Datadog vs. meshIQ

Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.

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If you're involved in any business that is related to banking, insurance and lending industry, take the short way and save yourself from thousands of wasted dollars on fraud detection and application management issues, Nastel is my savior and it's the most powerful killer solution to beat the fraud and have a winning application performance management, It's like hiring a mathematics magician with super powers to help businesses get over the delayed amount of time spent on a problem, and the average time to process a claim, reduce errors and most importantly to decrease the number of tickets at the help center for a better and higher customer satisfaction score.

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• Create Dashboards as per application, environments, and Custom metrics in one panel.
• Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
• Playbooks, SLA definition, success and error quotas, request visualizations.
• DB monitoring, Serverless stack monitoring.
• Alerting of Production incidents so we can quickly resolve the issues on time.

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• Its ability to detect and correct IBM MQ issues before they effect the production.
• performance trends and statistics in real-time.
• Rapid and accurate monitoring of Command Servers, Dead Letter Queues, Queue Managers, Qdepth and Listeners.
• Built-in complex event processing to gain valuable visibility into order fulfillment processes

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• Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
• I would appreciate more supportive examples for how to filter and view metrics in the explorer
• I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame

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• The UI needs a lot of improvements to meet today's standards while keeping the functional part highly performing as it used to be
• Being unable to run reports through the workgroup security manager is a serious con, I think they need to consider giving it more attention
• the auto-monitoring feature performance goes low when it's enabled during a heavy workloads, it leads to a lower/heavier performance, but during the latest update I feel it got lighter somehow.
• They also need to give more attention to the encryption and enhance it with the latest encryption technologies

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There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.

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The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

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We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.

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• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

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• A reduction in point of sale abandonment by 70% reflects the change in mindset of customers who are no longer irritated by price anomalies.
• The company was able to merge many unnecessary servers due to thousands of useless queues it had, resulting in yearly savings of more than $250,000
• improved efficiency and cost-savings by 80% within the first 2 months

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