Overview of AI in IT Infrastructure ManagementWith the growth in technology and infrastructure, rapid advancements are there in software-defined infrastructure and Cloud Computing. This has enabled the IT Infrastructure to be flexible, intangible and on-demand. On the other hand, IT Infrastructure is not yet intelligent enough to understand the correlation between the IT elements, recognizing the data trends and further take the appropriate decisions. Therefore, Artificial Intelligence is introduced. It enables to access and manage the computing resources to train, test and deploy AI algorithms.
AI is all about making computers think like humans with customer interaction solutions. Taken From Article, Artificial Intelligence Adoption Best Practices
What are the Challenges for building AI Enabled IT Infrastructure?
The below highlighted are the major challenges of building Artificial Intelligence enabled IT Infrastructure.
- Organize the data into logical partition applications and services.
- Mapping the data into correct source types.
- Reviewing the parsing process.
Personalize Artificial Intelligence
User Experience Alerts
- Perform Anomaly detection.
- Use the discovered anomalies and previous domain existing knowledge to create custom alerts based on factors affecting the customer’s experiences.
Customize DashboardsMeaningful and iterative dashboards to monitor the IT stack.
Measuring employee performance and the hiring process also plays a vital role in identifying the right person for the right job.Taken From Article, AI Platform for HR and Recruitment Management
Technologies for Building AI-based IT Infrastructure Platform
The main technologies which are necessary for building AI based IT infrastructure platform are below:
Data SourcesDiverse and extensive data sources are used such as events, metrics, logs, different job data, tickets, monitoring, etc.
Big DataAggregation of IT data for historical analysis and real-time reaction and insights.
Computation and AnalyticsEnable to generate the new data and metadata from given existing IT data.
- Eliminate noise
- Identification of patterns and noise
- Isolate probable causes
- Expose underlying problems
Artificial Intelligence AlgorithmsApply computation and algorithms efficiently and appropriately to expertise the machine and get desired outcomes.
Unsupervised Machine Learning
- Automatic alteration and creation of new algorithms based on the output of the algorithmic analysis.
- Introduction of new data into the system
VisualizationPresenting insights and recommendations in an easily consumable way.
Automation with Artificial IntelligenceAutomatic identification of issues with the use of outcomes obtained from analytics and machine learning .
A new label for the tools that took machine learning capabilities and applied them to IT Operations space.Taken From Article, AIOps: Artificial Intelligence for IT Operations
AI-based Methods to Influence the IT Infrastructure Automation
The various AI based methods to influence the IT infrastructure automation and management are defined below:
Capacity PlanningWith the use of AI, the workload can be mapped to the right configuration of servers and virtual machines.
- With the combination of AI, it becomes possible for the system to predict the scaling in which the infrastructure will automatically adjust itself based on historical data.
- No rules and configurations are required to enable elasticity.
- Storage resources are monitored continuously for optimum utilization and performance.
- By predictive analytics, the capacity of storage is automatically adjusted by adding new volumes proactively.
- Advanced machine learning algorithms are used to determine outliers effectively.
- Real-Time root cause analysis.
- Prevention of potential outages and disruptions faced by the infrastructure.
Threat Detection and AnalysisWith the use of application of machine learning algorithms and heuristics, anomalies and risk events can be detected and avoided.
Impact of Artificial Intelligence on Information Management Services
- The demand for greater resources
- The necessity for AI in security
- Intelligent Monitoring
- Automated Support
- Intelligent Storage
- AI-defined Infrastructure Management
Infrastructure services ensure the plans, designs, and implement organizational IT strategies and manage mission-critical IT infrastructure.Taken From Article, IT Infrastructure Management Services
Key Features of AIOps
The Key feature of AIOps are listed below;
- Automated behavior prediction
- Root cause analysis
- Data-driven recommendations
- Digital Transformation
- Faster Deployment
- Deploy automated actions for known events with embedded business logic.
- Increase the speed of monitoring and performance issues.
- Real-Time Analysis
- Real-time analysis and diagnosis of issues using various algorithms.
- Perform actionable insights.
- Alerts and Notifications
- DevOps and CloudOps Automation
- Automatic monitoring the deployment of metrics.
- Quickly invoke the issue detection rollbacks.
What are the Key Components of AIOps Platform?
- Monitoring Ecosystem
- Engagement Ecosystem
- System of Record
- System of Automation
- Data Lake
- Artificial Intelligence
- Time Series Database
- Time Series Analysis
Artificial Intelligence for IT Infrastructure Use Cases
Use Cases for Artificial Intelligence in IT Infrastructure:
Artificial Intelligence for Incident management
- Web-scale globalized infrastructure
- Hybrid clouds
- Heterogeneous technology stacks
- More than ten monitoring tools
Challenges for Incident management
- Managing the web-scale and hybrid cloud infrastructure
- Managing millions of events per month
- Event Analysis and Correlation
Solutions for Incident management
- Real-time Machine Learning Algorithms
- Operational Noise Reduction
- Advanced Event Correlation
Managing and Monitoring the IT Ecosystem
Challenges for managing and monitoring the IT Ecosystem
- Lack of multi-tenancy for domain experts
- Operational Noise and alert fatigue
- Thousands of tickets per month
Solutions for managing and monitoring the IT Ecosystem
- Automatically catch million of events
- Automatic dispatch the hundred of solutions to the right experts without dependency on rules and topology of models.
- Automate ticket generation
- Kubernetes and Amazon Web Services
- Smarter Architecture-Elegant Architecture
- Central Data Collection and Analytics Engine
- Optimize the distribution of servers automatically across the entire infrastructure
- Automatic determination of correlation from the wide variety of sources along with infrastructure information
Cost ReportsReal-time Cost Analysis
Prediction of Issues
- Automatic identification of issues that can impact the business.
- Pattern detection to predict and prevent business outages, increase revenues, improve customer satisfaction, and provide business agility.
- Dynamic threshold and multivariate anomaly detection.
- Prediction of resources that will run out of capacity.
A Cognitive Approach
To know more about Artificial Intelligence Solutions offerings for Infrastructure Industry we advise taking the below mentioned step-