more than doubled this year. There are two ways to run a large storage estate.
Teams can leverage daily activity data and metadata snapshots to build exactly the pipelines they need –Storage Intelligence still gives you that option – but most teams would prefer not to build pipelines if they don’t have to. They want to be told what changed in their storage environment and what to do about it. Storage Intelligence advisor is for them. Storage Intelligence advisor brings visibility into your storage without having to perform any setup. Advisor starts from a curated set of findings. There's no schema to design, no pipeline to manage, and no dashboard to assemble.