ChaosSearch Enhances Log Analytics Capabilities to Deliver Exploratory and Investigative Analytics at Scale

New features eliminate architectural complexity challenges associated with existing cloud data platforms to deliver operational intelligence for cloud services monitoring, threat hunting, troubleshooting, and more

ChaosSearch announced enhancements to its award-winning log analytics capabilities that make it easier for organizations to conduct exploratory and investigative analytics at scale. Built within the ChaosSearch Data Lake Platform and now available to all customers, the augmented capabilities eliminate the architectural complexity and challenges created by traditional data platforms and dramatically improve time to insights, data reliability, and cost.

The amount and variety of data being generated by businesses has grown exponentially in the last few years. While this should create unbounded opportunities for companies, the data lakes, warehouses, and lakehouses they currently rely on are not built for scale. With these platforms’ outdated infrastructures, organizations are only able to access and analyze a limited amount of data—making explorative and investigative analytics extremely challenging, expensive, and laborious to complete. In fact, the 2022 Data Delivery and Consumption Patterns Survey found that data quality and timeliness are the most pressing issues cited by respondents, with 65% reporting that these issues have increased over the past three years.

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To solve these challenges, ChaosSearch is delivering augmented log analytics capabilities that will eliminate the tradeoffs between data retention, performance, reliability, flexibility, and cost that organizations are forced to make today. Platform feature enhancements include:

• Incremental Load for Kibana Discover – Accelerates time to insight by improving data representation and speeding up the time it takes for users to display query results from the ChaosSearch platform in Kibana Discover views.
• Exact and Wildcard Match – Optimizes search/queries for maximum performance by allowing for the selection of segments a search/query needs to resolve a request during the scope of a query plan. By delivering 2x-5x average improvement, users can find answers faster.
• Aggregation Requests – Simplifies anomaly detection by showing a percentile representation of the value below which a certain percentage of observations occur for the specified field, making anomaly detection both easier and faster.
• Privacy Field Masking – Delivers enhanced flexibility for customers, allowing them to hide sensitive contents of Object Groups columns on-demand, and ensuring data privacy and compliance needs are met.

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“ChaosSearch has transformed how we think about log analytics by providing a single platform that internalizes logs while externalizing the work,” said Adam Dutko, Vice President of Cloud Engineering at Sixth Street. “After deploying ChaosSearch, we’re now logging everything. It’s not only delivering significant cost and time savings, but we now have better access to more data than ever before.”

“If you’re using any of the existing database platforms today, there is simply no way you’re looking at more than one day’s worth of data at a time without an astronomical price tag,” said Thomas Hazel, Founder, CTO, Chief Scientist, ChaosSearch. “We know how important investigative insights are to businesses—especially when handling time-sensitive issues like threats and system outages. Our platform makes it possible to execute on those types of searches across billions of data points in a matter of seconds. Getting deeper, wider log data storage, access, and analysis is becoming the difference maker for businesses, and our customers will be leading the charge.”

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