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Chapter
7

Reduce MTTR: Guide & Best Practices

November 12, 2023
8
 min read

The pursuit of near-perfect service reliability is challenging, even for high-performing teams. Incidents are inevitable, and maintaining high levels of reliability depends on swift and effective triage and remediation. It's here that MTTR – which is short for mean time to restore or mean time to resolve – can help enterprises measure the time taken to resolve an incident or restore service after it has been reported.

A mature incident response strategy is a foundational blueprint that helps teams reduce MTTR. However, execution is more complex than planning. Achieving low MTTR demands orchestrated efforts across diverse organizational units, efficient IT discovery, and precise service mapping. Such high-pressure, high-stakes situations also require specialized management responses and budgetary prudence.

In this article, we discuss the importance of MTTR in modern DevOps workflows and the core practices that help reduce MTTR.  

Summary of core practices to reduce MTTR

The table below summarizes the core practices this article will explore that can help DevOps and site reliability engineering (SRE) teams reduce MTTR.

As you review these concepts, think of your incident response process as a LEGO box. Each practice serves as a building block. The key is tying these practices together in a holistic incident response strategy.

Core practice Description
Use intelligent incident detection and triage Use automated systems and AI for early and accurate incident classification.
Integrate systems for alerting, diagnostics, and runbooks Combine alerts, diagnostic tools, and runbooks for an end-to-end incident resolution process.
Automate, orchestrate and leverage chaos engineering Apply IaC, container orchestration, and simulated failures to improve system resilience and expedite recovery.
Effectively communicate and collaborate in real time Utilize dedicated channels and collaborative platforms for quick decision-making during incidents.
Embrace continuous improvement, training, and runbooks Focus on post-incident analysis, simulated training, and updated runbooks for sustained efficiency in incident management.
Develop secure, traceable, and interoperable systems Focus on post-incident analysis, simulated training, and updated runbooks for sustained efficiency in incident management.

The role of MTTR in modern DevOps incident management

Modern DevOps practices focus on agility and continuous delivery. A high MTTR is contrary to these principles. The longer it takes to resolve an issue, the slower the pace of continuous development and deployment. Operationally, prolonged resolution times imply teams constantly firefighting rather than focusing on proactive tasks and innovation.

This status quo inflates operational costs, given that it often requires an all-hands-on-deck approach to incidents and diverts resources from other valuable tasks. Delayed resolutions also add to the backlog, forcing teams to divert resources from new feature development and strategic initiatives. Consequently, this misallocation of resources can negatively affect the product roadmap and delay the time to market for new offerings.

How to reduce MTTR: Best practices & considerations

After considering the nuances of MTTR, the organizational focus should shift to how DevOps teams can fine-tune incident resolution times and sustain those gains perpetually. While technology is instrumental, it's not always the only answer.

To create a complete framework to reduce MTTR, organizations should consider the following competencies:

  • Agile issue discovery coupled with rapid incident response and workflows that speed up the remediation steps.
  • A consolidated pool of multi-faceted data that offers a 360-degree view of application and system health for crucial contextual information.
  • A sustained focus on augmenting service reliability and enhancing the likelihood that a solved problem remains a closed case.

Use intelligent incident detection and triage

Faster incident resolution begins with intelligent detection and precise triage. Leveraging machine learning algorithms for anomaly detection lets you identify issues before they escalate, allowing proactive intervention rather than reactive troubleshooting. These algorithms sift through complex data sets to flag abnormal behaviors, providing an invaluable early-warning system. Unlike traditional manual methods, intelligent systems can rapidly detect and flag issues, often before they affect end-users. This speed is especially crucial in high-velocity CI/CD pipelines where new code is frequently deployed.

When an anomaly is detected:

  • Pre-emptive alerting can issue alerts before thresholds are breached, often preventing user-impacting incidents.
  • Pattern recognition models can recognize patterns and flag irregularities before they escalate.
  • Data aggregation from multiple sources can offer a holistic view of the environment, facilitating early detection.
Squadcast’s AI/ML-based reliability automation

Enterprises also struggle with too many irrelevant or low-priority alerts, ultimately diminishing the focus and responsiveness of their incident management strategy.

A robust triage process helps to quickly and accurately categorize incidents based on severity, impact, and other key metrics. Opt for platforms that offer these capabilities:

  • Alert consolidation: Consolidates alerts from various monitoring tools, offering a single pane of truth.
  • Immediate context: Delivers metadata, such as affected services and error logs, allowing for swift assessment and action.
  • Priority routing: Assigns priority to each alert, directing them to the appropriate responders without manual sorting.

Integrate systems for alerting, diagnostics, and runbooks

Consolidating alerting, diagnostics, and runbook functionalities into a centralized, cloud-based platform can considerably reduce the timeframe between an alert’s initiation and its ensuing action. This tight-knit integration can:

  • Streamline processes
  • Directly reduce MTTR
  • Optimize service uptime

Imagine a scenario where your system experiences a surge in error rates. Traditional methods require manual intervention, shuffling between different platforms to diagnose the issue, and then another switch to a runbook for resolution steps. Each switch is time-consuming and opens the door for manual errors.

In a centralized setup, the alerting system flags the abnormal error rate and immediately triggers automated diagnostics. Based on predefined logic, auto-executable runbooks execute vanilla actions like error log checks or auto-scaling resources. There is no need for human intervention to run basic diagnostic tests or to implement standard solutions.

