Partnership will speed adoption and time-to-value for enterprises and companies adopting AIOps.
The demand for AIOps (Artificial Intelligence in IT Operations) is “slowly” exploding. The pain is exploding while the adoption is slow due to the cost, time-to-value and risk associated with existing tools. The partnership between Einar & Partners and AIMS sets out to change the adoption curve.
Today, the customer demand is rising sharply as organizations now realise that adding headcount in IT Operations is not going to solve their new operational challenges driven by digital business, cloud adoption, agile deployments, hybrid environments, containers and microservices. With the Artificial Intelligence hype permeating throughout the economy it is no surprise that CIO’s and IT Operations leadership ask what Artificial Intelligence can do for IT Operations.
Gartner’s answer is to put AIOps near the top of their hype cycle, but recommends organizations to start testing, validating use cases or implement AIOps for select workloads.
Gartner says that AIOps will be transformative for IT Operations in the years to come and recommend CIOs and IT Operations teams to start experimenting with AIOps. Read the full Gartner report “How to Get Started with AIOps”.
To answer the question why demand is “slowly” exploding it is important to understand the available options to implement AIOps in the market and what is required. But first let’s cover the key capabilities of AIOps to make sure we know what we are talking about!
AIOps is ultimately about leveraging algorithms, machine learning (and maybe Artificial Intelligence depending on your definition) to automate tasks that IT Operations today struggle with - or fail at - due to the new complexities. In essences these are the capabilities of AIOps:
- A flexible data ingestion / harvesting capability for time series data and logs
- Service Topology detection to identify the components of infrastructure, applications and services a company’s critical services rely on (read : revenue or productivity generation)
- Correlation engine to identify anomalies and patterns
- Business context relevant anomaly alerting
- Ability to take action (manual or intelligent self-healing)
You should look at these capabilities as sequential building blocks. You cannot skip elements and jump to implementing intelligent self-healing (#5) and succeed. You need quality data in, the right “AI”, the right context and the right automation scripts all tuned. As the saying goes “shit in - shit out”.
This is why AIOps is “slowly” exploding. Implementing AIOps with the tools that have been available in the market has been time consuming requiring large projects and budgets with high uncertainty.
This is what AIMS has set out to change. At AIMS we have invested in building an automated, autonomous and generalized AIOps platform for years. Originating from scientific research at the University of Oslo, the AIMS AIOps platform allows organisations of any size to afford AIOps. This is done through reducing the barrier to implement and by shortening time-to-value to days - not months and years.
The partnership with Einar & Partners sets out to change the adoption rate and time-to-value for AIOps
The partnership with Einar & Partners is an important step towards making the AIMS AIOps platform available to the broader market, but also to enhance the value of the AIMS platform through integrating AIMS with ServiceNow.
Einar & Partners is a highly experienced consultancy in AIOps and ServiceNow implementation with a deep understanding of the needs and challenges organisations face implementing AIOps with the tools commonly used in the market.
ServiceNow is the workflow tool of choice for more than 6000 large enterprises globally. Through the partnership with Einar & Partners AIMS will be integrated with ServiceNow to ensure that AIMS easily integrates with customers' existing workflows. The integration intends to add value synergies across ITMS (ticketing), CMDB (service topology) and ITOM (anomaly detection) parts of ServiceNow.