Gartner published the 2025 edition of its Market Guide for Log Analytics earlier this year, and we are honored to be recognized as the only non-US-based solution featured in the report (cf. list below).
This report confirms what our customers experience every day: leveraging log and system data is vital to understand system behavior, detect issues early, and accelerate root cause analysis and troubleshooting. At Logmind, we help enterprises turn those billions of raw logs and unstructured data into meaningful insights, all automatically and without any effort.
Gartner’s conclusions closely align with our mission to future-proof IT operations with more intelligent automation, in that way reducing operational complexity, cost and boosting system resilience. As organizations struggle with increasingly complex IT environments, growing data noise and alert fatigue, rising costs and fragmented tools, Logmind help them focus on what matters.
The findings of the report highlight how log analytics is becoming a priority requirement for organizations:
- Log analysis is vital for companies to understand system behavior, performance, and enable efficient troubleshooting and root cause analysis.
- Main challenges that companies face today are (i) rapid log growth increasing noise and complexity, (ii) difficult to deliver the right log data to the right team (DevOps, I&O, Security, etc.) at the right time.
- Companies need to centralize and actively manage their logs from all data sources to get unified visibility and enhanced insights.
Gartner also recommends IT leaders to strengthen their log analytics capabilities in six steps:
- Identify data sources across infrastructure, network, applications, cloud, SaaS, and automation domains.
- Define telemetry architecture for how logs flow from workloads to analysis tools.
- Centralize log management by selecting platforms that support multiple use cases and correlate logs in their context.
- Establish governance policies to control log content, storage location, and retention throughout the telemetry life cycle.
- Enable AI-driven analysis to automate source identification, anomaly detection, and root cause analysis.
- Implement a log data life cycle with tiered storage to reduce infrastructure costs.
Logmind help enterprises accelerate this journey, with an end-to-end platform to centrally collect, automatically parse and analyze raw logs and event data from all sources. Our powerful Machine Learning engine will analyse this data and understand the dynamic baseline of your systems and services to automatically detect and troubleshoot early signal of IT issues. No pre-cleaning of the logs needed, no rule-based alerting, no complex configuration, all automated and real-time.
We are grateful for the recognition by Gartner and excited to continue helping organizations move from reactive troubleshooting to proactive IT operations.
