Elasticsearch vs Prometheus vs Zabbix

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Elasticsearch

25.4K
19.1K
+ 1
1.6K
Prometheus

2.5K
2.9K
+ 1
235
Zabbix

526
731
+ 1
57
Advice on Elasticsearch, Prometheus, and Zabbix
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 373.1K views
Needs advice
on
Prometheus
Graphite
and
Grafana

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.

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Replies (1)
Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 172.5K views

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.

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Sunil Chaudhari
Needs advice
on
Prometheus
and
Metricbeat

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.

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Replies (2)
Matthew Rothstein
Recommends
Prometheus

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.

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Recommends
Instana

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

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Needs advice
on
Zabbix
and
Centreon

My team is divided on using Centreon or Zabbix for enterprise monitoring and alert automation. Can someone let us know which one is better? There is one more tool called Datadog that we are using for cloud assets. Of course, Datadog presents us with huge bills. So we want to have a comparative study. Suggestions and advice are welcome. Thanks!

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Replies (4)
Geoffrey Timmerman
Systems Engineer at Simac · | 6 upvotes · 190.9K views
Recommends
Zabbix
at

I work at Volvo Car Corporation as a consultant Project Manager. We have deployed Zabbix in all of our factories for factory monitoring because after thorough investigation we saw that Zabbix supports the wide variety of Operating Systems, hardware peripherals and devices a Car Manufacturer has.

No other tool had the same amount of support onboard for our production environment and we didn't want to end up using a different tool again for several areas. That is the major strong point about Zabbix and it's free of course. Another strong point is the documentation which is widely available; Zabbix Youtube channel with tutorial video's, Zabbix share which holds free templates, the Zabbix online documentation and the Zabbix forum also helped us out quite a bit. Deployment is quite easy since it uses templates, so almost all configuration can be done on server side.

To conclude, we are really pleased with the tool so far, it helped us detect several causes of issues that were a pain to solve in the past.

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Recommends
Centreon

Centreon is part of the Nagios ecosystem, meaning there is a huge number of resources you may find around in the community (plugins, skills, addons). Zabbix monitoring paradigms are totally different from Centreon. Centreon plugins have some kind of intelligence when they are launched, where Zabbix monitoring rules are configured centrally with the raw data collected. Testing both will help you understand :) Users used to say Centreon may be faster for setup and deployment. And in the end, both are full of monitoring features. Centreon has out of the box a full catalog of probes from cloud to the edge https://www.centreon.com/en/plugins-pack-list/ As soon as you have defined your monitoring policies and template, you can deploy it fast through command line API or REST API. Centreon plays well in the ITSM, Automation, AIOps spaces with many connectors for Prometheus, ServiceNow, GLPI, Ansible, Chef, Splunk, ... The polling server mode is one of the differentiators with Centreon. You set up remote server(s) and chose btw multiple information-exchange mechanisms. Powerful and resilient for remote, VPN, DMZ, satellite networks. Centreon is a good value for price to do a data collection (availability, performance, fault) on a wide range of technologies (physical, legacy, cloud). There are pro support and enterprise version with dashboards and reporting. IT Central Station gathers many user feedback you can rely on both Centreon & Zabbix https://www.itcentralstation.com/products/centreon-reviews  

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muutech
at Muutech Monitoring Solutions, S.L. · | 3 upvotes · 190K views
Recommends
Zabbix

We highly recommend Zabbix. We have used it to build our own monitoring product (available on cloud -like datadog- or on premise with support) because of its flexibility and extendability. It can be easily integrated with the powerful dashboarding and data aggregation of Grafana, so it is perfect. All configuration is done via web and templates, so it scales well and can be distributed via proxies. I think there also more companies providing consultancy in Zabbix (like ours) than Centreon and community is much wider. Also Zabbix roadmap and focus (compatibility with Elasticsearch, Prometheus, TimescaleDB) is really really good.

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Recommends
Kamon
at

Hi Vivek, what's your stack? If huge monitoring bills are your concern and if you’re using a number of JVM languages, or mostly Scala / Akka, and would like “one tool to monitor them all”, Kamon might be the friendliest choice to go for.

Kamon APM’s major benefit is it comes with a built-in dashboard for the most important metrics to monitor, taking the pain of figuring out what to monitor and building your own dashboards for weeks out of the monitoring.

https://kamon.io/apm/

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Rana Usman Shahid
Chief Technology Officer at TechAvanza · | 5 upvotes · 158.6K views
Needs advice
on
Firebase
Elasticsearch
and
Algolia

Hey everybody! (1) I am developing an android application. I have data of around 3 million record (less than a TB). I want to save that data in the cloud. Which company provides the best cloud database services that would suit my scenario? It should be secured, long term useable, and provide better services. I decided to use Firebase Realtime database. Should I stick with Firebase or are there any other companies that provide a better service?

(2) I have the functionality of searching data in my app. Same data (less than a TB). Which search solution should I use in this case? I found Elasticsearch and Algolia search. It should be secure and fast. If any other company provides better services than these, please feel free to suggest them.

