Amazon CloudWatch Reviews

Amazon CloudWatch is a very small service that AWS provides. It is a monitoring service for applications within the AWS cloud, and we can integrate external applications using the APIs or SDK.

The basic feature and main use of Amazon CloudWatch is for monitoring. Users can configure it for any services within AWS or supported services using the APIs or SDK for external services. You can get CPU metrics, memory utilization, metrics for load balancers, metrics for ECS clusters, or whatever service is deployed on AWS. Everything can be monitored using Amazon CloudWatch.

Currently, we are using it to monitor all AWS services only, nothing external. Amazon CloudWatch is basically for AWS services. If a user who is not using AWS cloud, they will not be interested in Amazon CloudWatch. It is just for people who are using AWS cloud. It can be integrated with external systems using SDKs. It depends on the use case and why users need Amazon CloudWatch because there are other services that provide more sophisticated options. There is no proper visualization here, so when you want to monitor something, you can get any other service which has both proper dashboard and data pulling capabilities.

The basic feature and main use of Amazon CloudWatch is for monitoring. Users can configure it for any services within AWS or supported services using the APIs or SDK for external services. You can get CPU metrics, memory utilization, metrics for load balancers, metrics for ECS clusters, or whatever service is deployed on AWS.

We have used Amazon CloudWatch logs which is useful when we want to go back and see what happened at a particular time instance.

It provides a dashboard, and if there are external or internal users whom you want to give access to specific dashboards, you can share the dashboard. As an administrator, you can configure which metrics or data can be visible for the user on that dashboard. You can share the link and the username and password, allowing direct access to Amazon CloudWatch dashboard.

If there is a CPU spike or system issues, we set alarms to notify us if the system is going down or not reachable. All these things can be configured with Amazon CloudWatch, and we can get an email using SNS saying that a particular service or server is having an issue.

It is very easy to use. As a monitoring tool, whenever your system experiences issues, it will notify you and is directly linked to your service. If anything is wrong with your server or services, it means it is affecting your service and automatically indicates that user experience is degraded. That is why Amazon CloudWatch is important while running things on the cloud.

Amazon CloudWatch itself provides a lot of data. However, for visualization, we need to use third-party tools. We are in a process of integrating Grafana, Loki, and Prometheus to have better visualization on Amazon CloudWatch. We are also integrating Grafana with the application itself to get the application data and logs.

Alternatively, there is AWS Kinesis and Glue where you can scrape the logs and have visualization, but a more easy option is Grafana. If you want to get a proper visual representation to see what is happening, then you need to integrate a third-party tool. Amazon CloudWatch has all the data, but to see what is happening, you need some third-party tool.

We have been using the solution for more than 10 years.

There have been no stability issues.

It is not a scalable thing as it is not a service that has something a server. The implementation part and management part are handled by AWS itself. We just need to configure it to the resource which we want to monitor. When we use Amazon CloudWatch, we are not deploying any kind of server or service. It is already there as a managed service from AWS.

Regarding Amazon CloudWatch, we have not needed customer service. If we have anything we need to look into, we can search on Google and use AI.

Neutral

We have not used any previous solutions.

Amazon CloudWatch is by default available with AWS services. If you want enhanced monitoring on Amazon CloudWatch, then there will be a fraction of additional charges. It is available with AWS itself and not with any third-party services.

Amazon CloudWatch is by default available with AWS services. If you want enhanced monitoring on Amazon CloudWatch, then there will be a fraction of additional charges. It is available with AWS itself and not with any third-party services.

We work on AWS on a number of products including EC2, load balancers, Shield, CloudFront, and Amazon CloudWatch. On a scale of 1-10, I rate Amazon CloudWatch an 8.

My main use case for Amazon CloudWatch is the monitoring and analytics of the application servers. I basically use Amazon CloudWatch to monitor the microservices and AWS infrastructure, helping me track application logs and performance metrics, any API latency, error rate, and resource utilization. I also use CloudWatch Alarm to proactively detect issues and respond to production incidents before they affect us.

Using CloudWatch Alarms helps my team respond to incidents by giving us proactive visibility into production issues through monitoring metrics such as CPU utilization, memory utilization, API latency, and error rate. For example, an alarm detected unusually high API latency in a payment service, and the alert allowed us to quickly identify slow database queries, optimize them, and restore normal performance before they had a significant impact on users.

