Leveraging AIOps for SRE

Cloud, Agile, and DevOps have revolutionized how software is developed and consumed. Speed, dynamic implementation of changes, global presence, and quality are the areas that the IT revolution has influenced. While organizations are banking on the newer tech stacks and platforms to cater to the demands of a pool of ever-increasing users, it has become imperative to balance agility with reliability.

Site Reliability Engineering (SRE) is an approach that deals with operations, scalability, and reliability aspects of the development process. SRE applies the elements of software engineering to operations and infrastructure problems. The primary goal is to create scalable and highly reliable systems by offering solutions to handle complex operations. We can consider SRE as a specific implementation of DevOps. While DevOps is more focused on Ops and development pipelines, SRE focuses on ensuring the operations run as expected. Benjamin Treynor Sloss developed it in 2003 and, since then, has been an integral part of the DevOps process in many organizations. Simply put, SRE comes into play when preparing for failures in production. It helps companies boost the reliability of their site infrastructure by spotting failures, identifying backup plans, and taking steps to mitigate risks that may occur from failures in the future.

It is often said that data is the next biggest commodity. Thanks to the advancements in technology, we have plenty of it. The data that is produced and consumed right now is vast. Managing vast amounts of data is difficult but getting actionable outputs is humanly impossible. Effective management of enormous amounts of data needs systems in place, and that is where Artificial Intelligence for IT Operations (AIOps) comes in. AIOps platforms lean on machine learning, big data, and other data engineering techniques for monitoring and automation to enhance IT operations. They use different data collection methods to gather data, process it, and derive outputs that are valuable and can be put to use. Simply put, you are creating a process where you can get actionable items from your data.

How AIOps can solve SRE problems

SRE tracks and resolves IT outages before end-users are affected. However, monitoring all the processes and data in real-time can be challenging. This is where AIOps can be handy for the SRE teams. AIOps can provide reliable support with specialized proactive monitoring, warning, and reporting systems that will inform about the issues and incidents before they get out of hand and affect users. This saves considerable time and effort for SREs and directly benefits end-users. AI involves less manual work and needs lesser technical staff and fewer engineers to monitor or highlight problems in advance.

Let’s see how AIOps can augment your SRE initiatives.

Application of AIOps by SRE teams

Here are some of the most common application areas in SRE for AIOps:

  • Faster incident resolution: SREs must appropriately respond to challenges and manage incidents. SRE teams are responsible for complex and dynamic applications across different cloud environments. They focus on techniques that help avoid past incidents while mitigating risks at the end-user level. Vast amounts of data bring in multiple challenges, and Intelligent IT operations help them automate incident management, saving a lot of manual effort and time. AI can add intelligence to your automation and provide faster incident resolutions, and in some cases, can help predict the incidences before they happen.

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Opcito Technologies

Product engineering experts specializing in DevOps, Containers, Cloud, Automation, Blockchain, Test Engineering, & Open Source Tech