Key Highlights
Motadata ObserveOps converts raw logs into structured, searchable data on the fly, pairing pre-built parsers with dynamic UI rules and policy-based indexing, no code changes or pipeline restarts required.
Define and refine parsing rules through the interface, not through code.
Visual parsing rule builder that extracts fields from raw log lines, no scripting needed.
Instant preview of parsed output before rules apply to the live pipeline.
Application of updated parsing rules to incoming logs, eliminating pipeline restarts or interruptions.
Regex-based field extraction in the parser creation interface for non-standard formats (confirmed 8.0.7).
Start structured immediately for most common log sources.
Pre-built parsers for web servers, databases, operating systems, firewalls, and network devices.
Coverage for popular applications including Apache, Nginx, MySQL, PostgreSQL, IIS, and Windows Event.
Cloud platform log parsers for AWS CloudTrail, Azure Monitor, and GCP Logging formats.
Parser library updated continuously as new sources and formats are added.
Handle complex log formats that span multiple lines, preserving data integrity and alignment.
Java stack trace parsing with full exception chain reconstruction.
Multi-line application error parsing for Python, .NET, and custom logging frameworks.
Configurable line continuation rules to handle varied multi-line log delimiters.
Multi-line event assembly completed before indexing to ensure query accuracy.
Extend parsing coverage to proprietary and legacy log formats.
Plugin framework for developing parsers for non-standard or proprietary log formats.
Import and export of parser configurations for sharing between environments.
Integration with existing parsing logic from regular expression rules.
Custom field extraction and normalization for internally developed applications.
Control what is indexed, how long it is retained, and where it is stored.
Indexing policies configurable by log source, application, environment, or compliance requirement.
Selective indexing to reduce storage costs for high-volume, low-value log streams.
Compliance-driven retention schedules ensuring audit logs are retained for required periods.
Enrich indexed log data with contextual metadata at ingestion.
Automatic enrichment with host metadata, environment tags, and infrastructure context.
Schema normalization mapping source-specific field names to consistent shared definitions.
Geo-IP enrichment for IP address fields to enable geographic analysis.
Custom enrichment rules adding business context to log records: application name, service tier, cost center.
Intelligence
Unstructured log data degrades query performance, breaks pattern detection, and reduces analysis to manual text scanning. Absent a capable parsing layer, storage fills with data that cannot answer operational questions at speed, turning log data into a compliance burden instead of an intelligence asset.
Dynamic Parsing & Intelligent Indexing removes setup time with pre-built parsers for standard sources and eliminates developer dependency with dynamic UI rules for custom formats. Policy-based indexing stores and retains the structured data according to what each source requires.
How It Works
Receive raw log events from Universal Log Collection's ingestion pipeline.
Apply source-matched pre-built parsers or user-defined dynamic parsing rules.
Handle multi-line events with assembly logic before field extraction.
Enrich parsed fields with host metadata, environment context, and custom tags.
Apply indexing policies to determine retention and field visibility.
Deliver structured, enriched, indexed log records to the analytics and query layer.
Each log line arrives at analysis ready: structured, enriched, and correctly retained.
Role-Based Value
Each log line arrives at analysis ready: structured, enriched, and correctly retained.
Each log line arrives at analysis ready: structured, enriched, and correctly retained.
Control log storage costs through policy-based indexing that retains what is needed and archives or discards what is not.
Control log storage costs through policy-based indexing that retains what is needed and archives or discards what is not.
Query log data by any field, source, and time range regardless of the original line's internal format.
Query log data by any field, source, and time range regardless of the original line's internal format.
Adapt parsing rules for application logs, no code changes or re-ingestion delays needed.
Adapt parsing rules for application logs, no code changes or re-ingestion delays needed.
From Visibility to Control
Immediate structured query access for all onboarded log sources through pre-built parsers.
Parsing rule changes applied with no pipeline restarts or re-ingestion delay.
Reduced storage costs through policy-based indexing aligned to retention requirements.
Complete multi-line log event capture with no data loss or misaligned event boundaries.
Consistent field naming for heterogeneous sources through schema normalization.
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