I use Amazon CloudWatch in my daily work to monitor the microservices' performance and look into metrics such as CPU utilization, memory utilization, and server utilization. We monitor the containers deployed over AWS, checking their performance to easily debug if an API is experiencing high latency and readily find the bottleneck problem in the services.

In my opinion, the best features Amazon CloudWatch offers are Metrics, Analytics, Logs, Alarms, Dashboards, and Log Insights, with standout features being real-time monitoring and centralized logging, proactive alerting, and fast troubleshooting.

The dashboards in Amazon CloudWatch help with troubleshooting by allowing us to easily look into API latency and how much resource consumption is occurring. The CloudWatch dashboard provides real-time data and views of our application health while Log Insights lets us quickly search and analyze logs to identify root causes of production issues, making troubleshooting time efficient and monitoring much more streamlined.

Amazon CloudWatch has positively impacted my organization by improving our ability to monitor production issues and easily find the root cause in the application. We can quickly fix issues at the point of occurrence, and real-time metrics for microservices provide centralized logging and automated alerts that enable fast incident detection, quicker troubleshooting, and better application reliability, ultimately reducing operational efforts by giving engineers a single platform for monitoring AWS resources and microservices.

I have seen many positive outcomes in my organization, estimating that CloudWatch reduced troubleshooting time by around thirty to forty percent because engineers could correlate metrics and logging from a single platform. Early alerts also help us resolve many performance issues before they escalate into major incidents, contributing to improved service availability.

For improvements, I think Amazon CloudWatch could enhance certain areas, particularly regarding pricing structure. I wish to see simpler pricing, more intuitive dashboards, easier log queries for beginners, richer visualization options, and strong AI-assisted troubleshooting.

I have been using Amazon CloudWatch since four years in my career.

Amazon CloudWatch is stable in my experience, and we are using this technology for our application integration.

The scalability of Amazon CloudWatch is very good, providing high throughput and auto-managing applications alongside auto-dashboard support.

Customer support for Amazon CloudWatch has been excellent. I received responses within the expected time frame and faced resolutions to specific scenarios.

Before using Amazon CloudWatch, we considered tools such as Prometheus with Grafana and ELK stack, comprising Elasticsearch, Logstash, and Kibana. We switched to Amazon CloudWatch because it was a good fit, given that we were already running our applications on AWS, benefiting from its native integration and reducing the operational overhead of maintaining a separate monitoring platform.

I evaluated other options like Prometheus with Grafana and the ELK stack but found Amazon CloudWatch to be a good fit primarily because we are running our application on AWS, where its native integration and easy-to-manage characteristics reduced the operational overhead of maintaining separate monitoring solutions.

I have seen a return on investment from Amazon CloudWatch, as it clearly saves engineering time. Automated alerts, centralized dashboards, and log analysis reduce troubleshooting time, improve incident response, and minimize manual monitoring, translating operational improvements into better service reliability and increased developer productivity.

The experience with pricing, setup cost, and licensing for Amazon CloudWatch has been positive. It was very easy to set up because it is built into AWS and does not require separate licensing, being billed based on usage, which works well. Although costs can increase with large log volumes and custom metrics, proper monitoring and log retention policy helps keep costs under control.

I evaluated other options like Prometheus with Grafana and the ELK stack but found Amazon CloudWatch to be a good fit primarily because we are running our application on AWS, where its native integration and easy-to-manage characteristics reduced the operational overhead of maintaining separate monitoring solutions.

Amazon CloudWatch interface is intuitive, and the query language is straightforward once I start using it regularly.

I rate Amazon CloudWatch an eight out of ten because, in my experience, it provides excellent monitoring for microservices metrics and logging, alerting, and integration with AWS services, being very reliable for monitoring our applications and infrastructure, helping us detect issues early, and troubleshoot production incidents efficiently. Features such as troubleshooting alarms, dashboards, and Log Insights are practically valuable in day-to-day operations.

Regarding Amazon CloudWatch's governance and security, I note that in our organization, we primarily focus on standard governance practices.

