

OpenText AI Operations Management and IBM Turbonomic compete in the AI operations domain. OpenText excels in cost optimization and scalability, while IBM Turbonomic gains an edge with its automation and right-sizing capabilities, enhancing VM performance.
Features: OpenText AI Operations Management consolidates multiple monitoring teams into a single dashboard, providing efficient event correlation and reducing manual IT tasks. Its comprehensive data integration stands out. IBM Turbonomic focuses on forecasting, automating VM placement, and offering detailed resource optimization, aiding in efficient workload adjustments and real-time performance visibility.
Room for Improvement: OpenText could enhance its scalability, simplify its architecture, and revise its licensing model. IBM Turbonomic should improve its user interface, fully transition to HTML5, and broaden its reporting capabilities.
Ease of Deployment and Customer Service: OpenText is deployed primarily on-premises and in hybrid clouds with robust customer service, though technical support can be location-dependent. IBM Turbonomic supports flexible private and public cloud deployments, but offshore support quality needs enhancement.
Pricing and ROI: OpenText's setup costs might be high, but it offers substantial ROI through task automation, though its licensing is complex. IBM Turbonomic's pricing is aligned with virtual environment consumption, providing attractive ROI via resource management and automation. Both products promise operational savings with distinct pricing models.
OpenText goes out to bring the right people to answer any inquiries I have.
My team works with the customer success team for technical support and customer service for OpenText AI Operations Management.
The stability and scalability depend on architectural considerations and the company's specific situation.
We are following approximately 10,000 metrics and logs, and the platform performs pretty well.
You need to see the big picture and understand what the customer's pain points are to find the right tuning.
Splunk is more business-friendly due to its prettier interface.
With its automation capabilities and runbooks, it reduces after-hours costs by automatically handling recurring issues and known scenarios.
This integration ensures that when monitoring systems alert and subsequently resolve, tickets are automatically created and closed.
We have a platform where we are collecting metrics, logs, and traces for OpenText AI Operations Management, and if there is an anomaly, we directly open a ticket in our ITSM system.
| Product | Market Share (%) |
|---|---|
| IBM Turbonomic | 1.9% |
| OpenText AI Operations Management | 4.0% |
| Other | 94.1% |

| Company Size | Count |
|---|---|
| Small Business | 41 |
| Midsize Enterprise | 57 |
| Large Enterprise | 147 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 7 |
| Large Enterprise | 35 |
IBM Turbonomic offers automation, planning, and right-sizing recommendations to streamline resource management, improve efficiencies, and optimize costs across virtualized environments and cloud platforms.
IBM Turbonomic is valued for its capability to optimize resource allocation and monitor virtual environments efficiently. It facilitates automated decision-making in VM sizing, load balancing, and cost optimization for both on-premises and cloud deployments. Users can leverage insights for workload placement, ensure peak performance assurance, and effectively right-size across VMware and Azure. The ongoing transition to HTML5 aims to improve visual and navigational ease, while expanded reporting features are anticipated. Opportunities for improved training, documentation, and integrations enhance platform usability and functionality.
What Are the Key Features?In finance, IBM Turbonomic aids in maintaining platform efficiency during market fluctuations. Healthcare organizations leverage its capability for resource optimization during high-demand periods to enhance patient care support. Retailers use it for planning in peak seasons, ensuring resources align with fluctuating demand to maintain performance continuity.
OpenText AI Operations Management centralizes event correlation and monitoring across infrastructures, prioritizing scalability and automation for efficient alert management. It empowers organizations with transparency and insights essential for effective IT resource management in hybrid cloud environments.
OpenText AI Operations Management offers comprehensive solutions for event correlation, integration, and centralized alert management. With capabilities that streamline operations, this tool supports efficient IT management across AWS, GCP, and on-premises environments. Despite requiring improvements in performance and usability, its robust reporting and seamless monitoring provide valuable insights for root cause analysis. Users leverage this platform to integrate event data, automate incidents, and manage hybrid infrastructures effectively, making it a key component in enhancing service perspectives globally. Its heavy architecture and reliance on Java and Flash, coupled with complex licensing and pricing, necessitate attention to functionality and support areas.
What are the key features of OpenText AI Operations Management?OpenText AI Operations Management is widely implemented in industries requiring comprehensive monitoring capabilities. Organizations benefit from its ability to consolidate tools and manage events effectively across hybrid environments. The integration of incident automation and performance evaluation tools is particularly beneficial for those looking to enhance compliance support and reduce response times. Despite some challenges, the platform remains a valuable asset in managing complex IT environments and improving operational effectiveness.
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