How AIOps Platforms Are Transforming the IT Industry
When trying to determine how AIOps platforms are transforming the IT industry, start by looking at the evolution of IT infrastructure over the past decade. The digital transformation of the modern business has been underway for a while now. More and more services and applications are delivered online and reliance on the cloud continues to grow.
In order to keep up, the underlying infrastructure has had to adapt by upgrading legacy systems – even as next-generation technologies are deployed in parallel. The dependence on third-party tools such as cloud computing services is here to stay and is ever increasing.
Further, the prevalence of software-defined structures has brought about orchestration and provisioning services to accommodate the constantly morphing infrastructure.
As a result, IT operations teams have been thrust into a position where they are required to design, build and maintain dynamic, global scale infrastructures in hybrid ecosystems. Traditional IT operations management (ITOM) approaches simply can’t keep pace. Here are some of the major challenges that have surfaced:
- Although the infrastructure is dynamic, it still needs to be managed – making service assurance a moving target
- The multitude of monitoring and management tools often have overlapping functionality
- A preponderance of data has now proliferated the ecosystem, making monitoring difficult
- The larger the infrastructures get, the more IT domains that need to be managed are siloed
Enter AIOps Platforms
It is in addressing these challenges that artificial intelligence for IT operations (AIOps) has the potential to revolutionize the IT industry. The timing is right. Originally known as algorithmic intelligence for IT operations, AIOps capabilities are transforming the manner in which operations are conducted.
To further understand how this transformation will unfold, let’s examine some key capabilities of AIOps:
Big data:
AIOps solutions offer the ability to manage and respond to incidents in large volumes of disparate data by automatically consolidating, organizing, filtering and enriching data points to add value.
Machine learning:
Enables an IT ops system to automatically learn and improve from experience without explicit programming.
Analytics:
Encompassing data science, statistical and mathematical analysis, correlation, and modeling, today’s advanced analytics are able to extract meaningful insights from large volumes of data.
Automations:
This is the ability of AIOps platforms to act on insights in order to investigate and remediate issues – and to execute either predetermined or decision-driven workflow sequences.
These capabilities allow AIOps to perform two primary functions:
- Derive insights
- Act upon them
Let’s take a deeper look at these functions.
Deriving Meaningful Insights With AIOps Products
The typical global IT infrastructure that supports the delivery of services is extremely chatty when it comes to generating information. The challenge is how to glean useful intelligence from this tidal wave of data.
AIOps products excel in aggregating and consolidating data. First, it provides a common repository and access to it, via a data lake or a data pipeline. Next, they consolidate data from across monitoring and management systems.
While that in itself does not sound remarkable, it’s the manner in which they do it that is. AIOps products are able to leverage metadata and time-based information in their decision-making, and also have the intelligence to discriminate in order to reduce duplication.
This “data enrichment” in the ingestion phase makes it possible to then conduct AI-driven analysis necessary to generate cross-contextual insights:
- Historical data, such as logs and events, offer a retroactive view and are augmented by applying metadata and tags to provide context for search indexing.
- Real-time data, such as performance and telemetry information, are tagged to generate time-series by overlaying data points with time stamps.
Adding suitable labels to provide key-value pairs brings further value when this information is used later.
In addition to simply accepting what existing systems provide, AIOps products also have the ability to reach out and identify “data of interest.” This makes it possible to execute workflows to conduct the kind of forensic analysis and troubleshooting to determine causality – and to do it in a fast and automated manner.
By normalizing data, enriching it and making it universally accessible, AIOps products essentially democratize the data and make newer forms of analysis possible. They drive collaboration across teams and yield insights that, when properly implemented, bring about significant improvements in service assurance.
Acting Upon Insights
We can measure the extent to which AIOps platforms improve the infrastructure’s ability to heal. They are simply faster than traditional approaches when it comes to determining the root cause of issues when they occur. They also have the ability to provide troubleshooting and remediation services via workflows and automations. They excel at cutting through the maze of incoming events from multiple sources to rapidly identify patterns and focus on areas of interest.
The real promise of AIOps capabilities, however, lies in its predictive qualities. For the first time, it has become possible to realize a proactive and predictive approach to ITOM – to get ahead of issues before they occur.
By combining performance and application metrics with real-time monitoring, it is possible to apply techniques such as dynamic thresholds and baselines to detect abnormalities and see problems forming before they occur. In addition to providing alerts and notifications as service degradation begins to occur, these AIOps capabilities can be extended to alert the operations team of impending problems. This ability to know ahead of time allows actions to prevent an outage from occurring in the first place. When combined with automations, provisioning systems can kick in to allocate additional resources – for example, to stave off the impending impact to a business service that is supported by the affected infrastructure.
Building Proactive Operations
While this is just one of several use cases, it serves to demonstrate the truly proactive operations characteristics that AIOps can deliver to the IT industry.
Some AIOps platforms can also build a top-to-bottom view of the infrastructure and track from end-to-end the process flows that deliver a business service across it. This holistic view makes it possible to actually understand the business impact of an issue in the underlying architecture.
Capabilities such as this make for a customer-oriented approach to service assurance that focuses on the business impact rather than the technical issues underlying an outage.
In short, AIOps enables a data-driven, analytical approach to provide insights and actionable intelligence for IT operations monitoring tools. And this is what is transforming the IT industry.