Using AIOps for Better Incident Management
DevOps brought a more collaborative and efficient workflow to the tech world. With the integration of AIOps, automation was taken a step further, using artificial intelligence to provide teams with much faster root-cause analysis and algorithmic noise reduction. One of the primary areas that benefits largely from the adoption of AIOps is incident management.
AIOps can help DevOps teams automate workflows for smarter and more efficient incident management, freeing up time for IT operations team members to focus on innovation improving user experience.
In this article, we’ll take a look at how AIOps can improve incident management from detection and identification through response, as well as some of the top AIOps tools available to use for incident management.
How AIOps is Better for Incident Management
In DevOps, whenever an incident occurs, it is up to the SREs (Site Reliability Engineers) and DevOps team to sift through all of the noise and data in order to determine a root cause. Once an incident is detected and identified, it is up to them to correctly categorize and prioritize the incident before ultimately deciding which teams and people should be alerted and involved.
What this means for IT operations is that their focus is primarily on responding to incidents and jumping onto emergency tasks in order to avoid any unplanned downtime of the service. On-call workers often quickly burn out in this type of environment, becoming less agile or innovative and even leaving the company as a result of this excessive, unplanned work.
The fact is, analyzing and communicating with large amounts of different data points is a large and tedious task for any human. As services and infrastructures become more complex, so too do the data sources. Incident management can quickly become a lot for a single team to handle, so the obvious option was often to simply scale the team. Artificial intelligence can help teams effectively monitor and understand all of their data without relying solely on team members.
However, this is where AIOps truly shines. AIOps stands for Artificial Intelligence for IT Operations. Using data science and artificial intelligence to analyze all of the given data from your IT operations and DevOps tools, AIOps is able to provide DevOps teams with AI-backed insights and intelligence. This leads to faster root cause analysis through automated incident management processes, including:
- Incident identification: AIOps analyzes data to automatically detect and identify an incident. Once an incident is identified, its categorization can also be automated based on past occurrences of related incidents.
- Incident prioritization: Incidents can also automatically be prioritized by AIOps.
- Incident assignment: The system will determine which team members need to be involved in responding to an incident, if any. In some cases, AIOps is able to resolve incidents automatically from previous learning.
- Incident response: Incident response times are dramatically improved with AIOps automation, allowing team members to focus more on customer satisfaction and user experience.
AIOps allows teams to proactively detect and respond to incidents in real time, while applying machine learning (ML) to predict and prevent future or related problems from occurring.
Top AIOps Tools for Incident Management
There are several AIOps tools you can use to help with incident management. These AIOps tools can help the system learn about itself more quickly and effectively in order to create smarter algorithms.
These are some of our favorite AIOps tools for incident management:
Runbook Automation (Rundeck)
Runbook Automation works to reduce incident resolution times and minimize escalations. AIOps tools like RunDeck utlilize runbook automation (RBA) to quickly and effectively diagnose and resolve incidents as they happen. Rundeck is a great option because of its easy setup and it integrates seamlessly with your team’s existing tools, script, and APIs. Another great feature in Rundeck is its ability to easily expand the number of people able to react to incidents, as well as their specific capabilities in responding to an incident.
Github (Puppet and Evolven)
The Github community is a great resource for finding great open source AIOps tools to integrate within your infrastructure. Puppet Automation is an open source management and deployment tool that works to automate system administration processes. Evolven is a great AIOps tool for incident detection and management. Evolven uses intelligent analytics and machine learning to detect and prioritize incidents automatically, learning overtime to predict and prevent future incidents.
PagerDuty Event Intelligence is a powerful AIOps tool that is designed to help minimize the noise and provide DevOps teams with intelligent insight to take the right actions when incidents occur. Event Intelligence uses smart noise reduction to effectively silence alerts that require no response, and automatically group alerts based on the alert content, time period, past groupings, and custom thresholds your team may determine. As Event Intelligence learns more about the system, incident remediation can take place automatically without involving any team members.
How to Get the Most Out of AIOps
AIOps tools are a great way to truly get the most out of AIOps. These tools can integrate together within your applications and infrastructure in order to quickly learn the system and create more reliable services.
If you would like to learn more about integrating AIOps for your team, please give us a call to discuss your options and start a 14-day free trial today..
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