Amazon CloudWatch vs. Broadcom Application Delivery Analysis

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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Look no farther than this tool if you need an API testing solution that also includes service virtualization. This technology also forces you to move your testing lifecycle to earlier stages of development, which improves the overall SDLC.

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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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• This is an excellent tool for implementing Service virtualization in your own and/or third-party web services. This ensures that our automation and performance test environments are always available and consistent.
• This application also aids in the setup and maintenance of test data, which is an important component of test automation.

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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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• This tool has a license fee and is not free. Many open-source tools provide free API testing solutions, therefore turning some of this tool's features open-source might be beneficial.
• The tool's load testing component is not integrated and instead relies on the free Blaze meter.

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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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Along with the Parasoft SOA tool, it is unquestionably among the top leaders in API testing and virtualization. Many open-source API testing libraries are free, including Rest Assured, Karate, and even Postman and SOAP UI, which goes against CA.

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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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• In our group, this instrument produced a high return on investment. We saw a considerable reduction in downtime in our test environments thanks to service virtualization.
• In addition, service virtualization reduces the expenses of interacting with third-party services, which is common in low-cost contexts.

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