Amazon CloudWatch vs. meshIQ

For out business we find that AWS Cloudwatch is good at providing real-time metrics for monitoring and analysing the performance and usage of our platform by customers. It is possible to create custom metrics from log events, such people adding items to a basket, checking out or abandoning their orders.

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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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• It provides lot many out of the box dashboard to observe the health and usage of your cloud deployments. Few examples are CPU usage, Disk read/write, Network in/out etc.
• It is possible to stream CloudWatch log data to Amazon Elasticsearch to process them almost real time.
• If you have setup your code pipeline and wants to see the status, CloudWatch really helps. It can trigger lambda function when certain cloudWatch event happens and lambda can store the data to S3 or Athena which Quicksight can represent.

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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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• Memory metrics on EC2 are not available on CloudWatch. Depending on workloads if we need visibility on memory metrics we use Solarwinds Orion with the agent installed. For scalable workloads, this involves customization of images being used.
• Visualization out of the box. But this can easily be addressed with other solutions such as Grafana.
• By design, this is only used for AWS workloads so depending on your environment cannot be used as an all in one solution for your monitoring.

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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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It's excellent at collecting logs. It's easy to set up. The viewing & querying part could be much better, though. The query syntax takes some time to get used to, & the examples are not helpful. Also, while being great, Log Insights requires manual picking of log streams to query across every time.

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Support is effective, and we were able to get any problems that we couldn't get solved through community discussion forums solved for us by the AWS support team. For example, we were assisted in one instance where we were not sure about the best metrics to use in order to optimize an auto-scaling group on EC2. The support team was able to look at our metrics and give a useful recommendation on which metrics to use.

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Grafana is definitely a lot better and flexible in comparison with Amazon CloudWatch for visualisation, as it offers much more options and is versatile. VictoriaMetrics and Prometheus are time-series databases which can do almost everything cloudwatch can do in a better and cheaper way. Integrating Grafana with them will make it more capable Elasticsearch for log retention and querying will surpass cloudwatch log monitoring in both performance and speed

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• Positive for alarms and alert notifications once configured/customized.
• Has upfront learning curve, and cost can increase as does the alarm activity and monitoring details you may require.
• Cost-effective for any size organization keeping with AWS and utilizing its native tools is a savings in long-term ROI.

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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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