Of the four key elements, the most critical is open data access.  Challenges:

• Core IT will always have multiple technologies and systems of record from different vendors. These will also vary across IT disciplines.
• Freeing data from its organizational silos for big data aggregation and analysis is perhaps the most difficult challenge facing IT teams trying to implement AIOps.

An AIOps big data platform must also support responsive ad-hoc data exploration and deep queries. Big data technologies, originally created to handle large data lakes from data warehouses, have rapidly evolved into not just scalable but responsive data manipulation engines that can meet the needs of AIOps. Challenges:

• Digital transformation means high volumes of rapidly changing IT data.
• Traditional relational data warehouses are neither scalable nor responsive enough to support the quantity and speed of digital data.

Solution:

• AIOps represents the unification of deep data research and online, real-time analytics to elevate IT decision making.
• Analysis needs to take place in real-time on data as it comes in – not only offline, but whenever resources are available.

AIOps enables IT to move from rule-based, human management of analysis to machine-assisted analysis and machine learning systems. This is required not only because of limits to the amount and complexity of analysis human agents can achieve, but also to enable a level of change adaptation that hasn’t been possible.

• Pattern matching - Machine learning applies the computational power and speed of machines to the discovery and correlation of patterns in IT data.
• IT systems, users and ecosystems exhibit behaviors and relationships that can point to root causes, isolate issues, and indicate future problems.
• It does this more and faster than human agents and dynamically changes the algorithms used by analytics based on changes in the data.

AIOps should be applied by the system automatically based on the data, without the need for user intervention and decision.
Delivering machine-assisted analytics at scale on high volumes of digital IT data is useless if the outcomes still require human intervention.

• AIOps connects and drives automation in the hyper-complex, multi-source cloud environment.
• AIOps can generate workflows and measure the effects of those processes, feeding the results back into the system as data to be analyzed and learned from.

Event Automation 
Stop chasing routine events—automate resolution 
High volumes of system, network, and application events can bog down your operations team with recurring problems.

• Automate the resolution of recurring events that have standard remediation processes.
• TrueSight Orchestration works with TrueSight Operations Management and other event management solutions to take IT Operations from incident response to automated, proactive problem management.
• Get a holistic view into the health and security of your IT infrastructure including security events
• Validate an event or fault, create an incident and change ticket, automatically execute remediation, and close out change record

Deliver IT services faster, without manual touch 
Organizations are modernizing their service desk operations with mobile access and newer web interfaces. However, each call to the service desk requires human interaction, even for routine, repeatable tasks

• TrueSight Orchestration works with Remedy Service Management and other service desks to automate fulfillment of self-service requests and save money, time by automating manual service desk processes
• Shift from costly Level 1 and Level 2 support to self-service automated fulfillment, such as for account unlock, password reset, access to systems and applications, and employee onboarding
• Integrate with leading service management software for process approval and compliance
• Improve quality of service and customer satisfaction with consistent results

• Service-aware: Manage infrastructure components and communicate with business stakeholders based on their apps and services
• Analytics-driven: Accelerate real-time insights using machine learning and algorithms optimized for IT Ops, and reduce the need for data scientists
• Task and process automation: Make the most of current staff and accelerate standard process workflows using industry-leading IT Process Automation
• Data center: Consolidate tooling and manage the scale of traditional data centers supporting legacy applications and the latest custom app platforms.
• IaaS: Optimize server, network, and storage capacity before migrating app workloads to public cloud IaaS, then manage those workloads using the same tools you use on-premises.
• Cloud native: Optimize cloud spend and ensure the safe configuration of services, containers, and applications built natively on AWS, Azure, and GCP.

Enterprise-class service management must combine high levels of automation and integration with the ease of intuitive self-service to enable the breakthroughs in productivity that help you compete and win.

With Remedy Service Management you can:

• Enable your Service Desk to be 75% more productive with formless ticket entry
• Ensure essential task coverage including incident and problem management, change and release management, knowledge management, asset management, and mobile self-service
• Use social and collaboration tools to provide context-aware insights to help IT work smarter. Stunning reports and visualizations allow intuitive exploration of data.
• Integrate with IT operations management tools to reduce incident volume and speed problem resolution
• Embedded ITIL® v3 processes, with best practice reports and KPIs, available out-of-the-box
• Helix Multi-Cloud Service Management provides a seamless service experience across multi-cloud environments
• Cognitive capabilities transform the agent experience
• Container deployment lets you run Helix Remedy on any type of public cloud
• Native mobile apps let you use the full power of Remedy anywhere