Log analysis

Log intelligence at scale for hybrid and multi-cloud environments – instant access to contextualized and correlated logs and metrics in a single, unified cloud-based platform. With tiered retention options, including unlimited retention, and hot storage to optimize data hygiene and internal compliance initiatives.

Centralized log and metric data in one platform

Eliminate context switching between IT Infrastructure monitoring and Log management products, by correlating relevant logs with metrics in a single platform – with over 2,000 integrations, modules and pre-built templates for on-prem (like networking, servers, databases, Windows, Linux) and cloud (like AWS, Azure, GCP).

Harness the power of machine learning for all of your log data

Decrease troubleshooting

Get up to 80% faster troubleshooting and RCA with all of your logs and metrics in a unified cloud-based platform – with unlimited retention option for your log data for instant access, any time, every time.

Streamline IT workflows

Free up to 40% of non-value adding engineering time with log anomalies that automatically surface with machine learning – industry-leading ease of use for faster onboarding of your tech and resources.

Increase control & reduce risk

Become more proactive through automated correlation with metric-based alerts with full visibility into your technology ecosystem, enabling you to modernize your technology stack.

Unified logs and metrics

A single platform to give technical teams the access and information they need to investigate issues across their technology ecosystem with ease and speed:

  • Querying capabilities for all experience levels
  • Proactive management of log data through alert-based rules for critical infrastructure
  • Instant access to log data with tiered retention options; unlimited, 1 year, 30 days with hot storage and access to raw data
  • Unified collector for log and metric ingestion – with over 2,000 pre-built templates and modules
  • Eliminate context switching between tools and consoles
  • Metrics, logs and log anomalies are all associated with their corresponding devices, cloud instances, and containers

AIOps powered anomaly detection

Leverage powerful automation to surface anomalies and uncover trends to define with is “normal” for your organization:

  • Unseen behavior is brought to your attention with context – so you can find the root cause, faster
  • Eliminate the need for excessive searches and parsing to get the information you need
  • Find the needle, without the haystack – for dramatic reduction in MTTR and the only logs solution to offer unlimited log retention
  • Access to raw data for full visibility into your environment
  • Log analysis at time of ingest vs. relying on historic log metrics
  • Full IT operations lifecycle support through integrations like ServiceNow, CMDB, and automation tools like Ansible

Unified observability experience

Built with ITOps and DevOps teams in mind to aggregate log data, layered with patented algorithms to enhance ease of use:

  • The only platform to automatically correlate and contextualize log data without manual inspection
  • Focus only on those performance or availability impacting logs events immediately – without having to decipher what is “normal” or “abnormal”
  • Optimize ITOps and DevOps collaborations in increasingly complex hybrid and multi-cloud environments
  • Enable the rights teams to have access to the information and metrics that they need the most, without sacrificing productivity
  • Streamline incident management workflows to improve operational efficiency
  • 20-50% less expensive than other solutions, enabling teams to free up budget for other initiatives

Enterprise-scale Saas platform for log intelligence and aggregation

Successfully monitor complex, multi-cloud, and hybrid enterprise infrastructures at a global scale

Comprehensive and extensible log collection

LM Logs out of the box integrations make it easy to send logs to LogicMonitor.

Send it & forget it – logs are automatically matched to monitored resources & anomalies are automatically detected and contextually displayed.

A robust API enables users to customize log collection & send any logs to LogicMonitor, regardless of whether an integration is available

Customizable search & filtering

Supports keyword search, so users can quickly search for log events containing specific keywords, or perform complex queries to get more targeted results

Users can easily filter logs (raw logs & anomalies) based on the resource or resource group they relate to

Users can quickly filter displayed logs based on time range, either by configuring a specific time range or zooming in on specific ranges within the overview graph

Correlated log alerting

Log alerts are alert conditions based on log events and log pipelines. These alert conditions use regular expression patterns to match ingested logs and trigger LogicMonitor alerts to send you notifications when these log events or anomalies occur

With log alerts, you can speed up your investigation by adding alert conditions to track the logs you always want to know about or creating alerts on a detected anomaly

