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Prometheus vs Stackify: What are the differences?
<Write Introduction here>
Data Collection: Prometheus collects data through a pull mechanism where it scrapes metrics from the target servers. On the other hand, Stackify utilizes agents installed on each server to collect metrics and send them to the central repository.
Data Storage: Prometheus stores data in a time-series database that allows for efficient querying and analysis of historical data. Stackify stores data in a centralized database with built-in features like indexing and search capabilities for faster data retrieval.
Alerting: Prometheus has a robust alerting system that supports complex alerting rules and notifications based on metric conditions. Stackify offers alerting features as well, but it is more focused on application performance monitoring and triggering alerts based on predefined thresholds.
Integration: Prometheus integrates well with various third-party tools and services through its extensive API and ecosystem. Stackify also provides integrations with popular platforms and services but has a more specialized focus on application and server monitoring.
Scalability: Prometheus can scale horizontally by adding more instances to handle increased data collection and monitoring requirements. Stackify is designed to scale vertically by upgrading hardware resources to accommodate growing data volumes and processing needs.
Community Support: Prometheus benefits from a large and active open-source community that contributes to its development and maintenance. In comparison, Stackify has a dedicated support team that provides technical assistance and troubleshooting for users of their monitoring platform.
In Summary, Prometheus and Stackify have differences in data collection methodologies, data storage techniques, alerting capabilities, integration options, scalability approaches, and community support structures.
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 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
Pros of Stackify
- Error tracking8
- Monitoring7
- Easy setup7
- Log management7
- Real-time application health6
- Alerting6
- Application performance6
- exception tracking5
- Application Performance management2
- Good for .NET and Windows Server1
- Great APM with integrated log & exception management1
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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
Cons of Stackify
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