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.

My company uses the solution to collect logs from other sources, including Amazon Virtual Private Cloud. All the logs are collected from Amazon CloudWatch. From the log groups, my company sends S3 and other third-party applications. My company uses Amazon CloudWatch for monitoring purposes.

We use Amazon CloudWatch for monitoring infrastructure for EC2 instances. We created CPU, memory, system, status, and disk utilization checks. Based on those checks, we created actions such as disk cleaning by running a command, integrating with Lambda, and sending email notifications. We use the basic functionalities of Amazon CloudWatch.

My company's clients use Amazon CloudWatch, which offers a very good performance for application performance monitoring, as well as the integrations part.

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 use the solution to monitor the devices on our system or infrastructure. CloudWatch notifies you when a token is used or when the VM is not working. It helps you to determine the status of your infrastructure.

We're only using it for collecting the logs and forwarding it, and then in some areas, we use it for scheduling stuff and there are some new alerts that come in, and then from there, they had to trigger some Lambdas.

We build the monitoring and everything on top of the Datadog.

We use Amazon CloudWatch in our company to mainly troubleshoot Lambda functions. Then, we use CloudWatch to set up CloudWatch Alarms.

We use the solution for monitoring CPU usage, memory usage, Lambda logs, and load balancer logs.

Amazon CloudWatch is a monitoring and availability service designed to collect and check metrics and collect and monitor log files. We can set alarms, and Amazon CloudWatch allows users to gain operational insight into their application resource and services. The solution also helps users to ensure the reliability, performance, and availability of their infrastructure.

It serves as a diagnostic and profiling tool, particularly useful for dissecting the intricacies of applications, especially in scenarios like Microsoft's best applications. When a user triggers transactions through the GUI, such as purchasing tickets for events like cricket or concerts, the process involves multiple layers—starting from the front-end GUI to the back-end middle tier, microservices, and concluding with database interactions. It allows me to meticulously analyze and monitor these processes by creating and examining various logs. I can delve into the details of each stage, from API calls to network components, and server processing (involving Java Virtual Machine), and even gauge how long specific APIs or queries take to execute. This tool proves invaluable in identifying bottlenecks, such as waiting times or timeouts and understanding the performance of APIs, queries, and even the efficiency of gateways.

CloudWatch is used to monitor not only for the cloud but also for on-premises services. So, you could think of it as a comprehensive monitoring tool. It's just proprietary monitoring software.

The primary use cases are creating a platform for customer experience and customer engagement. This is more about profiling a customer and it is more about using or basically understanding the customer's needs and wants and profiling the data and showing it to a business analyst.

Whenever we launch any instances or use any service we receive default metrics from Amazon CloudWatch. It is easy to track what is happening in the services that we are using. Additionally, it provides metrics logs from servers and what is happening from the infrastructure.

CloudWatch is important because we use it to remediate automation. For example, I had to integrate GuardDuty with CloudWatch. If anything went wrong in the environment when GuardDuty had captured all the APIs, and if someone got an alarm on the server, it was basically because of CloudWatch. CloudWatch would have seen an intruder, thinking, "This is what's happening," and so on.

I used the solution to monitor, collect, and store metrics from AWS solutions like EC2. Taking all these metrics from other sections, such as GuardDuty for the security department and all the security hubs, you are presented with all the views at once.

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.

While we have used CloudWatch, we have not used it extensively. We should start monitoring our applications once it starts performing in production. We are not at that stage yet. However, we have implemented it. In the end, we will use it mainly to monitor our applications.

We're using Amazon CloudWatch to monitor the entire application instances, client application, and backend communication. We're also using the solution to monitor service availability and application development.

Amazon CloudWatch for infrastructure and serverless monitoring.

We use the solution for monitoring purposes. We also use it for events and alerts. 

We are primarily using the solution to monitor some of the instances that we have on Amazon for our testing development. It is also the go-to solution used by our organization to track logs and organize metrics across all applications deployed on Amazon Web Services

We use it for testing environments.

We use CloudWatch to monitor our infrastructure and resources, such as bandwidth, etc. It comes with the AWS package we use, and it's easier when all your services come from one vendor. 

We use the solution to set alerts. We can set up thresholds to trigger alerts if an instance in AWS reaches the threshold value. Based on the alerts, we check the issue in the instance.

We are using Amazon CloudWatch for all of our data monitoring.

The majority of the use cases are monitoring of all the AWS services, which can be integrated into CloudWatch. Also, the application logs also can be integrated. Due to that, if there are multiple instances they can be monitored through CloudWatch. The monitoring can be automated as well. It has automated thresholds that can be set for alerting. Therefore, we use CloudWatch for monitoring and incident alerts.

We use the solution for monitoring the traffic. We analyze any suspicious traffic detected by AWS.

Our company used the solution for a project that included data message and data lake architecture, performance testing, and an engineering solution to monitor virtual machines or the S3 bucket. 

The solution monitored key performance indicators for almost all services including Aurora, Fargate, Lambda, Snowflake NoSQL databases, and Sumo Logic.  

The solution is used for monitoring systems and for protection. For example, there are ransomware attacks and other threats that need to be secured.

We are kind of consultants. We maintain our customers' environment on AWS. 

We use the product to monitor resources for reporting purposes. It alerts us when we are required to scale up resources.

When alarms are triggered, we rely on CloudWatch to check various metrics such as memory utilization and application performance. We examine all the relevant matrices during this process.

We always use whatever's the latest because that's all we have access to. Because we deploy to other companies, we do public and hybrid clouds. Some of it is hybrid, some of it would be private as well. The majority is probably hybrid, but we're deploying for customers. Most of it's around optimizing utilization, their cloud utilization. They're making sure that they're getting the most out of their in-cloud environments and their instances. Making sure that there's no strange behavior in the environment. That's really what we're trying to do. And that's what Cloud Watch really helps with, is it's making sure it's collecting, monitoring, analyzing, all the things that are going on within their instance, so that we can optimize it better. And if there are any anomalies, anything that is out of the norm, then we're able to catch it and fix it pretty quickly. The ability of it to detect anomalies, and setting dynamic alarms, and automating a lot of the actions. I think that's a huge benefit that the companies have seen.

We primarily use the solution for budgeting and monitoring for abnormal behaviour.

We use it to monitor our servers, to check the memory of our servers, and to determine whether the CPU is overhead or not.

We also use the alerting system to inform us when something goes wrong.