Amazon CloudWatch Reviews

We use CloudWatch for monitoring and logging. It helps us monitor our applications' performance, particularly in ensuring that every API hit returns a response within four seconds, which is our SLA. We also monitor invocation errors in Lambda and use CloudWatch alerts to notify us of any issues.

CloudWatch allows us to discover errors before our end customers do, enabling us to proactively address issues. We can notify our business relationship managers of potential issues due to recent deployments.

I use Amazon CloudWatch to check the log we have sent, ensuring it isn't blocked. That is the primary purpose.

I like its filtering capability and its ability to give the cyber engine insights. It's useful to analyze past data and compare it with recent activities.

We utilize Amazon CloudWatch for logging purposes, and when it comes to monitoring our services, like the current task of setting up EPS clusters, we rely on it for essential checks. This includes monitoring the health and performance of our EKS (Elastic Kubernetes Service) and regularly inspecting the cluster's status through the management portal.

We have been highly satisfied with its event scheduler feature. Enabling this feature has proven to be quite beneficial as it allows for the seamless automation of various tasks. It offers direct integrations with various storage providers, making it convenient to push logs from CloudWatch to these external platforms. For instance, if I need to transfer my logs from CloudWatch to a third-party storage solution, it provides a robust integration mechanism for such use cases.

It's a monitoring tool. If we want to monitor any of the applications hosted in AWS, we can see the logs and the artifacts of those applications in CloudWatch.

If we deploy anything and get into some issues, it would be pretty difficult to understand it. So, we go through the CloudWatch logs of the application to understand why we are getting the error. It helps us to resolve the issues.

We use the solution to monitor our AWS resources. We used Azure extensively but a couple of years back we moved to use both Azure and AWS. Currently, we have three main use cases. 

Our predominant use case is monitoring our S3 which includes terabytes of data. We monitor all the buckets and containers plus who has access to them, the thresholds, and user data. We constantly watch all the KPIs and CloudWatch metrics. 

Our second use case is watching logs and processes for other products such as AWS tools, AWS Glue, and Redshift which includes a few terabytes of data.

Our third use case is minor and with Athena.

Our fourth use case is new. We just started using SageMaker for a small POC and want to complete all of our data modeling and logs.

In the future, we will be using the solution with Airflow, which will become one of our biggest use cases. 

CloudWatch works very well with any of the AWS resources so we always monitor through it.

Our business flow has improved because we monitor email thresholds and immediately get an alert from CloudWatch if use goes beyond thresholds. Without this alert, we would have to use external monitoring. 

We collect the CloudWatch logs and use them to analyze security. It helps us to monitor malicious activity.

Amazon CloudWatch is an important tool in AWS. If we have an AWS-based infrastructure, the product must be enabled in all environments. If we have different environments in the cloud, CloudWatch is mandatory. The tool enables live monitoring. It is easier for us to track who logs in and out of the systems and how the computing services work.

The product is more than enough for what we need daily. Amazon improves things year on year. It is quite straightforward for us. We are using the solution to monitor our live environment. If an attack happens, we can track it down using the logs easily and act fast to isolate the threat. The retention of the logs and live tracking features are useful for us.

I use it for log monitoring and log capture. That's the main purpose. 

Alerts and notifications functions help with the operational response. For example, if you have a critical server and want to set an alert if CPU utilization exceeds 90%, a notification will be raised. You can link an action to that notification, not just notify. 

You can automate actions or use AWS functionalities like auto-scaling, where you can configure the metrics to add more nodes if the threshold is exceeded. AWS has become very rich in functionality over time, and the same piece of functionality can solve different problems.

CloudWatch automation works through notifications linked to Lambda functions, which can then perform any automation you like.