What’s the right way to manage growing volumes of enterprise data, while providing the consistency, data quality and governance required for analytics at scale? Is centralizing data management in a data lake the right approach? Or is a distributed data mesh architecture right for your organization? When it comes down to it, most organizations seeking these solutions are looking for a way to analyze data without having to move or transform it via complex extract, transform and load (ETL) pipelines.

The ephemeral nature of the cloud has made compliance and security a greater challenge for organizations. The volume of data that companies must collect and retain from their cloud services, depending on their industry, is ballooning fast. According to ESG, 71% of companies believe their observability data (logs, metrics and traces) is growing at a concerning rate. Even so, outcomes are getting worse, not better. Six out of 10 teams are unable to prevent issues before customers are impacted.

Operational IT data, such as log data and other application telemetry, can play an important role in understanding your users. Leveraging user data to continuously optimize and improve products is a core tenet of product-led growth (PLG). Let’s learn more about PLG, and how IT telemetry data can be used to power strategic growth.

As enteprise networks grow larger and more complex, IT teams are increasingly dependent on the enhanced network visibility and monitoring capabilities provided by log analytics solutions. Log analytics gives enterprise Engineering, DevOps, and SecOps teams the ability to efficiently troubleshoot cloud services and infrastructure, monitor the security posture of enterprise IT assets, and measure application performance throughout the application lifecycle or DevOps release pipeline.