Fast search, scalable ingestion, zero noise
Ingest logs from any source, query them naturally, and get real-time insights no data overload.
The Pain Points Every Team Faces
Traditional log management tools create more problems than they solve. High costs, slow searches, and overwhelming noise make debugging a nightmare.
Paying per GB ingested means every log line costs money. Traffic spikes, verbose logging, and debug noise drive costs through the roof.
Logs scattered across containers, servers, cloud providers, and services. No unified view means hours spent jumping between tools.
Debug logs, health checks, and routine messages drown out actual errors. Finding the signal in the noise becomes impossible.
Complex query syntax, slow full-text searches, and limited filtering make finding relevant logs a time-consuming process.
Unified, Smart, Cost-Effective
Logify360 Logs unifies ingestion, eliminates noise, enables fast search, and integrates with metrics and traces for complete observability.
Unified ingestion from any source
Intelligent noise filtering
Fast, natural language queries
Cross-signal correlation
Cost guardrails & smart retention
Loading Smart Search demo...
Capabilities that scale with you
Collect logs from any source - containers, servers, cloud providers, agents, applications. Supports OpenTelemetry (OTLP), file logs, Docker stdout/stderr, syslog, Fluentd forward protocol, TCP logs, and native integrations.
One platform for all your logs, no matter where they originate.
Example:
Ingest from Kubernetes pods via OTLP, Docker container logs, Nginx access logs, system syslog, and Fluentd forwarders all in one unified view.
Smart retention policies with configurable TTL, automatic archiving, and restore capabilities. Manage retention by table, set custom retention days, and optimize storage costs.
Reduce log storage costs by 20/40% while preserving critical debugging data with flexible retention policies.
Example:
Set 30-day retention for production logs, 7-day for dev, and automatically archive older data with restore on demand.
Lightning-fast search across billions of log lines with Smart Search (NLQ). Support for free-text queries, structured filters, field-based searches, and natural language queries that translate to optimized ClickHouse queries.
Find relevant logs in seconds, not minutes - even across massive datasets. Query in plain English or use advanced syntax.
Example:
Search 'errors after 10:05 deploy in checkout-api' and Smart Search translates to optimized filters showing instant results with top stack traces.
Automatic pattern detection identifies common log patterns, clusters similar logs, and creates fingerprints for grouping. Detect patterns, view frequency, confidence scores, and create alerts based on pattern occurrences.
Discover recurring issues automatically. Group similar logs together and identify noisy sources for optimization.
Example:
System detects 50+ variations of 'connection timeout' errors, groups them into a pattern with 95% confidence, and suggests creating an alert when frequency exceeds threshold.
Stream logs in real-time with live tail functionality. Filter by service, severity, and watch logs as they arrive. Auto-scroll, pause, and clear capabilities for efficient monitoring.
Monitor production issues in real-time. See errors and warnings as they happen without refreshing.
Example:
Start live tail for 'payment-service' with ERROR severity filter to watch for payment failures in real-time during a deployment.
Multiple visualization views: table view, time series charts, pie charts, top lists, patterns view, fingerprints view, and explorer. Analytics dashboard with volume trends, service distribution, and severity breakdowns.
Understand log data from multiple perspectives. Visualize trends, distributions, and patterns at a glance.
Example:
View error rate trends over time, see top 10 services by log volume, analyze severity distribution, and explore log patterns interactively.
Export logs in multiple formats: CSV, JSON, Excel, and NDJSON. Select specific fields, apply filters, and download large datasets. Export API supports time range filtering and field selection.
Take your log data anywhere. Export for analysis, compliance, or integration with other tools.
Example:
Export last 24 hours of error logs as CSV with selected fields (timestamp, service, severity, message) for external analysis or reporting.
Logs connect directly to traces and metrics. Jump from a log error to related traces showing the full request path, view correlated metrics, and understand the complete context of an issue.
Complete observability picture. Understand the full impact of log events across your stack without context switching.
Example:
Click a log error → see related traces showing the request path → view metrics showing latency spike → identify root cause in seconds.
Real results from real teams
Built for scale, security, and reliability
Discover how Logify360 helps you monitor and optimize your entire stack
See how Logify360 Logs helps you reduce costs, find issues faster, and get complete observability across your stack.
