Amazon CloudWatch vs. Azure Kubernetes Service (AKS)

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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AKS works very well for running containerized applications that require high availability and scalability. This includes systems like our HRIS platform and customer-facing web applications. AKS is a good choice when applications are broken into multiple services that need independent scaling and deployment. It provides the flexibility needed to manage these architectures effectively. But for single, low-traffic applications or simple internal tools, AKS can be overkill. For scenarios like that Azure App Service would be better.

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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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• AKS makes it easier to replicate data to multiple regions
• Azure portal make it easier to manage the resources of the organization

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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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• Steep learning curve
• Expected charges are unclear until you see real production usage
• Operations teams need to learn an entirely new skill set

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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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As already said, the UI/CLI and even terraform are perfectly fine, but certain details could be documented better. For instance, if I want to secure the whole Azure Kubernetes Service (AKS) with my own managed keys, then it is very complex and hard to get there. Not really a single source that gives you the whole picture. Besides that, it is still good to use, in most cases intuitive but details mentioned as above can be tricky.

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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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Microsoft support was really good, whenever we raise any ticket they come back to us within a couple of hours.

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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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Amazon EKS stacked up very well and had better performance in some areas. However, Azure Kubernetes Service was a better fit given our Azure environment.

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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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• We had to spend more time on Azure Kubernetes Service (AKS) than on AWS and GCP to get our kubernetes cluster up and running
• The resources on nodes need to be left out unused, so effectively it is wasting money there
• It definitely made us spend more time into maintaining kubernetes

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