

Datadog and OpenText AI Operations Management compete in the IT operations management space. Datadog appears to have an advantage with its extensive integrations and user-friendly interface, making monitoring intuitive for users.
Features:Datadog stands out for its extensive integrations, intuitive monitoring capabilities, and user-friendly dashboards, which ease metric visualization and alert configuration. It also offers over 300 monitors, a strong API ecosystem, seamless integrations with platforms like AWS and Docker, and a hosted infrastructure that eliminates management burdens. OpenText AI Operations Management is recognized for efficiently integrating various data sources to provide a comprehensive view of IT operations. Its automation capabilities effectively manage large alert volumes, which is particularly valued by users.
Room for Improvement:Datadog requires refinement in pricing transparency and cost control, as users note unexpected expenses with logs and new features. Enhancements in real-time usage metrics and customer support responsiveness would be beneficial. OpenText AI Operations Management users would benefit from improvements in its visual design and user-friendliness. Enhancing AI integration for predictive analytics is suggested as an area of growth.
Ease of Deployment and Customer Service:Datadog offers versatile deployment options across private, public, and hybrid cloud environments. It generally provides robust customer service, although responsiveness varies in complex scenarios. OpenText AI Operations Management targets primarily on-premises and hybrid cloud setups. It is well-regarded for high-quality technical support, although initial deployment may be complex and configuration-intensive.
Pricing and ROI:Datadog has a modular pricing model that can be costly without careful management, potentially leading to unexpected costs. Its investment is often justified by improved visibility and operational efficiency. OpenText AI Operations Management, although seen as expensive, offers flexible module-based pricing. Its automation features significantly reduce operational costs, providing good ROI by easing manual processes.
Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five.
Datadog has delivered more than its value through reduced downtime, faster recovery, and infrastructure optimization.
I believe features that would provide a lot of time savings, just enabling you to really narrow down and filter the type of frustration or user interaction that you're looking for.
When I have additional questions, the ticket is updated with actual recommendations or suggestions pointing me in the correct direction.
Overall, the entire Datadog comprehensive experience of support, onboarding, getting everything in there, and having a good line of feedback has been exceptional.
I've had a couple instances where I reached out to Datadog's support team, and they have been really super helpful and very kind, even reaching back out after resolving my issues to check if everything's going well.
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.
Datadog's scalability has been great as it has been able to grow with our needs.
We did, as a trial, engage the AWS integration, and immediately it found all of our AWS resources and presented them to us.
Datadog's scalability is strong; we've continued to significantly grow our software, and there are processes in place to ensure that as new servers, realms, and environments are introduced, we're able to include them all in Datadog without noticing any performance issues.
The stability and scalability depend on architectural considerations and the company's specific situation.
Datadog is very stable, as there hasn't been any downtime or issues since I've been here, and it's always on time.
Datadog seems stable in my experience without any downtime or reliability issues.
Datadog seems to be more stable, and I really want to have a complete demo before making a call to decide on this.
We are following approximately 10,000 metrics and logs, and the platform performs pretty well.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
We want to be able to customize the cost part, and we would appreciate more granular access control.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
Normally, predictive features can be more useful, but this is an end-to-end solution that needs to be customized.
Splunk is more business-friendly due to its prettier interface.
The setup cost for Datadog is more than $100.
Everybody wants the agent installed, but we only have so many dollars to spread across, so it's been difficult for me to prioritize who will benefit from Datadog at this time.
My experience with pricing, setup cost, and licensing is that it is really expensive.
From a cost perspective, OpenText Operations Bridge is cost-effective as it saves us man hours.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
Having all that associated analytics helps me in troubleshooting by not having to bounce around to other tools, which saves me a lot of time.
Datadog was able to find the alerts and trigger to notify our team in a very prompt manner before it got worse, allowing us to promptly adjust and remediate the situation in time.
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 (%) |
|---|---|
| Datadog | 6.7% |
| OpenText AI Operations Management | 0.9% |
| Other | 92.4% |

| Company Size | Count |
|---|---|
| Small Business | 80 |
| Midsize Enterprise | 46 |
| Large Enterprise | 99 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 7 |
| Large Enterprise | 35 |
Datadog integrates extensive monitoring solutions with features like customizable dashboards and real-time alerting, supporting efficient system management. Its seamless integration capabilities with tools like AWS and Slack make it a critical part of cloud infrastructure monitoring.
Datadog offers centralized logging and monitoring, making troubleshooting fast and efficient. It facilitates performance tracking in cloud environments such as AWS and Azure, utilizing tools like EC2 and APM for service management. Custom metrics and alerts improve the ability to respond to issues swiftly, while real-time tools enhance system responsiveness. However, users express the need for improved query performance, a more intuitive UI, and increased integration capabilities. Concerns about the pricing model's complexity have led to calls for greater transparency and control, and additional advanced customization options are sought. Datadog's implementation requires attention to these aspects, with enhanced documentation and onboarding recommended to reduce the learning curve.
What are Datadog's Key Features?In industries like finance and technology, Datadog is implemented for its monitoring capabilities across cloud architectures. Its ability to aggregate logs and provide a unified view enhances reliability in environments demanding high performance. By leveraging real-time insights and integration with platforms like AWS and Azure, organizations in these sectors efficiently manage their cloud infrastructures, ensuring optimal performance and proactive issue resolution.
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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