Fast search, scalable ingestion, zero noise
Ingest logs from any source, query them naturally, and get real-time insights no data overload.
The Pain Points Every Team Faces
Traditional log management tools create more problems than they solve. High costs, slow searches, and overwhelming noise make debugging a nightmare.
Paying per GB ingested means every log line costs money. Traffic spikes, verbose logging, and debug noise drive costs through the roof.
Logs scattered across containers, servers, cloud providers, and services. No unified view means hours spent jumping between tools.
Debug logs, health checks, and routine messages drown out actual errors. Finding the signal in the noise becomes impossible.
Complex query syntax, slow full-text searches, and limited filtering make finding relevant logs a time-consuming process.
Unified, Smart, Cost-Effective
Logify360 Logs unifies ingestion, eliminates noise, enables fast search, and integrates with metrics and traces for complete observability.
Unified ingestion from any source
Intelligent noise filtering
Fast, natural language queries
Cross-signal correlation
Cost guardrails & smart retention
Loading Smart Search demo...
Capabilities that scale with you
Collect logs from any source - containers, servers, cloud providers, agents, applications. Supports OpenTelemetry (OTLP), file logs, Docker stdout/stderr, syslog, Fluentd forward protocol, TCP logs, and native integrations.
One platform for all your logs, no matter where they originate.
Example:
Ingest from Kubernetes pods via OTLP, Docker container logs, Nginx access logs, system syslog, and Fluentd forwarders all in one unified view.
Smart retention policies with configurable TTL, automatic archiving, and restore capabilities. Manage retention by table, set custom retention days, and optimize storage costs.
Reduce log storage costs by 20/40% while preserving critical debugging data with flexible retention policies.
Example:
Set 30-day retention for production logs, 7-day for dev, and automatically archive older data with restore on demand.
Lightning-fast search across billions of log lines with Smart Search (NLQ). Support for free-text queries, structured filters, field-based searches, and natural language queries that translate to optimized ClickHouse queries.
Find relevant logs in seconds, not minutes - even across massive datasets. Query in plain English or use advanced syntax.
Example:
Search 'errors after 10:05 deploy in checkout-api' and Smart Search translates to optimized filters showing instant results with top stack traces.
Automatic pattern detection identifies common log patterns, clusters similar logs, and creates fingerprints for grouping. Detect patterns, view frequency, confidence scores, and create alerts based on pattern occurrences.
Discover recurring issues automatically. Group similar logs together and identify noisy sources for optimization.
Example:
System detects 50+ variations of 'connection timeout' errors, groups them into a pattern with 95% confidence, and suggests creating an alert when frequency exceeds threshold.
Stream logs in real-time with live tail functionality. Filter by service, severity, and watch logs as they arrive. Auto-scroll, pause, and clear capabilities for efficient monitoring.
Monitor production issues in real-time. See errors and warnings as they happen without refreshing.
Example:
Start live tail for 'payment-service' with ERROR severity filter to watch for payment failures in real-time during a deployment.
Multiple visualization views: table view, time series charts, pie charts, top lists, patterns view, fingerprints view, and explorer. Analytics dashboard with volume trends, service distribution, and severity breakdowns.
Understand log data from multiple perspectives. Visualize trends, distributions, and patterns at a glance.
Example:
View error rate trends over time, see top 10 services by log volume, analyze severity distribution, and explore log patterns interactively.
Export logs in multiple formats: CSV, JSON, Excel, and NDJSON. Select specific fields, apply filters, and download large datasets. Export API supports time range filtering and field selection.
Take your log data anywhere. Export for analysis, compliance, or integration with other tools.
Example:
Export last 24 hours of error logs as CSV with selected fields (timestamp, service, severity, message) for external analysis or reporting.
Logs connect directly to traces and metrics. Jump from a log error to related traces showing the full request path, view correlated metrics, and understand the complete context of an issue.
Complete observability picture. Understand the full impact of log events across your stack without context switching.
Example:
Click a log error → see related traces showing the request path → view metrics showing latency spike → identify root cause in seconds.
Real results from real teams
Built for scale, security, and reliability
Discover how Logify360 helps you monitor and optimize your entire stack
See how Logify360 Logs helps you reduce costs, find issues faster, and get complete observability across your stack.
Waiting for query...
Waiting for query...