Beating the odds: How log data helps detect and lower MTTR

Beating the odds: How log data helps detect and lower MTTR

Why does Reducing MTTR Matter?

Depending on your business, MTTR stands for mean time to repair or mean time to recovery – but it can also mean resolution, resolve, or restore. No matter how you define it, the basic measurement is the same: it’s the time it takes from when something goes down to when it is back and fully functional. This includes everything from finding the problem to fixing it. For ITOps teams, keeping MTTR to an absolute minimum is crucial. And the biggest obstacle to lowering MTTR is correlating information from disparate sources.  You can’t fix what you don’t understand.

The right monitoring solution brings information from your entire stack into a single, centralized view to ensure time is spent on resolving problems, not swiveling between tools and solutions looking to find where the problem lies. Ops teams can’t reduce MTTR without understanding connectivity across IT environments and removing guesswork at every step. It’s difficult in modern, complex IT environments to know precisely why a failure occurred to quickly identify, fix, and leverage learnings to maximize service availability.

A modern infrastructure stack contains a large number of resources, servers, and services all generating a large amount of data. When a problem occurs, it’s reported from multiple sources at different severity levels, and often missing some crucial data for identification, troubleshooting, and resolution. As an ITOps team striving for high performance and efficient response times, you must find ways to seamlessly correlate such diverse data across the complex network and cloud environment they manage.

Is your monitoring today enough to hit your MTTR goals?

ITIM Monitoring helps assess the impact and severity of a problem. Still, this alone is no longer enough to quickly resolve issues. Monitoring alone does not provide enough information to move quickly from diagnosing to resolving incidents across complex hybrid IT environments. Ops teams aren’t equipped with the right solution to analyze the noise and connect the data across IT to know where to investigate and troubleshoot. Instead they are forced to switch between tools and sift through siloed data streams trying to find connections. 

IT metrics and alerts can also help resolve issues but only acknowledge that a problem is happening, not necessarily where and how. Alerts are often based on manual static thresholds to determine the severity and don’t provide enough connection to the primary issue. With just IT metrics and signals alone, Ops teams rely on inefficient, manual processes to fill in the gaps in IT health, wasting time blindly troubleshooting to resolve issues.

Here is an example of a failure that could impact your Ops teams today. What happens when one of your most important Database servers stops consuming messages from Kafka and service is interrupted across your customer base? Metrics and alerts show that something has gone wrong  but your Ops teams can’t quantify how many customers are affected or the root cause. The team can’t spend hours manually troubleshooting the situation by looking at the servers because your customers are affected and you can’t guess since the impact is unknown. There is a solution – but it requires filling in the gap to IT monitoring with a context-rich data source: logs. 

Traditional IT monitoring alone leads to long, costly, high MTTR for Ops teams and your overall business.

Reducing MTTR with actionable, contextual data

Context is key to reducing MTTR. IT monitoring provides information around the health of your environment, but logging IT data for devices generates and records specific events that occur in your environment. Logging helps explain what was happening at the time the log was created. Teams need the right information at the right time, in the right context, to troubleshoot IT issues faster and reduce overall MTTR. IT monitoring without log data for devices and cloud services isn’t enough to connect data across complex hybrid IT environments to pinpoint root causes for troubleshooting.

Integrating as much context-rich information about your modern IT environment will strengthen the impact of your metrics and alerts to provide intelligence for Ops.  

Modern monitoring solutions support integrations with visibility into hybrid and multi-cloud solutions from applications or IT infrastructure devices. 

  • Syslogs are one of the most common log data sources in enterprise environments 
  • Windows Event logs help fill immediate gaps in valuable data for systems built around Windows servers and VMs 
  • Collecting logs from either AWS, Azure, or GCP provides insight into specific events happening across your cloud services that may impact your infrastructure health
  • Kubernetes logs provide details around the health of your container monitoring
  • Application logs, and all other types of custom logs, fill in the gap of data possible to record for a better understanding of what is happening alongside IT metrics

Contextual log data helps Ops teams follow alerting to increase detection of the issue across devices, cloud services, and applications, whether on-premises or in the cloud, for faster problem resolution,  and ensure there are no dead-end investigations. 

Radically reducing MTTR requires a modern monitoring solution that centralizes log data for Ops teams from both on-prem and cloud, correlates metrics and logs, and creates new practices to understand root causes of problems. Surfacing this log data alongside existing monitored resources makes it possible to know what is wrong with your system with key IT health metrics that show you why the problem is happening. 

Log data helps detect and reduce MTTR across modern IT environments 

A system with unified logs and metrics gives Ops teams full visibility into their entire infrastructure ecosystem with context and correlation to analyze log data to achieve insight and resolution. Log and IT infrastructure data in one solution removes context switching and helps Ops teams meet and accelerate their business objectives to focus on innovation.

For example IT performance metrics dashboards allow Ops users to analyze spikes in key health indicators like memory and CPU usage dropping, page load time, and disk utilization increasing, and hop over to log data for the specific devices to read error messaging and identify the root cause faster. Empower your Ops teams with insights and context alongside infrastructure metrics for rapid troubleshooting.

The result? Ops teams become a stronger first line of defense with log data available at their fingertips when issues occur to decrease MTTR by comparing log data alongside IT metrics. Ops teams can see which logs are important to identify further and continue the investigation.  

In short, access to log data helps detect and solve issues faster by providing guidance on precisely where the problem is occurring with detailed, timestamped information for each device.

Fixing problems once and for all requires log data

IT faces a landscape of increasingly challenging business continuity, MTTR, and performance requirements. Organizations must deal with the complexity of their modern IT environment, the large number of devices and applications, with cross-site operations and disaster recovery requirements. Ops teams need centralized access to the log data information relevant to their specific functions. Unified logs and metrics give Ops teams full visibility into their entire infrastructure ecosystem with context and correlation to analyze log data to achieve insight and reduce MTTR. There are many tools and solutions out there to take control of complex environments, but traditional IT monitoring is no longer enough. As you plan for the future, it’s crucial to remove existing blindspots and streamline workflows within a single monitoring solution to enable IT teams to work efficiently, without swivel chair switching between monitoring and logging solutions.  

To truly unlock the power of IT Ops and significantly reduce MTTR, however you define it, the solution is a long-term investment in log data infrastructure that can both collect and respond to the diverse, complex log data generated by increasingly complex IT environments. So, what are you waiting for?