This is a guest post by Richard Gerdis, vice-president for Asia-Pacific at LogicMonitor
IT teams in Asia are under nonstop pressure to work faster and deliver better results – with fewer employees and at a lower cost than ever before. Against the backdrop of new virus strains causing repeated lockdowns for Asia-Pacific nations, the challenge of making digital transformation happen for organisations has become a difficult balancing act for IT teams everywhere.
Compounding these rising expectations is the complexity of the modern IT environment, which now includes hybrid infrastructures and ever-increasing data needs. The only way to remain operational in this space is to have extensive visibility of and capability within the IT environment.
That isn’t easy. To enable speed and agility, especially given current market conditions, many IT organisations must support infrastructure in multiple clouds, on-premises, the connections in between, and software-as-a-service (SaaS) applications. On top of that, organisations are up against the rapid growth in data volumes generated by infrastructure and applications that must be captured, analysed, and used to improve business processes.
If organisations struggle to maintain visibility into their entire IT infrastructure, they will also be blind to issues that arise in their environments, leading to downtime and poor performance. In IT, performance is a key component of customer satisfaction and retention. After all, if a customer is impeded from using a ride hailing app, food delivery service, or fintech platform, they will simply choose a competitor that can provide the service they are looking for. With certain industries facing increasing pressure and strain due to coronavirus outbreaks around the world, now is not the time for unplanned downtime or service disruptions.
To meet these challenges and ensure continuity of service, many companies are turning to AIOps.
What is AIOps?
Coined by Gartner, AIOps is a term that stands for artificial intelligence (AI) for IT operations (Ops). AIOps uses machine learning (ML) and data science to help identify, troubleshoot and resolve IT operations and performance issues. The concept of AIOps also typically involves at least some automation and reduction in manual efforts.
AIOps starts with the ingestion of big data that could be used to produce a historical analysis of stored data, or a real-time analysis of the ingested data. By leveraging ML, AIOps initiates an action based on insights and analytics gathered from the aforementioned sources. These capabilities give IT teams a powerful way to stay on top of tasks that are otherwise labour-intensive without the platform.
As IT infrastructure increases in complexity, so does the uptick in AIOps’ popularity. In fact, Gartner predicts that the use of AIOps and digital experience monitoring tools to monitor applications and infrastructure among large enterprises will increase to 30% in 2023. Gartner also projects that the global AI-derived business value will reach nearly $3.9tn by 2022.
What problems can AIOps solve?
Given the pressure that IT teams are put under to solve problems as quickly as possible, it is beneficial for them to use an intelligent infrastructure monitoring system to analyse large amounts of data and present findings in an efficient, actionable way. AIOps resolves these needs by providing the data-validated insight IT teams need to make smarter, faster decisions in an automated way. This data includes:
- Infrastructure and application data, such as the data from monitoring systems and logs from intelligent application and service monitoring (IASM) tools
- IT service management (ITSM) data, such as tickets, change controls and asset information
- Business system data, including robotics process automation (RPA) tools
- Advanced business metrics to help stakeholders understand how issues affect their business
The biggest advantage of AIOps is arguably its performance monitoring capabilities. Modern monitoring platforms can provide visibility into today’s hybrid infrastructures, but visibility alone is no longer enough. Traditional manual processes of sorting through deep arrays of monitored data to find meaningful information are not scalable, and take too long in the event of an outage. IT teams need an intelligent monitoring platform to identify issues faster, especially given today’s increasingly complex environments.
AIOps drives better business outcomes
For IT organisations, bringing together a full range of relevant data can enable service improvements and dramatically enhance business outcomes. AIOps provides IT teams with more context and insight into issues through predictive capabilities and root cause analyses.
For example, AIOps can detect problematic resource usage patterns that, if continued, will result in an outage. Using AIOps’ automated data-driven analysis, IT teams can then provide recommendations for avoiding that outage and, ultimately, correct the problem without dozens of hours of human involvement or costly service disruptions. These capabilities can dramatically lighten the workload of IT teams who are already stretched thin.
In addition, AIOps can deliver the insights required to support more stable, highly available customer-facing services. Organisations can prioritise the elimination of application and infrastructure faults based on their impact on stability. The result is often an improved user satisfaction, better long-term customer retention, and higher revenues.
The future of AIOps
As organisations embrace AIOps, capabilities will continue to evolve. AIOps and automation are expected to unlock benefits for organisations such as:
- Enhanced prescriptive and predictive functionality: The ability to mine more datacentres for patterns with ML will provide more actionable insights and new proactive capabilities. Contextualising machine data with incident, problem, change, and knowledge-based data from humans or the infrastructure sets the stage for self-healing organisations.
- More effective security analytics: Organisations are already contextualising data to detect application and infrastructure anomalies. The next step is to spot anomalous user behaviour. The average cost of a corporate data breach is $3.9m. Security analytics are a compelling capability for organisations that do not have a complete security information and event management (SIEM) solution.
- Superior employee experience: In today’s talent-driven economy, organisations are focusing on measuring the employee experience to boost retention and productivity. The right application of technology can help them determine how happy employees are with their applications, and which tools are most effective. End-user experience management capabilities will increasingly become commodity capabilities.
Today more than ever, AIOps has the potential to help mission-critical IT departments weather remote work and digital business transactions. Modern IT operations teams are facing new challenges in 2021, but at least testing the waters of AIOps capabilities comes with little immediate risk and many potential rewards.