Find out what your peers are saying about Zabbix, Datadog, Microsoft and others in Cloud Monitoring Software.
The return on investment is huge and unmatched, as the devices are not expensive and are highly beneficial for day-to-day business operations.
The support quality needs improvement, particularly in terms of reachability and response time after the merger.
The issues were mainly related to response time.
I would rate scalability at nine out of ten.
In terms of scalability, Mist AI and Cloud is scalable.
Mist AI and Cloud is stable, and I would rate its stability as eight out of ten.
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.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
There should be a clearer view of the expenses.
Since the merger or integration between Mist AI and Cloud and HP, it has affected service quality negatively.
If Juniper or Mist can enhance the management of third-party devices, it would make sense, as the current functionalities offer limited insight compared to managing Juniper or Mist devices.
From a Juniper perspective, there is a need for further improvements in the SRX and the given solution area.
The setup cost for Datadog is more than $100.
Mist AI and Cloud is not an expensive tool and is very competitive.
Compared with other solutions, Mist AI and Cloud is not that expensive and is considered moderate in pricing.
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.
The technology itself is generally very useful.
Mist AI and Cloud's orchestration is beneficial for troubleshooting and proactive analysis, offering proactive solutions before issues arise.
The AI-driven automation, like Mist, assists the network manager and operation manager in troubleshooting the wireless network by identifying signal issues and offering timely assistance.
Juniper doesn't have a wireless LAN controller; they used to have it in the past, but recently everything about Juniper wireless LAN is on Mist AI.
Product | Market Share (%) |
---|---|
Datadog | 8.8% |
Zabbix | 15.5% |
Checkmk | 5.5% |
Other | 70.2% |
Product | Market Share (%) |
---|---|
Mist AI and Cloud | 1.7% |
Aruba Wireless | 15.7% |
Ruckus Wireless | 14.0% |
Other | 68.6% |
Company Size | Count |
---|---|
Small Business | 78 |
Midsize Enterprise | 42 |
Large Enterprise | 82 |
Company Size | Count |
---|---|
Small Business | 9 |
Midsize Enterprise | 7 |
Large Enterprise | 8 |
Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.
Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.
What are the key features of Datadog?
What benefits and ROI should users look for in reviews?
Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's requirements.
Mist AI uses a combination of artificial intelligence, machine learning, and data science techniques to optimize user experiences and simplify operations across the wireless access, wired access, and SD-WAN domains.
Data is ingested from numerous sources, including Juniper Mist Access Points, Switches, Session Smart Routers, and Firewalls for end-to-end insight into user experiences. These devices work in concert with Mist AI to optimize user experiences from client-to-cloud, including automated event correlation, root cause identification, Self-Driving Network™ operations, network assurance, proactive anomaly detection, and more.
Juniper also leverages Mist AI for next-generation customer support. It is the foundational element behind Marvis, the industry’s first AI-driven Virtual Network Assistant, which provides extensive insight and guidance to IT staff via a natural language conversational interface.
With Mist AI, operators save time and money with faster problem resolution and fewer onsite visits. Users benefit from a network infrastructure that is more predictable, reliable, and measurable.
We monitor all Cloud Monitoring Software reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.