Intelligent log analytics

LM Logs correlates logs with metrics and alerts to troubleshoot critical problems deep inside the applications, infrastructure, and network. The log analytics capability includes:

  • Presenting logs contextually with devices, resources, and groups
  • Presenting logs contextually with alerts

Tiered retention & hot storage

For customers running critical production and compliance-sensitive environments, LM Logs provides tiered log retention capabilities

LM Logs provides several data retention options (30 days, 1 year, unlimited) to meet any of your data retention needs for internal compliance, risk mitigation and data hygiene

All LM Logs data is available whenever you need it (hot storage) with no need to store the data somewhere else or wait for log re-ingestion

Related Solutions

Accelerate your path to unified observability

Full visibility into your hybrid infrastructure

LogicMonitor’s cloud-based collectors automatically detect, monitor, and alert on your entire IT infrastructure. With automated discovery of all resources, you’ll have full-stack visibility across all cloud, hybrid and on-premises environments in just minutes.

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Proactively manage your technology ecosystem with AIOps

The LogicMonitor Early Warning System layers AIOps capabilities (including anomaly detection, root cause analysis, and dynamic thresholds) across your infrastructure environment to trigger actions, such as integrations and custom scripts, enabling you to prevent issue occurrence.

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Rapidly deploy dynamic microservices monitoring

Get visibility into your microservices and containerized applications, like Kubernetes, alongside the rest of your hybrid IT infrastructure in a single monitoring platform.

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LM Logs FAQ

What is log monitoring?

Log monitoring is the process of collecting and centralizing logs and event information from any of your technologies from on-prem to cloud, infrastructure to applications, to gain insight into what’s going on in your environment. Log data is aggregated over time and retained and accessible for a defined period time.

How do you monitor logs?

Sending your logs from a variety of sources and technologies via log collectors/aggregators for centralized log collection. Popular log collectors include FluentD and Logstash. Applications can be configured to send logs directly from the code.

Which logs should be monitored?

Some of the more common log types to monitor include event logs, access and audit logs, and transactional logs. Event logs contain important information about what’s happening in a system and help determine an underlying issue. Access and audit logs keep track of who’s accessing a system and keeping track of their activity. Transactional logs show how systems are interacting with each other, like a web server connecting to a database server.

What is the difference between logging and monitoring?

Logging generates and records events that occur in your technical environment and keeps them for review. Logging helps explain what is happening at the time the log is created. Monitoring provides information around the data you’ve identified. You can monitor infrastructure performance metrics or you can monitor the number of logs generated by a given device.

What is tracing monitoring?

Tracing represents the entire application flow and the journey a user takes when accessing the application. Collecting traces from applications will provide better insight into the health performance of the application and how to optimize.

How are logs maintained and monitored?

Each device, system, or application generate their own logs and are kept locally. User can centralize their logs in a unified space by using a log collector or aggregator, often times to a local logging server or a SaaS-based solution. Once the logs are centralized, users can search through the logs to find the information they need and many solutions provide log alerting capabilities to notify when certain log conditions have been identified.

What is log analysis?

Log analysis helps make sense of your log data. Systems can generate thousands a logs per day and finding the log that you need can be challenging. When log data is analyzed, log data can provide more insight and context to what’s happening. Log analysis could include analyzing every log for the log severity written in the log and being able to search for the severity that is the target of your investigation.

Why is logging so important?

Logging provides information about events and transactions taking place in your technical environment. Without logging all events, you may have a difficult time identifying issues or determining the root cause of a problem.

Log analysis vs APM

Log analysis focuses on collecting and aggregating logs from a variety of sources, making it easier to search across all of your systems. APM focuses on application performance and is used to identify user experience and ways to optimize the application.

What is log file monitoring?

System events and transactions can be written to local log files for review. The log files can be sent to your logging tool using a log shipper like FluentD or Logstash. Every time new logs are written to the local log file, the new logs will be sent to the logging tool with no concerns about duplicating previous logs.

It’s almost like magic. Let’s chat.