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ElastAlert vs Prometheus: What are the differences?
Key Differences between ElastAlert and Prometheus
ElastAlert and Prometheus are two popular monitoring and alerting systems used in the field of IT operations. While they both serve similar purposes, there are some key differences that set them apart.
Architecture: ElastAlert is an open-source framework that integrates with Elasticsearch, providing the ability to create complex rules and trigger alerts based on events in real-time. On the other hand, Prometheus is a standalone monitoring system that uses a pull-based model to collect and process metrics from various targets.
Data Collection: ElastAlert primarily gathers data from Elasticsearch, making it well-suited for monitoring and analyzing log data. Prometheus, on the other hand, supports a multitude of data sources, including HTTP endpoints, service discovery mechanisms, and various third-party integrations, making it more versatile in terms of data collection.
Alerting Capabilities: ElastAlert offers a wide range of alerting options, including email, Slack, and JIRA integration. It provides fine-grained control over alerting rules and can leverage machine learning algorithms for anomaly detection. On the contrary, Prometheus focuses on providing alerting based on metrics, with support for integrations with tools like PagerDuty and VictorOps.
Metric Processing: ElastAlert allows for complex event processing based on Elasticsearch queries, enabling powerful rule creation. Prometheus, on the other hand, employs PromQL, a powerful query language specifically designed for analyzing time-series data, enabling developers to perform complex calculations and aggregations.
Scalability: ElastAlert's scalability primarily depends on the underlying Elasticsearch cluster's scalability. As Elasticsearch is horizontally scalable, ElastAlert can handle large amounts of data. In contrast, Prometheus is known for its scalability as it is designed to handle high volumes of metric data and has built-in support for sharding and load balancing.
Community Support and Ecosystem: Both ElastAlert and Prometheus have active and growing communities. However, Prometheus has a broader ecosystem of exporters, libraries, and third-party integrations, making it easier to extend and integrate with other tools in the monitoring landscape. ElastAlert, being more Elasticsearch-centric, has a smaller ecosystem comparatively.
In Summary, ElastAlert and Prometheus differ in terms of architecture, data collection capabilities, alerting options, metric processing mechanisms, scalability, and community support.
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.
Pros of ElastAlert
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 ElastAlert
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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