Datadog and Cisco UCS Manager are prominent players in system monitoring and management. Datadog seems to have the upper hand in cloud-based environments with its extensive integrations and ease of use, while Cisco UCS Manager is well-suited for managing physical infrastructure with its flexibility in hardware configurations.
Features: Datadog is known for its seamless integrations with over 300 platforms, intuitive tag usage, and comprehensive metrics and dashboards that enhance alert creation and monitor visibility. The product allows users to perform monitoring actions easily, like creating monitors from metrics. Its ecosystem includes integration with services such as Amazon ECS and Slack. Meanwhile, Cisco UCS Manager focuses on centralized management and configuration capabilities for physical infrastructure. It facilitates flexibility in creating hardware profiles and integrates effectively with network and storage systems.
Room for Improvement: Datadog users suggest improvements in dashboard customization and desire more stability in newer features. There is also a need for better pricing transparency and responsive technical support, as well as consistent APIs. For Cisco UCS Manager, the complexity of its interface is a notable concern. There is room to improve automation, as well as scalability and performance monitoring features.
Ease of Deployment and Customer Service: Datadog excels in public and hybrid cloud deployments, with generally well-regarded customer support, though responsiveness varies. Cisco UCS Manager serves primarily on-premises deployments. Its customer support is praised, but the training and setup processes can add complexity.
Pricing and ROI: Datadog's pricing, which fluctuates based on data usage and additional features, is often seen as expensive but justified by its observability capabilities. In contrast, Cisco UCS Manager's pricing is influenced by its hardware dependency, and although higher than some competitors, it is justified by perceived reliability and discounts. Both products are valued for enhancing operational efficiency and visibility despite differences in environment preferences and cost structures.
There's no need for an extra management device or virtual machine, as everything runs within the fabric interconnect.
Cisco UCS Manager provides cost savings by reducing the time support staff spend on long deployments.
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.
For a severity one case, a call ensures immediate assistance and resolution of the matter.
With Intersight, service requests are automatically generated, enhancing the user experience and providing timely resolutions.
Regarding Cisco tech, they are pretty good.
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.
Adding new chassis and extra blades is streamlined.
I would rate the scalability at nine out of ten, probably.
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.
If there's a really complex problem, I would probably give it a ten since it gets escalated quickly.
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.
These incidents are related to log service, indexes, and metric capturing issues.
We would benefit from advancements in AI that offer firmware recommendations automatically, reducing the need for human intervention and vendor communication.
It doesn't work straight out of the UCS, so someone who knows what they're doing is needed immediately, and it can be quite confusing.
While it has been improved from using Java to HTML, simplifying the tabs would enhance user experience.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
Recently, we acquired an excellent bundle with significant discounts, with offers like buying three servers and getting one free, along with UCSC and fabric included for free.
As long as they can afford it, there is a setup cost involved.
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.
It supports ease of deployment, allowing for quick mass deployments in the data center, saving time and resources by doing so from a remote location.
Whenever there's a failure of any component, it's very easy to swap because you just disassociate that profile, remove the faulty blade, connect the new blade, and associate that profile, maintaining the same MAC address and worldwide port name.
One of the valuable features is the user interface base, specifically the C user interface.
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.
| Product | Market Share (%) |
|---|---|
| Datadog | 5.0% |
| Cisco UCS Manager | 1.2% |
| Other | 93.8% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 3 |
| Large Enterprise | 18 |
| Company Size | Count |
|---|---|
| Small Business | 80 |
| Midsize Enterprise | 46 |
| Large Enterprise | 94 |
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.
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