The AI capabilities of Amazon CloudWatch are good, as they provide better outcomes for users looking to easily find issues. The AI-assisted capability is reliable for detecting unusual behavior and helping identify potential issues. Although alerts are generally accurate, they are most effective when combined with proper alarm configuration, historical data, and manual investigation. I rate the accuracy and reliability as very good for operational monitoring.

For purchasing Amazon CloudWatch, we did not buy it through the AWS Marketplace since Amazon CloudWatch is a native AWS service that was enabled directly with our AWS account and billed as part of our regular AWS usage.

My advice for others looking into using Amazon CloudWatch is to start with the most important metrics and alarms, avoid collecting unnecessary logs, configure log retention to manage costs, and make full use of dashboards and Log Insights. If your application runs on AWS, Amazon CloudWatch is a reliable and scalable monitoring solution that provides excellent operational visibility.

Amazon CloudWatch has been a valuable part of our AWS environment, helping us find error rates, API latencies, and application metrics, while centralizing logging and providing reliable monitoring and proactive alerts with strong integration into AWS services. Despite needing some improvements, I confidently recommend it to any organization running applications on AWS, as it significantly improves operational visibility and incident performance. I have given Amazon CloudWatch an overall rating of eight out of ten.

Positive

The typical use case for this solution is a banking solution where a lot of observability is required, including visibility into transactions and how traffic moves from different places. A good amount of traceability is required, which is where Amazon CloudWatch is used. This is purely a banking solution, so we must ensure tracking of any transaction loss or in-flight transactions. The visibility, monitoring, and management of infrastructure and logging are very important for banking solutions.

The best features of Amazon CloudWatch need to improve visibility into the network because when using hundreds of network resources such as transit gateway, VPNs, routers, route tables, and firewalls, it does not give many details in a structured manner. The traceability is not optimal when flowing through the network.

There is room for improvement for Amazon CloudWatch, specifically regarding the traceability aspect of network resources.

Apart from traceability of network resources, Amazon CloudWatch needs to be more interoperable with other tools because many companies are starting to use AI-based dashboards. When using third-party dashboards such as Kibana or Grafana and other visualization tools, there should be a way to feed CloudWatch's data and logging capabilities into these visualization tools.

It is usually deployed on the cloud and works effectively with its native cloud resources on AWS, whether public or private. With hybrid cloud, it has some difficulty maintaining visibility into other cloud resources. For instance, when connecting to Google Cloud, there is no visibility or traceability from Google Cloud into CloudWatch. There should be some mechanism for hybrid cloud scenarios, though it works fine with private and public cloud.

I have approximately four to five years of experience working with Amazon CloudWatch.

I would rate technical support from Amazon as six out of ten. The reason for this rating is that any kind of dedicated tech support requires extra premium payment. While using their cloud and cloud resources, if you have an issue with CloudWatch, you must pay additional monthly fees to get time from dedicated tech support. Without premium support, the turnaround time is quite high. When reporting issues, responses sometimes come after three to four days.

Neutral

The initial setup of Amazon CloudWatch is very straightforward.

I have not seen an ROI from this solution because Amazon CloudWatch is not a solution that can generate revenue. ROI does not apply here. It is one of the requirements for most banking solutions. You cannot sell a product without having proper monitoring, visibility, and logging. That is the reason why people are using CloudWatch. It cannot be used as a selling point to customers as they are not concerned about it.

Overall, the pricing of Amazon CloudWatch is very expensive.

The scalability of Amazon CloudWatch rates as high scalability, scoring a perfect ten. Amazon CloudWatch is highly stable with excellent high availability, scalability, and stability. On a scale of one to ten, this solution deserves an overall rating of 8.

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.

CloudWatch provides essential monitoring capabilities that integrate seamlessly with other AWS services. It helps us check response times and detect errors, allowing us to take corrective actions such as increasing concurrency or adjusting memory limits.

There is room for improvement in setting up custom metrics in CloudWatch. Adding conditional expressions would enhance its functionality.

We have not faced any stability issues or outages related to CloudWatch. It has consistently shown reliable and desired values.

CloudWatch is highly available and scalable. It does not go down like other services, ensuring that monitoring is consistently reliable.

Customer service has been rated eight out of ten because of the knowledge they have for specific issues. Their documentation and workshops provide valuable support.

