Share your experience using CloudFabrix Software

Our main use case for Datadog is that we heavily rely on it for our infrastructure monitoring and application monitoring, including some of the browser-based application monitoring, which is RUM.

A specific example of how we use Datadog for monitoring is that we monitor our infrastructure CPU and memory utilization. Sometimes we see slowness and figure out CPU utilization was near the threshold, around 90-95%, which helped us to resolve the issue, underlying SQL problem, and that helped us to troubleshoot the issue.

In addition to our main use case, we also use RUM monitoring and synthetic monitoring, which really help us to look at our end-user sessions and proactively solve any slowness or errors spiking up.

The best feature that Datadog offers is infrastructure monitoring, where it can look at the CPU utilization, different process utilization, all the processes which are running, and alert us in advance if things are going beyond normal threshold.

I think everything about the features of Datadog is amazing. Datadog provides details up to the transactions. We can look at the transaction log too for the application, which is really helpful.

Datadog has impacted our organization positively since we were previously using AppDynamics and then we switched to Datadog. It has improved a lot in our alerting and monitoring in the infrastructure space and application space. We can monitor business transactions and take proactive action. It is really great to take actions on the issues before an end user reports it, which is a great advantage for us.

The world is moving toward artificial intelligence, so maybe we can have an inbuilt AI agent within Datadog, or maybe it exists and I have not used it.

The AI aspect would be great where we would not need to go and look at different transactions or different modules of Datadog, as AI can actually provide the data to us on Datadog UI. If we need more details, it could have a link to go to that specific module to look at more details for the application and infrastructure monitoring and alerts.

I have been using Datadog for three years now.

Datadog is stable for our organization, and we have not seen any downtime or issues so far.

Datadog's scalability has been great as it has been able to grow with our needs. As per our need, we are able to utilize different modules and there was never any need where we needed to scale anything else. We have limited our transition recording to 45 days, which helps. That is what our need is. It is really helpful and nothing additional is needed.

We reached out to Datadog only once to find out our AMI images, which we needed for our infrastructure as a code component, and it was a great experience. We got the required information and that helped us.

Neutral

Before Datadog, we previously used OpsRamp and also AppDynamics, and both of the tools we retired and moved to Datadog due to our enterprise approach to consolidate overall monitoring to Datadog.

I gave Datadog a nine out of ten because it is amazing. All the features and functionalities are amazing. The ease of implementation was a bit difficult for us for the database servers where we have different kinds of databases. We needed different kinds of agents to be installed, and that was a bit tricky for us. I think it is not on Datadog but it is about our complex infrastructure where we have a different set of infrastructure in place, so that created a bit of trouble during the implementation.

Since using Datadog, we have seen a return on investment with a lot of savings around infrastructure monitoring, and also on the people needed to monitor overall application and infrastructure on both sides. Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five. That is a huge saving.

We did not evaluate other options before choosing Datadog, we went with Datadog directly.

My advice for others looking into using Datadog is to keep exploring the tool and utilize the different modules and the different functionalities of features Datadog offers. There are multiple features and functionalities available with the Datadog agents which are really helpful and powerful to troubleshoot, alert, and monitor both applications and infrastructure.

So far, all the features I have used in Datadog are amazing. It captures all the logging information which I have, and I can include the links of Datadog transactions on my Splunk logs. It is integrated with Splunk and other platforms, which is great.

On a scale of one to ten, I rate Datadog a nine.

Incident management is streamlined with Moogsoft. One standout feature is its unique situation-creation capability, differentiating it from other fault management tools. While other tools typically convert alarms directly into tickets or incidents, Moogsoft adds a middle layer where multiple alarms can be aggregated into one incident. Moogsoft's strong AI capabilities also allow it to correlate similar alarms automatically based on past experiences.

The solution comes with a collaboration feature. This feature allows team members to communicate and work together on various issues. If there are ten incidents, then ten chats will be open.

The solution comes with features like PRC, designed to streamline alarm flow, reduce noise, and prevent alarm flooding. These features are particularly beneficial when used with a basic understanding of network operations. It has a time-based algorithm that continuously learns from alarm flows. When the alarm flow reaches a certain limit, it collects all alarms together based on historical data. This is particularly useful during major events such as power outages, where alarms could flood. In such cases, the product activates to hold all alarms for a certain period, anticipating a fluctuation rather than immediately triggering the alert manager.

The tool needs to improve its support. It appears that the support responsiveness from Moogsoft is not aligned with the severity of the incident. Instead of proactively addressing issues, customers have to chase Moogsoft for resolution. In Moogsoft, unlike other tools like Splunk, the process follows a step-by-step sequence. You need to start each process in a specific order, typically following a sequence. 

I have been working with the solution for five years. 

The tool is scalable. About 70 customers were able to run on the tool's single instance. My company has customers spread across various industries, including FMCG, and  hospitality. 

I have used Netcool and Splunk before, and each tool has its own capabilities, advantages, and disadvantages. Splunk is great for heavy data processing, while Moogsoft excels in integrating with various tools through intelligent plugins. With Moogsoft, you install the plugin and provide basic login credentials for integration. Every tool has its unique strengths and experiences. There's no situation where Moogsoft can do something that other tools can't, or vice versa. For example, Moogsoft offers intelligent alarm correlation through situations, while Netcool provides impact policies for coordinating different alarms.

Installing Moogsoft requires moderate effort, as it's not overly complex but does demand some expertise. Users should understand databases and Linux file systems well to ensure a smooth installation process. While it's not overly complicated, having an experienced individual handle the installation is recommended. 

The tool's maintenance is smooth and easy. 

I rate the product an eight out of ten.