Gartner has recently released their 2019 market guide for AIOps platforms, their key findings include: AIOps improves the decision making of I&O (infrastructure operation) leaders by summarising the huge data sets. I&O leaders make use of the AIOps platform to refine the application performance across the application lifecycle. It improves IT service management and automation.
- The AIOps improves the IT functions including event correlation, anomaly detection, root cause analysis, and natural language processing, but the Application of AIOps working as ITSM and DevOps is evolving at a slower pace.
- The AIOps platform offerings are split into two approaches including domain-agonistic and domain-centric solutions.
- Enterprises adopt the AIOps platform to correlate across Application Performance Monitoring (APM), IT Infrastructure Monitoring (ITIM), Network Performance Monitoring (NPM), diagnostics tools, and digital experience monitoring.
- AIOps platform maturity, IT skills and operations maturity are essential elements to provide quick time to value. Other emerging challenges for advanced deployments include data quality and insufficient data science skills within I&O.
Recommendations for I&O leaders
This guide recommends I&O leaders focused on cloud management and operations to:
- Focus on a particular use case and adopt an incremental approach by replacing rule-based event analytics and expand the domain-centric workflows including application and network diagnostics.
- Adopt the AIOps solution to address specific use cases that are built into a monitoring tool that consumes events, metrics, and traces.
- Choose the AIOps platform that can be applied to ITSM use cases including support task automation, knowledge management, and change analysis.
- Enable continuous insights across IT operations management of AIOps platform by supporting three aspects of AIOps platform: observe, engage and act.
“By 2023, 40% of DevOps teams will augment application and infrastructure monitoring tools with artificial intelligence for IT operations (AIOps) platform capabilities.” – Gartner
AIOps platform addresses the ever-increasing volume, variety, and velocity of data generated in response to digital transformation.
AIOps platform improves a broad range of IT operations and their central functions include:
- Obtaining data from multiple sources including infrastructure, network, applications, cloud and monitoring tools.
- Enabling data analytics using machine learning at two points:
- Real-time analysis
- Historical data analysis
- Storing and proving access to the data
- Suggesting contextual responses for the analysis
- Initiates the next action based on the prescription
Gartner estimates the growth of the AIOps market to be between $300 million and $500 million per year. Artificial Intelligence technologies including machine learning influenced the growth of ITOM over the past two decades.
Use of AI in IT operations will address the following:
- Rapid data volumes generated by IT systems, networks, and applications.
- Increases the data variety by analyzing events, metrics, traces, wire data, network flow data, customer sentiment and more.
- Increases velocity of data being generated, change in IT infrastructures and maintains observability and enhance engagement due to adoption of cloud-native and ephemeral architectures.
- Predict change success and SLA failure.
According to Gartner, the 4 stages of IT operations monitoring is given below
According to Gartner, the key capabilities of the AIOps platform include:
- Data injection and handling: All organizations operating in a complex environment should be able to obtain data, metrics, and events across different data sources.
- Implement machine learning algorithms for event correlation, pattern discovery and anomaly detection and root cause analysis.
- Making use of prescriptive advice to take automated actions to solve issues and bridge ITSM and ITOM processes.