How the Incident Response Software Stack Has Evolved


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Remember when incident response involved receiving notifications via physical pagers when something went wrong? Unless you’ve worked in IT for a number of decades, you probably don’t. It has been many years since incident response technology was so primitive and manual.

If you are fortunate enough not to remember those early days – or if you do and have lost track of just how far we’ve come since that time – this article is for you. Below, we walk through the major stages in the evolution of incident response, with a focus on how the tooling has evolved and what the major changes in incident response software have meant for the way teams work.

The Early Days: Manual Monitoring and Alerting

Prior to the late 1990s, nothing resembling modern incident management or monitoring tooling existed. You often learned that your server had gone down only because an end-user complained. To the extent that any sort of automated monitoring was possible, it was powered by custom scripts that used very basic methods, such as pings to check whether a host was up or the df command to see if file systems were running out of space. If your script was really sophisticated for its time, it might send you an email to let you know when something seemed off.

Although this approach to incident response may seem hopelessly primitive by modern standards, it made sense at the time. IT environments were smaller and simpler. Virtually everything ran on-premises, which increased the chances that an IT team would literally hear or see a server going down.

There were also far fewer layers of infrastructure to monitor: you had bare-metal servers, the applications hosted on them, and some routers to handle networking. There was less to monitor and less that could fail.

The Birth of Automated Monitoring

The incident management landscape experienced a major breakthrough in the initial years of the new millenium, when the first automated monitoring platforms debuted. Some of the most commonly used open source tools today, including Zabbix (which became an open source project in 2001) and Nagios (first released in 2002), trace their roots to this period.

For the first time, these tools made it possible to automate monitoring workflows that had previously depended on manual effort and custom scripting. In that respect, they gave birth to the type of Application Performance Management (APM) tooling that is still familiar to incident management teams today.

In other ways, though, tools like Nagios and Zabbix were a far cry from modern incident management platforms. They told you when something was wrong, but did little or nothing to help pinpoint the root cause of the problem. For that, you needed to look through logs manually. Furthermore, these tools did not help incident response teams manage the response process by categorizing incidents according to importance or coordinating on-call duties, for example. Those tasks were also left to engineers to figure out manually.

The Arrival of the Cloud

By the later 2000s, as more and more organizations began migrating workloads to the cloud, incident response stacks had to evolve for the cloud era. Not only did the software need to become capable of monitoring workloads hosted on cloud servers over which incident response teams had no physical control, but it also had to gain greater awareness of environment context.

The latter functionality is important in a cloud-based environment because cloud workloads tend to scale up and down frequently. In the cloud, a server or database that shuts down could be a sign of a critical problem, or it could just be a natural response to a fluctuation in demand. Incident response tools must be able to recognize the difference.

Grappling with New Levels of Complexity

Over the course of the 2010s, as organizations built complicated hybrid-cloud and multi-cloud models that hosted a mix of bare-metal servers, virtual machines, and containers, the complexity of the environments they had to manage reached new levels. So did the challenge of achieving visibility into the multi-layered, constantly changing infrastructures that hosted these workloads.

These pressures gave rise to incident response tools that are more sophisticated than ever, and that prioritize efficiency and optimization over simply putting out fires as they appear. Today’s best incident response platforms analyze data not just to understand incidents better, but also to help SREs determine which incidents to prioritize, mitigate alert fatigue, and ensure that the right team members are assigned to respond to each incident. In these respects, modern incident response stacks empower teams to achieve greater levels of reliability with fewer resources.

If you look back over the way incident response has evolved over the past two decades, a few overarching trends are clear:

  • Automation: Incident response tools and workflows have become increasingly automated.
  • Context awareness: In order to work effectively in constantly changing environments, incident response platforms have gained the ability to use analytics to understand the many variables at play in monitoring for incidents. In this way, they can successfully distinguish real problems from ordinary churn.
  • Improving the incident management process: In recent years, the focus of incident response has expanded to include simplifying the workflow that engineers use when responding to incidents. The goal of incident management software today is not just to help teams detect and interpret issues, but also to organize their response efforts as efficiently as possible.

What comes next? Time will tell, but the ability to handle an even greater amount of complexity – both in terms of the composition of software environments and the workflows required to handle incidents – seems likely to be a continued area of focus for incident response software going forward.

Chris Tozzi has worked as a journalist and Linux systems administrator. He has particular interests in open source, agile infrastructure and networking. He is Senior Editor of content and a DevOps Analyst at Fixate IO.


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