Humio delivers seamless access to live and archived data with Bucket Storage and introduces new features including Joins, Query Quotas, and Vega support
Humio announced the launch of Humio Bucket Storage, enabling cloud scalability for organizations of all sizes. Bucket Storage makes cloud deployments less expensive, faster, and easier to run by using bucket storage for retaining data. The significant decrease in the cost of storage and infinite capacity removes concerns related to storing large volumes of data for a longer period of time. The company also launched several new features in the Humio platform including Joins, Query Quotas, and migration to Vega for our visualization engine. In addition, Humio Cloud is now available hosted by Amazon Web Services (AWS) in the United States providing customers additional options related to geographic data restrictions.
“At Humio, we believe that all data is live data and the amount of data collected should never be limited. Humio now uses our new bucket storage for persistent data, removing the boundaries between live data and archiving data,” said Morten Gram, EVP at Humio. “Our modern, index-free architecture combined with our high compression of data requires no re-ingesting or hydrating for customers to achieve 100% real-time observability on premise or in the cloud. And our scalability goes beyond just log ingestion by enabling users to increase data storage beyond petabytes. With 5-15x compression and the low cost of bucket storage, we are decreasing storage costs for our customers.”
Bucket Storage: Humio supports bucket storage designed for streaming data from major cloud providers, as well as on-premise providers including Min.io. Customers searching retained data — even from years ago — can achieve results in seconds, without re-ingesting. Cloud deployments of Humio are now even cheaper, faster, and easier to run by using Bucket Storage for persistent data. This enables infinite retention, for storing more events than was practical with local disks.
Joins: Join filters make it easy to perform a search or update a dashboard that combines data from different data sets. Match data together from more than one data source, using the new join() filter query to easily search for a combined result set from two queries. Humio provides two join modes: inner joins and left joins.
Quotas: Quotas are used to limit the amount of CPU, memory, and I/O resources any one user or group of users has access to when searching. Usage is tracked continuously as searches are executed. Whenever a user exceeds their quota, the query is stopped and the user is notified.
Vega: The company transitioned the Humio chart engine to Vega visualization specifications, and converted existing charts. We will be opening up for users to define custom visualizations in the future. Humio provides a set of pre-built visualizations, so users don’t have to learn Vega to use Humio.
“We are excited to offer our users increasing scalability through Humio’s Bucket Storage capabilities,” said Garima Kapoor, Co-founder Min.io. “Buckets storage drives efficiency by making deployments significantly less expensive and removes the concerns around storing large volumes of data.”