New technology rises: AIOps aims to facilitate, unify and modernize existing Ops processes
AIOps is an emerging technology which focuses on bringing the benefits of artificial intelligence to Ops. However, AIOps is *not* designed to replace existing operations model as well as tools, rather unify and modernize them with algorithmic approach powered by machine learning and big data. We talked with Enzo Signore, CMO at FixStream about its benefits, tooling and more.
JAXenter: We have DevOps, NoOps, and now AIOps. What is Algorithmic IT Operations and why do we need to add machine learning and artificial intelligence to software development and network operations?
Enzo Signore: AIOps stands for Artificial Intelligence for IT Operations. It’s the next generation of IT operations analytics or ITOA. And its value is in helping organizations address IT challenges on a number of fronts.
These challenges include:
· The increasing complexity and dynamic nature of IT architectures
· Digital business transformation
· Siloed IT operations
· Exponential growth of uncorrelated data
All of the above render traditional, domain-centric monitoring and IT operations management inadequate. Such systems can’t correlate the onslaught of data various IT domains create. What’s more, they’re unable to provide the insights IT operations teams need to proactively manage their environments. And that just doesn’t work.
IT organizations need a new class of technology to modernize the IT operations process. This technology needs to be able to correlate millions of data points across all IT domains. It should have the smarts to apply machine learning to detect patterns. And it should present that information so organizations can easily see what’s happening and gain insights.
This technology is AIOps.
JAXenter: How is machine learning transforming IT operations?
We don’t foresee AIOps eliminating existing operations methodologies anytime soon, rather will optimize them to gain agility and efficiency.
Enzo Signore: Machine learning is transforming IT since it can correlate millions of disparate data points across the entire IT stack, detect patterns and predict issues much faster and with a much higher degree of accuracy than traditional tools can.
For instance, it takes today on average 4 hours to determine the root cause of an issue across relatively static and predictable IT environments. Add virtualization (which literally moves applications across the environment), add cloud that reduces visibility, and add containers that can live for very short periods of time, and IT cannot simply understand anymore the correlation of data and events in a predictable way. ML can automatically detect the patterns and help IT operations find the root cause as well as predict the next set of events.
JAXenter: Who came up with this term and why is it gaining momentum?
Enzo Signore: Several analysts have focused on this segment, but Gartner is the largest/first firm to name/focus on this.
JAXenter: How can AIOps help me navigate my DevOps tasks?
Enzo Signore: It can help correlate containers with other entities and help DevOps accelerate their processes.
DevOps tasks are fully automated with CI/CD methodologies and can significantly be benefitted by analytics-driven from application to infrastructure mapping. This will allow the DevOps orchestration for scale-up, scale-down as well as operations management of micro-services across infrastructure entities in a hybrid environment.
JAXenter: Does AIOps mean that we need to embrace NoOps first or is there no connection between them?
Enzo Signore: No need to have NoOps – AIOps is facilitating, unifying and modernizing existing IT Ops processes.
The objectives of AIOps are centered around automating and unifying operations tasks across domains as much as possible. This is not designed to replace existing operations model as well as tools, rather unify and modernize them with algorithmic approach powered by machine learning and big data. We don’t foresee AIOps eliminating existing operations methodologies anytime soon, rather will optimize them to gain agility and efficiency.
JAXenter: What tooling does AIOps come with?
Enzo Signore: AIOps tools comes with a variety of capabilities that centers around efficient operational data acquisition for a varieties of sources, ability to detect relationships and patterns between them, open API interfaces to connect with existing domain centric tools to collect data and applying machine learning techniques, detects root causes of business impacting issues triggered from problems across the stacks, predicting issues before they even happen.
The foundational architecture components of an AIOps platform are – open data ingestion, auto-discovery, correlation, visualization, machine learning and automation.
JAXenter: How can AIOps technology transform enterprise IT?
Enzo Signore: AIOps technology brings business KPIs and SLA closer to efficiency in IT operations, thus significantly transforming enterprise IT operations to make them more business driven. This increases business efficiency and agility, enables innovation, increases customer satisfaction.