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Amazon CloudWatch vs Prometheus: What are the differences?
Amazon CloudWatch and Prometheus are both popular monitoring services used in the management of cloud infrastructure. Let's explore the key differences between them.
Data Collection: Amazon CloudWatch is designed to collect and monitor metrics from various AWS resources and services, providing a comprehensive view of the cloud environment. Prometheus, on the other hand, is a more flexible solution that can work with any system, allowing users to monitor custom application metrics and resources outside of AWS.
Metric Storage: CloudWatch stores metrics for a maximum of 15 months, providing long-term retention for historical data. Prometheus, however, utilizes a local time series database that retains data for a configurable amount of time, making it more suitable for short-term data storage and analysis.
Alerting and Notifications: CloudWatch includes a built-in alerting mechanism that triggers notifications based on defined thresholds. It can send notifications via email, SNS, or trigger automated actions through CloudWatch Alarms. Prometheus also supports alerting but relies on external integrations such as Alertmanager to handle alert notifications, making it more flexible in terms of notification customization.
Querying and Analysis: When it comes to querying and analysis, Prometheus offers a powerful and flexible query language called PromQL. It allows users to perform complex queries and provides advanced operator functions for metric selection and manipulation. CloudWatch, on the other hand, provides a simpler query interface with a limited set of query functions, making it less flexible in terms of data analysis capabilities.
Scalability and Cost: CloudWatch is a fully managed service provided by AWS, which means it automatically scales with the cloud environment. The pricing for CloudWatch varies based on the number of metrics ingested and API requests made. Prometheus, being an open-source project, requires manual setup and configuration to scale and can be run on-premises or in the cloud. While Prometheus itself is free to use, the overall cost may vary depending on the infrastructure and resources required for its deployment.
Integration Ecosystem: CloudWatch integrates seamlessly with other AWS services, allowing users to monitor and manage the entire AWS infrastructure from a single interface. It also provides built-in integrations with various third-party tools and platforms. Prometheus has a vast ecosystem of exporters and integrations, enabling users to collect metrics from a wide range of systems, services, and frameworks, providing more flexibility in terms of data collection.
In summary, Amazon CloudWatch is a managed service tightly integrated into AWS, providing a comprehensive monitoring solution for AWS resources. Prometheus, on the other hand, is a highly flexible and extensible solution suitable for monitoring custom metrics in both cloud and on-premises environments.
Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:
- Must be able to get custom data from AS400,
- Able to display automation test results,
- System monitoring / Nginx API,
- Able to get data from 3rd parties DB.
Grafana is almost solving all the problems, except AS400 and no database to get automation test results.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.
Is it OK to use Metricbeat for Linux server or can we use Prometheus?
What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?
Regards, Sunil.
If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.
Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.
Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose
We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.
The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.
Pros of Amazon CloudWatch
- Monitor aws resources76
- Zero setup46
- Detailed Monitoring30
- Backed by Amazon23
- Auto Scaling groups19
- SNS and autoscaling integrations11
- Burstable instances metrics (t2 cpu credit balance)5
- HIPAA/PCI/SOC Compliance-friendly3
- Native tool for AWS so understand AWS out of the box1
Pros of Prometheus
- Powerful easy to use monitoring47
- Flexible query language38
- Dimensional data model32
- Alerts27
- Active and responsive community23
- Extensive integrations22
- Easy to setup19
- Beautiful Model and Query language12
- Easy to extend7
- Nice6
- Written in Go3
- Good for experimentation2
- Easy for monitoring1
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Cons of Amazon CloudWatch
- Poor Search Capabilities2
Cons of Prometheus
- Just for metrics12
- Bad UI6
- Needs monitoring to access metrics endpoints6
- Not easy to configure and use4
- Supports only active agents3
- Written in Go2
- TLS is quite difficult to understand2
- Requires multiple applications and tools2
- Single point of failure1
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