Amazon CloudWatch is a native AWS monitoring tool for AWS programs. It provides data collection and resource monitoring capabilities.
$0
per canary run
Google App Engine
Score 8.2 out of 10
N/A
Google App Engine is Google Cloud's platform-as-a-service offering. It features pay-per-use pricing and support for a broad array of programming languages.
$0.05
Per Hour Per Instance
Pricing
Amazon CloudWatch
Google App Engine
Editions & Modules
Canaries
$0.0012
per canary run
Logs - Analyze (Logs Insights queries)
$0.005
per GB of data scanned
Over 1,000,000 Metrics
$0.02
per month
Contributor Insights - Matched Log Events
$0.02
per month per one million log events that match the rule
Logs - Store (Archival)
$0.03
per GB
Next 750,000 Metrics
$0.05
per month
Next 240,000 Metrics
$0.10
per month
Alarm - Standard Resolution (60 Sec)
$0.10
per month per alarm metric
First 10,000 Metrics
$0.30
per month
Alarm - High Resolution (10 Sec)
$0.30
per month per alarm metric
Alarm - Composite
$0.50
per month per alarm
Logs - Collect (Data Ingestion)
$0.50
per GB
Contributor Insights
$0.50
per month per rule
Events - Custom
$1.00
per million events
Events - Cross-account
$1.00
per million events
CloudWatch RUM
$1
per 100k events
Dashboard
$3.00
per month per dashboard
CloudWatch Evidently - Events
$5
per 1 million events
CloudWatch Evidently - Analysis Units
$7.50
per 1 million analysis units
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
Offerings
Pricing Offerings
Amazon CloudWatch
Google App Engine
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
With Amazon CloudWatch, there is no up-front commitment or minimum fee; you simply pay for what you use. You will be charged at the end of the month for your usage.
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More Pricing Information
Community Pulse
Amazon CloudWatch
Google App Engine
Features
Amazon CloudWatch
Google App Engine
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
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.
App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.
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.
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.
There is a slight learning curve to getting used to code on Google App Engine.
Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)
App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.
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.
I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster
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.
Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.
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
We were on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.
Effective integration to other java based frameworks.
Time to market is very quick. Build, test, deploy and use.
The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.