AI-Ops : Next generation Ops, should you be worried?
Artificial Intelligence (AI) has burst on the scene as a way of mitigating many challenges. Gartner reports that by 2019, 25% of global enterprises would implement an AIOps platform supporting two or more major IT operations functions. Furthermore, they report that, by 2020, approximately 50% of enterprises will be actively using AI Ops for business execution and IT Operations.
AI and ML today are getting applied to automate hitherto manual tasks and processes in IT Ops. This is plausible with the tools such as MoogSoft, Digitate Ignio etc as they have self healing capability. These tools and platforms analyze large amount of data from disparate sources and using algorithms , identify patterns for predictive and preventive insight.
These tools have multitude of capabilities but its not limited to the following. This includes 1) Anomaly detection 2) Automated remediation 3) self-healing capability from tickets/monitors. 4) knowledge base. 5) quick resolution 6) Precision
Platform Components or Elements
If looked at holistically, the key components for enterprise level IT AIL Ops platform includes a 1) System of Engagement , 2) A system of Record 3) Automation and 4) A Big Data platform . Since they are still not at a maturity level, they address some specific aspect
System of Data Source : If we start from the bottom , the data source ecosystem provides visibility across the both the virtual and physical stack. The data from tickets, monitoring tool , Application logs , Events , batch Jobs etc can generate lots of data which needs to be consumed with filers and actionable items that is useful for the IT operation team
System of Engagement : The system of engagement should be designed for reducing noise and give insight in real time. It uses Real time processing for any potential break in the system and let the Ops team know in advance. This means it helps the team in early incident detection . Examples of System of Engagement are tools like Moogsoft or Ignio
System of Record; This is the source of truth data aligned between the IT and ITSM folks.This essentially manages all tickets that broke the system and knowledge for future reference and ties back to the CMDB . This can be improved over time by the system of engagement as the relationships are not known and are discovered on a continuous basis. Systems of Record include tools like ServiceNow and Jira.
Automation : This helps to automatically run resolution scripts to streamline repetitive tasks from incidents that occur on a regular basis.Common actions include orchestration, runbook automation, and IT automation like patch application of servers. Systems of Automation include tools generally used in DevOps like Ansible and Puppet and plug them into the CI/CD tool chain.
Big Data : The big data platform is used to create meaning full dashboard for business for reporting and potentially diagnostics. It ideally maintains all of the data that you would ever need to investigate, which typically exists in the form of logs. When you know what you need to look for (from insights provided by the System of Engagement) the data store is crucial for conducting that deeper analysis. Data store tools include products such as Splunk and ELK.
In Conclusion : AIOps Platforms are the “next generation” solution for IT Operations. IT complexity will continue to increase at an exponential pace, faster than manual capacity. This is why IT operations need to strategically leverage AIOps platforms to accomplish certain tasks, and use resources to be responsible for others tasks particularly as it relates to analytics and customer experience.
Source: Gartner for 2019 growth and Prediction for AIOps