How a Fast-growing SaaS Scaled Log Analytics While Saving 30% per Month

In the era of product-led growth, log data is king. Yet many organizations only retain a few days or maybe a week’s worth of log data for analytics, max. Why? Because current log management solutions are too complex, brittle, and expensive at scale, forcing organizations to compromise. However, some companies are taking a new approach. Join this session to glean insights from one fast-growing SaaS firm’s journey first-hand. You'll learn: >> Why it’s important to collect, store and analyze long-term log data >> How to activate their existing cloud object storage environment(s) into a data lake for analytics at scale >> Lessons learned from others facing similar log data challenges Jimmy McDermott, CTO and Co-founder of Transeo, will talk through their reasons for modernizing their log management stack, how their current environment works, and provide examples of the business value they’re recognizing while saving 30% in monthly costs vs. the Elasticsearch stack. ChaosSearch’s Thomas Hazel will weigh in and explain how the ChaosSearch Data Lake Platform indexes customers’ cloud data, rendering it fully searchable and enabling analytics at scale with massive reductions of time, cost and complexity.