Positive

CloudWatch is easy to use, and AWS provides excellent documentation and a workshop-style website to assist users.

Before setting up any alarms or monitoring, it is advisable to review the documentation to know how to effectively monitor your applications for different use cases.

I'd rate the solution eight out of ten.

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.

CloudWatch itself is fine. That said, maybe Amazon Web Services can improve by providing a library for CloudWatch with some useful features.

We have been using it for about two to three years.

I have never experienced any issues with stability.

I have not contacted their support team.

Positive

From my perspective as a tester, the initial setup is easy. However, for setting up cloud logging and management, developers might have more insights.

It is easy to access all previous historic logs and retrieve phased data as per our filters. That is the best capability it offers.

I'd rate the solution nine out of ten.

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. 

It is valuable that CloudWatch collects all the metrics. I primarily like the RUM. There is an instantaneous response when monitoring logs and KPIs. CloudWatch immediately hooks up and connects to the KPIs and all the metrics. 

Even though the product works well with most AWS, it is a nightmare to use with Snowflake. Snowflake is a SaaS product hosted on AWS, but using it with CloudWatch still doesn't give us the support we need so we rely on separate monitoring. 

We have many databases such as MongoDB and SQL Server, RDS, and PostgreSQL. For these, CloudWatch is good but a little basic and additional monitoring tools are required. It's challenging to use one monitoring tool for S3 and another monitoring tool for Snowflake. 

It would be beneficial for CloudWatch to provide an API interface and some kind of custom configuration because everybody uses APIs now. Suppose Snowflake says we'd get all the same things with MongoDB such as APIs, hookups, or even monitoring. That would allow us to build our own custom solution because that is the biggest limitation of CloudWatch. If you go a bit beyond AWS products even if they're hosted on AWS, CloudWatch doesn't work very well. 

I'd also like an improved UI because it hasn't significantly improved in a few years and we want to see it at a more granular level. I get my KPIs in a bucket usage for yesterday but I'd like to see them by a particular date and week. We have three buckets rolled by hundreds of people and I want to see use cases for an individual to determine where I need to customize and provide more room. I want aggregation on multiples, not one terameter. 

I have been using the solution for two years. 

The solution is very stable with absolutely no issues. We used to see a delay when we were setting up three buckets but now we receive instantaneous notifications. 

The solution is definitely scalable. Most of our development environment uses it and we are running three teams of 150-200 people. Usage levels are different between developers and the support team so the total users at one time is 100-150. 

The solution is managed by our internal AWS maintenance team. Seven people manage our cloud environment and seven manage our platform side for not just CloudWatch, but everything on AWS.

We still need to find a solution for Snowflake and Tableau environments unless CloudWatch provides better support in the future. 

The support staff are seasoned professionals and are good. Amazon provides the benchmark for support and nothing else compares.

On-premises, we have used other solutions like Sumo Logic, Azure Logic Apps and others. Not everyone uses AWS so we have a lot of tools we use.

Previously we used some main external app logic but it didn't work well with AWS tools. I would have to figure it out and configure Aurora to do something or find a way to do S3 buckets. Those solutions worked well for on-premises, but not with AWS and clouds.

The setup for this solution is pretty simple and anyone can do it if they are on AWS. Setting up all our VPC and private links connecting to our gateways took some time, but CloudWatch setup was a no-brainer and took a couple of days. 

Our implementation was done in conjunction with a third party. We like to bring in a few engineers to work with our engineers and then we partner with a third party like Slalom to help with integration. Our process is a mix of all three with AWS staff helping for a couple of weeks and Slalom for a couple of months. Our team slowly takes over management. 

We plan to increase our usage because we don't have another monitoring tool right now. With the Airflow orchestration, our CloudWatch use will significantly increase as we monitor all of our RUM, notifications, jobs, and runs. Our runs and billings will increase 20-30% once we start using Airflow. 

Because CloudWatch doesn't support all externally hosted products, I rate it a nine out of ten for ROI. 

I don't know specifics about pricing because we pay for all our AWS services in a monthly bundle and that includes CloudWatch, Redshift, VPCs, EC2s, S3s, A39s, and others. We spend about $5 million per year on AWS with CloudWatch being about 5% of that cost. 

