Predicting Issues, Proactive Remediation


With highly scalable infrastructure and on-demand resource acquisition, it is easier than ever to build a massive cloud IT network, infrastructure and systems. The complexity of managing such IT assets increases and visibility becomes a problem with distributed multi-cloud resources, requiring holistic monitoring solutions for full visibility.

Lack of predictive insight also reduces operational agility, increasing the likelihood of an outage due to increased mean time to acknowledge (MTTA) and mean time to remediation (MTTR).

To overcome these challenges, enterprises need the assistance of innovative technologies such as AIOps, (Artificial Intelligence for IT Operations).

AIOps is augmenting existing ITOM (IT Operations Management) processes and workflows with artificial intelligence, helping streamline the administration and maintenance of cloud infrastructure.

Predicting Issues, Proactive Remediation

Our AIOps Capabilities


Trianz’s AIOps service offering provides predictive analytics capabilities to IT operations by leveraging big data, machine learning to analyze super large volumes of structured and unstructured data.

Our technology competencies and partnerships cuts across core infrastructure monitoring, application performance monitoring, network monitoring, log analytics, event management and AIOps. Expertise across a best-in-breed technology stack along with understanding of business use cases for AIOps implementation is required for a successful rollout.

 

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Our Approach for AIOps


Trianz has been at the forefront of rolling out AIOps solutions to our clients. Our experience across engagements has resulted in ready-to-use frameworks to ingest almost any kind of data from any source, enabling:

  • Analysis of real-time and historical content

  • Application of bleeding edge AI and ML capabilities

  • Anomaly detection

  • Predictive analytics generation

  • Faster root-cause determination

The AIOPs Platform relies on large system-level datasets to operate, using logs and network events to manage your infrastructure proactively. This enables the automation of ITOM processes, paving the way for adaptive and self-healing cloud IT networks.

 

digital transformation

Copyright © 2022 Trianz

Our Solutions Offerings for AIOps


AIOps Strategy and Roadmap

AIOps Strategy and Roadmap

  • Problem definition and defining AIOps vision and goal

  • Assessing current state with respect to process, technology and tools

  • Developing AIOps strategy and roadmap for implementation

  • Creating a blueprint for future state AIOps Architecture

  • Defining KPIs and CSFs to measure success

AIOps Proof of Value Implementation

AIOps Proof of Value Implementation

  • Use case analysis and finalization

  • Technology investigations and final AIOps solutions

  • AIOps Architecture Blueprint

  • Data source analysis (incident, monitoring and event data)

  • Proof of Value(PoV) use-case implementation

  • Review of results

Enterprise Level Scaling

Enterprise Level Scaling

  • Phased deployment of scalable architecture

  • Scaling PoV Use Cases and development of additional use cases

  • Integration and automation across impacted ITOps platforms

  • Continuous ops and continuous deployments

Operations

Operations

  • Governance programs

  • Automated security monitoring

  • End-to-End process automation

Delivering the Next Gen Modernized IT Operations Platform


Assured Service

Assured Service

  • Increased business application assurance and uptime

  • Reduced Mean-Time-to-Detect (MTTD) and Mean Time-to-Repair (MTTR)

Automation

Automation

  • Intelligent automations to proactively detect and fix issues based on machine learning algorithms

  • Proactive and data driven IT Operations reduces client impacting Incidents and event noise

Optimization

Optimization

  • End-to-end view of business services health including network, servers, databases and applications.

  • Optimize resources to enable IT operations to become a proactive source of innovation.

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