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Transform management of your cloud operations

In our digital age, delivering an exceptional user experience is paramount. CGI SiteReliability360, deeply integrated with artificial intelligence (AI) and machine learning capabilities, excels in ensuring reliability through cloud-agnostic deployments and continuous monitoring to maintain stringent service level objectives (SLOs). The union of AI and cognitive technology provides a solid foundation for elevating user satisfaction, ensuring unwavering reliability and offering unparalleled efficiency in IT cloud operations management.

CGI SiteReliability360 leverages cognitive automation for efficient operations management and proactively addresses anomalies through auto-healing. It also optimizes role-based access, enables comprehensive telemetry, monitors resource utilization and manages costs effectively through a multi-tenant governance layer.

CGI SiteReliability360 is built on the principles of site reliability engineering (SRE) and includes features that empower engineers and application teams to simplify the complexities of a hybrid IT infrastructure.

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Decoupling of application blueprints from underlying infrastructure

A cloud-agnostic visual blueprint of the platform, such as web servers, app servers, and databases, performs the provisioning and configuration of the entire application stack across any private or public cloud.

Deployment innovation

Create reliable cloud-agnostic deployments of applications on any underlying cloud, in high-availability mode, without a single line of script. The platform follows Topology and Orchestration Specification for Cloud Applications (TOSCA) standards, enabling seamless interoperability between similar platforms.

Precise configuration management database mapping

Isolate issues quickly through a built-in service model mapped in the configuration database to maintain updated records.

Smart event management and automated processes

Utilize advanced machine learning models for efficient incident management. CGI SiteReliability360 aggregates, filters, deduplicates and correlates events from multiple sources into a single console to reduce manual effort and enable self-healing for streamlined incident resolution.

Intelligent auto-scale, auto-heal and auto-replace

AI-powered "right-sizing" reports, suggest compute scaling and automatically heal and replace "unhealthy" objects if auto-healing attempts fail.

Business and IT process automation

Runbook automation workflows automate repetitive and mundane processes to reduce effort and apply cognitively triggered last-mile handlers or workflows to automatically perform corrective actions.

Multi-cloud management

Manage cloud resources with consistency and security using a multi-use, intra-operable environment and cloud-agnostic high-level and low-level designs.

DevOps and DevSecOps

Facilitate seamless DevOps and support quick and reliable building, testing and application releases, while integrating security practices in every step of the process to safely distribute security decisions at speed and scale.

Predictive self-healing

Leverage AI, machine learning and predictive self-healing to diagnose, isolate and resolve errors, optimize systems and application availability, and mitigate the impact of application and infrastructure failures.

Benefits of CGI SiteReliability360

CGI SiteReliability360 harnesses the power of AI and machine learning to streamline IT asset management, event correlation and automation to offer a host of benefits, including:

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  • Improving productivity by bridging the gap between development and operations teams
  • Automating repetitive processes to reduce effort and improve automation maturity by leveraging the automation marketplace
  • Enabling hybrid cloud management and support
  • Enabling recommended workflows and self-healing through AI-powered intelligence
  • Facilitating AI-driven predictive analytics for proactive issue resolution to prevent downtime
  • Proactively monitoring and analyzing application availability, capacity and performance
  • Tracking clients’ service level objectives (SLOs)
  • Categorizing, suppressing and prioritizing alerts intelligently through machine learning algorithms to reduce alert fatigue
  • Maximizing rich telemetry and diagnostics
  • Facilitating seamless integration of DevOps and DevSecOps