I did not evaluate other solutions. Once we moved to AWS, we looked for a tool that was native to that cloud. That is the process we are currently undertaking for Snowflake and Tableau because CloudWatch doesn't support them well. We do try to use CloudWatch as much as possible. 

The solution is pretty good because it automatically comes and works well with AWS. Before you use any product from AWS, think about whether it is supported or how it will interface. I suggest using the solution with one product at a time and then transitioning to important interfaces. 

If you find you can't configure the solution with Redshift for example, and are struggling to build your S3 even though both use S3, then you may have to find another monitoring solution. It makes sense to follow Amazon's best practices. They advise not to use certain monitoring components alone but to use them as an integral part of your system. Monitor your ecosystem and think of a high-level picture of it rather than just determining that CloudWatch must be a part of Redshift. This solution is just one part of an entire system. 

I would rate the solution a nine out of ten. 

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.

There could be further enhancements through CloudWatch's partnerships. It allows integration with additional log archive tools, such as Splunk. I am not certain if direct integration is currently available, this would be a valuable improvement to explore.

I have been working with it for five years.

Occasionally, there can be some complexity involved in crafting custom queries to extract specific information from them, so I would rate the stability eight out of ten.

It is highly scalable and capable of handling a vast amount of logs. In our particular scenario, we haven't encountered a use case where we need to retain logs for the past fifteen years. I would rate it eight out of ten.

In the past, we relied on on-premises services for logging and other tasks, so we often had to manage a lot of data transfer between different systems, which could be quite cumbersome. Since we've transitioned to AWS for hosting our resources and solutions, we've found that it's much more efficient to use cloud-native services like CloudWatch. When your infrastructure and solutions are already on AWS, it's a logical choice to leverage the cloud's services rather than dealing with the complexities of integrating with external services.

The initial setup was not complex.

Synchronization is the default setting for certain services, and it's automatically enabled. For custom configurations, we had to take proactive steps and perform specific deployments. Apart from these cases, deploying this solution is generally straightforward.

It is a free-of-charge service.

We encountered several challenges during our transition, with the integration process. When considering third-party logging solutions, one of the key concerns is how the integration process will be handled, as it may not be as straightforward as using built-in services.

The choice of logging solution should always be determined by the specific business requirements. It is crucial to align the logging strategy with what type of logs are needed and how they should be used. There are instances where we require custom solutions to retrieve logs, especially application logs that may not be easily accessible through CloudWatch or similar services. When we heavily rely on AWS native services, CloudWatch is indeed a robust choice. However, in certain scenarios, we might need integration capabilities with other tools, and if they can incorporate such features, it would enhance overall logging capabilities. I would rate it eight out of ten.

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

The monitoring features are valuable. The product pushes notifications with the help of SNS. We can increase or decrease our instances horizontally or vertically. We are collecting CloudWatch logs in Grafana too. We have also configured it with Kibana.

CloudWatch doesn’t monitor disk throughput by default. It is part of EC2. If EC2 forwards the logs, then we can do it.

I have been using the solution for three years.

I rate the tool’s stability an eight out of ten.

The tool’s scalability is good. I rate the scalability a seven and a half out of ten. I have configured two instances for CPU usage. It breaks the threshold. It scales up and down multiple times. It is better to build only one instance in such facilities. We have 30 users in our organization.

The support is good.

Positive

The initial setup is easy. The deployment takes around five minutes. It is very fast.

The pricing is average.

We were using third-party tools before. We had to configure the third-party tools.

I will recommend the tool to others. Overall, I rate the solution an eight out of ten.

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.

CloudWatch is required for the organization to stay compliant.

The detection is the most valuable feature.

CloudWatch's scalability could be improved.

I've been using CloudWatch for almost five years.

I rate CloudWatch's stability a seven out of ten.

I rate CloudWatch's scalability a seven out of ten.

The solution was easy to deploy.

The price is okay for me. How good the pricing is depends on how you want to use the solution.

CloudWatch has good features and tools. No matter how many people are on the security team, CloudWatch monitors the performance of your gateway resources daily, including CPU utilization and network traffic. If you are new to monitoring, CloudWatch is good because it helps you monitor your environment and your logs and captures and generates logs by applications and resources. I rate CloudWatch an eight out of ten.