LogFlow by LOGIQ AI Manages Machine data for Organizations Successfully
LogFlow from LOGIQ.AI is SOC2-compliant, prioritizing data security and integrity. LogFlow's InstaStore and built-in insurance mitigate data hazards connected with machine data pipelines.
Fremont, CA: Data pipelines allow data to move from an application to a data warehouse, from a data lake to an analytics database, or from a payment processing system to a payment processing system. LogFlow, an Observability Data Pipeline as a Service, has been developed by LOGIQAI, a leading provider of data management, analytics, and observability solutions for IT, DevOps, and SecOps organizations (DPaaS). LogFlow is a new machine data management paradigm that allows businesses to unlock the full power of machine data by linking it to SMEs on demand.
According to IDC, global data production and replication is expanding at a CAGR of 23percent, and 70 percent of companies will alter their attention to give more context for data analytics (Gartner). To optimize data volume and increase data quality, new tooling is required. At both the core and the edge, LogFlow handles these data challenges.
Greg O'Reilly, Observability Consultant at Visibility Platforms, states, "LogFlow enables our customers to take a whole new approach to observability data; one that helps regain control and unblock vendor or cost limitation. We're opening up discussions between ITOps and Security teams for the first time with a unified solution that keeps data secure, compliant, manageable, and readily available to those who need it on the front lines."
Over 2000 rules filter, tag, extract and rewrite data for typical client environments, and workloads are included in LogFlow's built-in "Rule Packs." Security event detection and labeling are also possible with LogFlow's SIEM Rule Packs. LogFlow from LOGIQ.AI gives teams absolute control over observability data pipelines and delivers high-value, high-quality data in real-time, all the time. Organizations can now have complete control over data collection, consolidation, retention, manipulation, and upstream data flow management for the first time.