The global pandemic has radically changed how enterprise IT services are consumed, both in the short and long term. Here's how AIOps can help IT Ops teams:
Start with The New Normal for IT Ops Deepens Need for AI - Part 1
Managing the New Normal
The new normal includes not only periodic recurrences of Covid-19 outbreaks but also the periodic emergence of new global pandemics. This means putting in place at least three layers of digital business continuity practice:
■ Continuity for illness-free periods
■ Continuity for periods marked by known pandemics
■ Continuity for periods marked by new pandemics
Rules-based, historical data analysis, and predictive analysis based on history become useless in this scenario. Instead, what's needed is technology that can anticipate outages without reliance on stable historical patterns, as AIOps does.
Significant economic contraction and resulting pressure on both capital and operational expenditures will lead to chronic understaffing of IT operations and NOC functions. IT Ops can leverage AIOps to achieve heightened levels of automation and to support radically deep cuts in the number of tools required to both monitor the digital infrastructure and respond to incidents that occur.
As remote work becomes default, it will become impossible to replicate the "monitoring cockpit" experience or the "service desk cockpit" experience. IT operations team members and first responders will need to get by with standard IT management software. That requires a significant increase in the number of signals that require observation on the one hand and the number of tickets which require response on the other hand. AIOps can help to manage this by reducing signals and tickets.
Optimizing the New Normal
The move to an almost entirely virtualized infrastructure and service portfolio will allow for maximum agility and the ability to reconfigure people, processes and technologies to meet emerging business needs (which will themselves likely be novel in the new normal.) To provide continuous assurance of service levels (even as the services themselves evolve), IT Ops teams can leverage AIOps and its ability to anticipate outages and brown-outs on the basis of data as it arrives, as opposed to pre-existing static models of topology and user behaviour.
The shift from an IT budget that, beyond labor commitments, is dominated by capital expenditures and maintenance, to one that is almost entirely dominated by renewable operational expenditures, will increase business resilience in the face of the three types of continuity issues outlined above. AIOps can help in this area as well by helping to anticipate short-term fluctuations in resource requirements based on the possibility of looming outages and brown-outs.
The economic contraction will accelerate digitalization and, in fact, lead to what may be called "maximum digitalization" with the consequence that, for the most part, business process events will be IT system state changes. One will not be able to manage business processes unless one simultaneously manages IT system events. AIOps can be invaluable here by effectively discovering and managing the higher-level IT system event patterns that are, in fact, business process patterns.
The Latest
In MEAN TIME TO INSIGHT Episode 11, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Secure Access Service Edge (SASE) ...
On average, only 48% of digital initiatives enterprise-wide meet or exceed their business outcome targets according to Gartner's annual global survey of CIOs and technology executives ...
Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...
The mobile app industry continues to grow in size, complexity, and competition. Also not slowing down? Consumer expectations are rising exponentially along with the use of mobile apps. To meet these expectations, mobile teams need to take a comprehensive, holistic approach to their app experience ...
Users have become digital hoarders, saving everything they handle, including outdated reports, duplicate files and irrelevant documents that make it difficult to find critical information, slowing down systems and productivity. In digital terms, they have simply shoved the mess off their desks and into the virtual storage bins ...
Today we could be witnessing the dawn of a new age in software development, transformed by Artificial Intelligence (AI). But is AI a gateway or a precipice? Is AI in software development transformative, just the latest helpful tool, or a bunch of hype? To help with this assessment, DEVOPSdigest invited experts across the industry to comment on how AI can support the SDLC. In this epic multi-part series to be posted over the next several weeks, DEVOPSdigest will explore the advantages and disadvantages; the current state of maturity and adoption; and how AI will impact the processes, the developers, and the future of software development ...
Half of all employees are using Shadow AI (i.e. non-company issued AI tools), according to a new report by Software AG ...
On their digital transformation journey, companies are migrating more workloads to the cloud, which can incur higher costs during the process due to the higher volume of cloud resources needed ... Here are four critical components of a cloud governance framework that can help keep cloud costs under control ...
Operational resilience is an organization's ability to predict, respond to, and prevent unplanned work to drive reliable customer experiences and protect revenue. This doesn't just apply to downtime; it also covers service degradation due to latency or other factors. But make no mistake — when things go sideways, the bottom line and the customer are impacted ...
Organizations continue to struggle to generate business value with AI. Despite increased investments in AI, only 34% of AI professionals feel fully equipped with the tools necessary to meet their organization's AI goals, according to The Unmet AI Needs Surveywas conducted by DataRobot ...