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Intelligent Log Monitoring

Make smarter, faster decisions when troubleshooting and measuring the health of your application environments.

Actionable insights for all your critical use cases


Automatically unify logs, traces, and metrics of events in real time

  • Navigate from traces to logs to user sessions and vice versa to get full stack visibility
  • Resolve issues faster with AI-powered root cause analysis
  • Instantly understand business impact and dependencies
  • Reduce MTTR by eliminating manual correlation between multiple tools, alerts, and data silos
Kubernetes Observability

Easily monitor Kubernetes

  • Improve cluster health and ensure performant applications across complex multi-cloud environments
  • Store, analyze, and query cluster-level logs
  • Filter by namespace, workload, node, pod, and container to simplify analysis
  • Diagnose cluster health and troubleshoot application performance with AI-assisted analytics
Log Processing

Optimize storage costs by extracting metrics from logs at ingest or on read

  • Collect and parse log data in real-time without indexing
  • Replace alert storms with AI-powered baselining and anomaly detection
  • Filter, monitor, and transform log fields to meet policy and compliance requirements
Audit and Forensics

Resolve incidents faster

  • Analyze and isolate attack patterns and impact
  • Make any query, at any time, on any data set without reindexing with Dynatrace Query Language (DQL)
  • Retain logs from days to years to meet your audit requirements

Do it all with the power of Grail

Pull actionable insights from your log data quickly, cost-effectively, and at scale with Dynatrace Grail, the industry’s most powerful (and only) causational data lakehouse.
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Developing a log management and analytics strategy

As organizations grow, cloud application environments create complexity that makes managing and analyzing log data difficult.

The traditional approach to log management is often manual and siloed, which limits scalability and ultimately hinders organizational innovation.

Many organizations are stuck in the status quo, which makes them vulnerable to being outpaced by their competition. There is a need to focus less on manual, reactive IT work and more on strategic, proactive innovation and optimization.

This guide explores how a unified approach to log management and analytics eliminates data silos and maximizes ROI from log data.

Read the guide

Bmo customer story
Dynatrace is invaluable in BMO’s journey to become a data-driven organization, harnessing unified observability and powerful AI capabilities to accelerate technology-led innovation and deliver flawless digital experiences.
Rohan Shah Senior Manager for Site Reliability Engineering at BMO

Empower every team to work faster and more effectively

  • Faster Troubleshooting

    Gain real time access to log events data in context of your traces, metrics, and topology to reduce mean time to repair by 90%.​

  • Cost-effective architecture

    With no more schemas to manage or indexes to wait on, teams no longer have to pay a premium for data they’ll never use. ​

  • Actionable analytics

    Query and parse logs to identify, metric, and reduce major outages and degradations by 60%. ​

  • Situational awareness

    Collaborate securely with live data and generate information-rich tables, charts, and dashboards.​

  • Unified observability

    Replace distracting war rooms and alert storms with AI-powered root cause analysis to increase DevOps efficiency by over 40%.​

Interactive tour

Get precise answers from unified log data in context

Start analyzing logs, metrics, and events in the context of traces, topology, and user sessions - with no more schemas or storage tiers to manage.
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