Find out in this report how the two Application Performance Monitoring (APM) and Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Amazon CloudWatch offers cost-saving advantages by being an inbuilt solution that requires no separate setup or maintenance for monitoring tasks.
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.
In recent years, due to business expansion, knowledge levels among support engineers seem to vary.
My advice for people who are new to Grafana or considering it is to reach out to the community mainly, as that's the primary benefit of Grafana.
I do not use Grafana's support for technical issues because I have found solutions on Stack Overflow and ChatGPT helps me as well.
Grafana's customer support is mainly for developers.
Amazon CloudWatch's scalability is managed by AWS.
In assessing Grafana's scalability, we started noticing logs missing or metrics not syncing in time.
In terms of our company, the infrastructure is using two availability zones in AWS.
I sometimes notice slowness when Amazon CloudWatch agents are installed on machines with less capacity, causing me to use other monitoring tools.
When something in their dashboard does not work, because it is open source, I am able to find all the relative combinations that people are having, making it much easier for me to fix.
Once you get to a higher load, you need to re-evaluate your architecture and put that into account.
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.
Amazon CloudWatch charges extra for custom metrics, which is a significant disadvantage.
Maybe Amazon Web Services can improve by providing a library for CloudWatch with some useful features.
It would be better if they made the technology easy to use without needing to read extensive documentation.
Regarding the clarity of the official documentation for installation, I think the official documentation, which has something called Alloy, the Alloy integration, is not that clear.
I would give it a ten if it were much simpler for users who just want to get a simple objective in Grafana and are not experienced with technical configuration.
Overall, the pricing of Amazon CloudWatch is very expensive.
Amazon CloudWatch charges more for custom metrics as well as for changes in the timeline.
The costs associated with using Grafana are somewhere in the ten thousands because we are able to control the logs in a more efficient way to reduce it.
In an enterprise setting, pricing is reasonable, as many customers use it.
Being an inbuilt solution from AWS, it saves time on installation, setup, and maintenance.
I like its filtering capability and its ability to give the cyber engine insights.
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.
Users can monitor metrics with greater ease, and the tool aids in quickly identifying issues by providing a visual representation of data.
Its alerting feature is effective because it allows me to set thresholds to send an email if a certain threshold is met.
The main benefits I have seen from using Grafana in my day-to-day activities is the visualization of the metrics, specifically Dora Metrics.
Amazon CloudWatch is used for monitoring, tracking logs, and organizing metrics across AWS services. It detects anomalies, sets dynamic alarms, and automates actions to optimize cloud utilization, troubleshoot, and ensure service availability.
Organizations leverage Amazon CloudWatch for collecting and analyzing logs, triggering alerts, and profiling application performance. It's also employed for monitoring bandwidth, virtual machines, Lambda functions, and Kubernetes clusters. Valuable features include seamless integration with AWS, real-time data and alerts, detailed metrics, and a user-friendly interface. It provides robust monitoring capabilities for infrastructure and application performance, log aggregation, and analytics. Users appreciate its scalability, ease of setup, and affordability. Additional key aspects are the ability to create alarms, dashboards, and automated responses, along with detailed insights into system and application health. Room for improvement includes dashboards and UI enhancements for better visualization and customizability, log streaming speed, advanced machine learning and reporting capabilities, pricing, and integration with non-AWS services and databases. Users also seek more real-time monitoring and comprehensive application performance features, and simpler alerts and configuration processes.
What are the most important features?
What benefits and ROI can users expect?
Amazon CloudWatch is implemented across a range of industries, including technology, finance, healthcare, and retail. Technology firms use it to monitor application performance and traffic, while financial organizations leverage it for ensuring compliance and system reliability. Healthcare entities rely on it for maintaining service availability and monitoring data flow, and retail companies utilize it for tracking customer interactions and optimizing server usage.
Grafana is an open-source visualization and analytics platform that stands out in the field of monitoring solutions. Grafana is widely recognized for its powerful, easy-to-set-up dashboards and visualizations. Grafana supports integration with a wide array of data sources and tools, including Prometheus, InfluxDB, MySQL, Splunk, and Elasticsearch, enhancing its versatility. Grafana has open-source and cloud options; the open-source version is a good choice for organizations with the resources to manage their infrastructure and want more control over their deployment. The cloud service is a good choice if you want a fully managed solution that is easy to start with and scale.
A key strength of Grafana lies in its ability to explore, visualize, query, and alert on the collected data through operational dashboards. These dashboards are highly customizable and visually appealing, making them a valuable asset for data analysis, performance tracking, trend spotting, and detecting irregularities.
Grafana provides both an open-source solution with an active community and Grafana Cloud, a fully managed and composable observability offering that packages together metrics, logs, and traces with Grafana. The open-source version is licensed under the Affero General Public License version 3.0 (AGPLv3), being free and unlimited. Grafana Cloud and Grafana Enterprise are available for more advanced needs, catering to a wider range of organizational requirements. Grafana offers options for self-managed backend systems or fully managed services via Grafana Cloud. Grafana Cloud extends observability with a wide range of solutions for infrastructure monitoring, IRM, load testing, Kubernetes monitoring, continuous profiling, frontend observability, and more.
The Grafana users we interviewed generally appreciate Grafana's ability to connect with various data sources, its straightforward usability, and its integration capabilities, especially in developer-oriented environments. The platform is noted for its practical alert configurations, ticketing backend integration, and as a powerful tool for developing dashboards. However, some users find a learning curve in the initial setup and mention the need for time investment to customize and leverage Grafana effectively. There are also calls for clearer documentation and simplification of notification alert templates.
In summary, Grafana is a comprehensive solution for data visualization and monitoring, widely used across industries for its versatility, ease of use, and extensive integration options. It suits organizations seeking a customizable and scalable platform for visualizing time-series data from diverse sources. However, users should be prepared for some complexity in setup and customization and may need to invest time in learning and tailoring the system to their specific needs.
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