Amazon CloudWatch vs. Docker

Cloud watch is great and essential if you decide to invest in AWS and have any need to monitor the health of all aspects of your VPC resources, or at the organizational level (multiple accounts). Another benefit of the service is constant upgrades at no additional costs; the software evolves to develop modules and interface improvements. For first-time users in AWS, this is going to take a bit to understand, so the learning curve to this metrics environment can seem overwhelming at first glance/use.

Incentivized

You are going to be able to find the most resources and examples using Docker whenever you are working with a container orchestration software like Kubernetes. There will always some entropy when you run in a container, a containerized application will never be as purely performant as an app running directly on the OS. However, in most scenarios this loss will be negligible to the time saved in deployment, monitoring, etc.

Incentivized

• 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.

Incentivized

• Packaging of application to limit the space occupied
• Ease of running the application
• Provide multiple ways to handle the application issues and integration of different components like pipeline, ansible, terraform etc

• 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.

Incentivized

• Docker hub image retention policy can be relaxed
• Docker hub policies can be more developer friendly
• Docker CLI help section can be improved
• Image and container storage (local) management can be optimized

Incentivized

Very easy to use, great tutorials, documentation and cheat sheets out there to help you become a Docker Wiz

Incentivized

Haven't seen any outages, fatal/unrecoverable errors in my usage so far. Enough said.

Incentivized

Docker Desktop. The CPU high usage is a known issue. Needs fixing. Otherwise, it is great overall. Would not use anything else still.

Incentivized

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.

Incentivized

I believe that CloudWatch is a better solution to use with AWS services and resources in terms of cost and ease of integration with AWS infrastructure services. But keep in mind that Elasticsearch is better at aggregating application-level metrics. We chose CloudWatch because of its capabilities to integrate and monitor AWS services in almost real-time.

Incentivized

The reason why we are still using Docker right now is due to that is the best among its peers and suits our needs the best. However, the trend we foresee for the future might indicate Amazon lambda could potentially fit our needs to code enviornmentless in the near future.

Incentivized

It is the only tool in our toolset that has not [had] any issues so far. That is really a mark of reliability, and it's a testimony to how well the product is made, and a tool that does its job well is a tool well worth having. It is the base tool that I would say any organisation must have if they do scalable deployment.

Incentivized

• We were able to set up log streaming, retention, and simple downtime alerts within a few hours, having no prior experience with CloudWatch, freeing up our engineers to focus on more important business goals.
• CloudWatch log groups have made it relatively easy to detect and diagnose issues in production by allowing us to aggregate logs across servers, correlate failures, isolate misbehaving servers, etc. Thanks to CloudWatch, we are generally able to identify, understand and mitigate most production fires within 10-15 minutes.
• Choosing CloudWatch to manage log aggregation has saved us quite a bit of time and money over the past year. Generally, 3rd-party log aggregation solutions tend to get quite expensive unless you self-host, in which case you typically need to spend a fair amount of time setting up, maintaining, and monitoring these services.

Incentivized

• Reduces the number of virtual machine which impacted our quarterly billing
• Using docker with proxy we run multiple application on same port on same host.
• impact on billing is we have to provide docker training to the people who are working on it.