While these might appear as mere technical upgrades, in practice, they fundamentally reshape an incident management workflow. The single platform not only cuts down MTTR but also enhances the reliability of your KPIs. For instance, when diagnostics are automated and closely tied to alerts and runbooks, MTTR measurements become more accurate and reflective of both rapid and reliable incident resolution.

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Automate, orchestrate and leverage chaos engineering

Although it might seem counterintuitive, introducing controlled failures into systems offers invaluable insights. Chaos engineering helps simulate incidents and identify vulnerabilities before they manifest into full-blown system outages. The underlying principle is to know the system's weak links and strengthen them, and when actual incidents arise in a live environment, teams aren't diagnosing them for the first time. As an outcome of such iterative drills, they've seen issues flare up, addressed them, and have strategies to combat them. This preparedness, borne from proactive testing, translates to reduced troubleshooting times and, by extension, a considerably reduced MTTR.

Despite the level of preparedness, there will always be incidents that test your system’s resilience.

Consider a scenario where a critical system component fails due to a misconfigured server or a missing dependency. Traditionally, recovery would entail sifting through documentation, manually identifying the fault, and undertaking a time-consuming rebuild. These processes, while thorough, are time-intensive and introduce room for human error.

Compare this with an agile approach, where when incidents arise, automation tools can route alerts and execute predefined corrective measures to minimize recovery times. But automation is just a part of the equation. With Infrastructure as Code (IaC), modern enterprises can deploy, modify, and recover infrastructure setups at breakneck speeds. When an incident arises, IaC acts as the playbook containing the blueprint of the desired infrastructure state, from server configurations to application dependencies.

Effective communication and real-time collaboration

Many modern businesses, especially those adapting to the digital age, lean towards a flexible approach to managing incidents that encourages cross-functional collaboration and emphasizes continuous training to handle problems more efficiently. This approach helps get the right people with the right skills involved quickly, especially when it's unclear what's going wrong.

Once you have the actionable insights, the next logical step is to couple them with a streamlined flow of information. The right stakeholders should receive instant notifications through automated alert routing, with real-time status pages outlining the health of services and intertwined components.

Modern cloud-based collaboration platforms offer integrated toolchains, ensuring that alerts, logs, and collaboration tools interplay seamlessly. These platforms also provide APIs and webhooks to support custom integrations with other enterprise solutions, ensuring no information silo exists. As alerts trigger, stakeholders are notified immediately through a real-time status page to track services and related components.

Squadcast’s Status Page

A critical aspect here is to opt for real-time dashboards capable of not just displaying system statuses but can also be configured to showcase granular metrics, including service-level indicators (SLIs) and intricate dependency maps. This allows DevOps teams to pinpoint issues faster, reducing the time spent on status updates and coordination required for incident resolution.

Consider features like Squadcast’s Issue History Timeline, which offers a granular view into the progression of any incident. The feature provides a chronological account of incident developments that keep stakeholders informed during major service disruptions.

Embrace continuous improvement, training, and runbooks

Your enterprise's ability to identify gaps in the current response process fundamentally drives the effectiveness of post-incident reviews. Was there a step that took longer than it should have? Was there a dependency that wasn't previously accounted for? Answering these questions should highlight areas of potential improvement, ensuring that with each incident, the response becomes faster and more efficient.

In system design, redundancy is planned. The same should apply to skills within the team. While specialists are invaluable, having a team where each member is versed in various roles and functions ensures that the absence of one doesn't halt any operations.

Runbooks play a key role in cross-training and incident resolution. They encapsulate specialized knowledge and ensure that even without a particular expert, the team has a guide to navigate the resolution. It's essential to understand a runbook's limitations, though. A runbook is not an exhaustive solution manual. As each incident has unique challenges, teams can't include every remediation in a runbook.

Runbook with a checklist of steps

However, for known issues, runbooks should be developed to be as comprehensive as possible to provide step-by-step guidance, ensuring that the on-call responder isn't starting from scratch. This way, your team is prepared for known challenges while acknowledging the unpredictability of novel incidents.

Develop secure, traceable, and interoperable systems

Security protocols must be agile, adaptable, and able to keep pace with automated response actions. Implement the secure-by-design principle and incident management platforms that integrate ITSM workflows directly with your existing monitoring and alerting frameworks. This ensures that security threats trigger the same response workflows as operational issues.

Leverage advanced traceability features to reduce the need for gut-based decision-making, replacing it with data-driven insights. To expedite the traceability process, employ tagging and context-aware logging that offer immediate context for anomalous events.

For practical real-time oversight, overlay deployment information on telemetry data through dashboards. With a setup like Grafana or Kibana, you can visualize the impact of deployments, making it easier to correlate them with system performance metrics. This provides a more direct, data-driven path to understand disruptions and act on them, further minimizing MTTR and enhancing system robustness.

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Conclusion

As Murphy's Law states, what can go wrong will go wrong. A strategic approach to MTTR helps teams deal with this reality without compromising on availability.

Systematically improving the resilience of your systems requires a well-calibrated alert policy and real-time data streams for contextual depth. By following the best practices in this article, teams can reliability reduce MTTR and keep critical systems functioning and delivering business value.

To learn more about how Squadcast’s rule-based triggers, Response Actions, and Executable Runbooks can improve your incident response strategy, click for a free demo here.

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Squadcast is a leader in Incident Management on G2 Squadcast is a leader in Mid-Market IT Service Management (ITSM) Tools on G2 Squadcast is a leader in Americas IT Alerting on G2
Best IT Management Products 2024 Squadcast is a leader in Europe IT Alerting on G2 Squadcast is a leader in Enterprise Incident Management on G2
Users love Squadcast on G2
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