Thank you!

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Replies (2)
Josh Dzielak
Co-Founder & CTO at Orbit · | 7 upvotes · 120.4K views
Recommends
Algolia

Hi Rana, good question! From my Firebase experience, 3 million records is not too big at all, as long as the cost is within reason for you. With Firebase you will be able to access the data from anywhere, including an android app, and implement fine-grained security with JSON rules. The real-time-ness works perfectly. As a fully managed database, Firebase really takes care of everything. The only thing to watch out for is if you need complex query patterns - Firestore (also in the Firebase family) can be a better fit there.

To answer question 2: the right answer will depend on what's most important to you. Algolia is like Firebase is that it is fully-managed, very easy to set up, and has great SDKs for Android. Algolia is really a full-stack search solution in this case, and it is easy to connect with your Firebase data. Bear in mind that Algolia does cost money, so you'll want to make sure the cost is okay for you, but you will save a lot of engineering time and never have to worry about scale. The search-as-you-type performance with Algolia is flawless, as that is a primary aspect of its design. Elasticsearch can store tons of data and has all the flexibility, is hosted for cheap by many cloud services, and has many users. If you haven't done a lot with search before, the learning curve is higher than Algolia for getting the results ranked properly, and there is another learning curve if you want to do the DevOps part yourself. Both are very good platforms for search, Algolia shines when buliding your app is the most important and you don't want to spend many engineering hours, Elasticsearch shines when you have a lot of data and don't mind learning how to run and optimize it.

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Mike Endale
Recommends
Cloud Firestore

Rana - we use Cloud Firestore at our startup. It handles many million records without any issues. It provides you the same set of features that the Firebase Realtime Database provides on top of the indexing and security trims. The only thing to watch out for is to make sure your Cloud Functions have proper exception handling and there are no infinite loop in the code. This will be too costly if not caught quickly.

For search; Algolia is a great option, but cost is a real consideration. Indexing large number of records can be cost prohibitive for most projects. Elasticsearch is a solid alternative, but requires a little additional work to configure and maintain if you want to self-host.

Hope this helps.

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Mat Jovanovic
Head of Cloud at Mats Cloud · | 3 upvotes · 331K views
Needs advice
on
Datadog
Grafana
and
Prometheus

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.

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Replies (2)
Recommends
Datadog

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.

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Lucas Rincon
Recommends
Instana

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/

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Decisions about Elasticsearch, Prometheus, and Zabbix
Long Nguyen
Engineering Director at Ecommerce Startup · | 2 upvotes · 4.5K views

Our primary source of monitoring and alerting is Prometheus, also have APM in Elasticsearch, for all incidents trigger we route to Opsgenie. Kubernetes is for Deployment, RabbitMQ is for Eventbus, Golang in Backend and Postgresql for Database.

We use Holistics to log all segmentation for our tracker.

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Pros of Elasticsearch
Pros of Prometheus
Pros of Zabbix
  • 321
    Powerful api
  • 311
    Great search engine
  • 231
    Open source
  • 213
    Restful
  • 200
    Near real-time search
  • 96
    Free
  • 83
    Search everything
  • 54
    Easy to get started
  • 45
    Analytics
  • 26
    Distributed
  • 6
    Fast search
  • 5
    More than a search engine
  • 3
    Great docs
  • 3
    Awesome, great tool
  • 3
    Easy to scale
  • 2
    Intuitive API
  • 2
    Great piece of software
  • 2
    Fast
  • 2
    Nosql DB
  • 2
    Easy setup
  • 2
    Highly Available
  • 2
    Document Store
  • 2
    Great customer support
  • 1
    Reliable
  • 1
    Not stable
  • 1
    Potato
  • 1
    Open
  • 1
    Github
  • 1
    Elaticsearch
  • 1
    Actively developing
  • 1
    Responsive maintainers on GitHub
  • 1
    Ecosystem
  • 1
    Scalability
  • 0
    Easy to get hot data
  • 0
    Community
  • 45
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
    Alerts
  • 22
    Active and responsive community
  • 21
    Extensive integrations
  • 19
    Easy to setup
  • 12
    Beautiful Model and Query language
  • 7
    Easy to extend
  • 6
    Nice
  • 3
    Written in Go
  • 2
    Good for experimentation
  • 1
    Easy for monitoring
  • 16
    Free
  • 7
    Alerts
  • 5
    Service/node/network discovery
  • 4
    Templates
  • 4
    Base metrics from the box
  • 3
    Multi-dashboards
  • 3
    SMS/Email/Messenger alerts
  • 2
    Supports Graphs ans screens
  • 2
    Support proxies (for monitoring remote branches)
  • 2
    Grafana plugin available
  • 1
    API available for creating own apps
  • 1
    Templates free available (Zabbix Share)
  • 1
    Works with multiple databases
  • 1
    Supports large variety of Operating Systems
  • 1
    Supports multiple protocols/agents
  • 1
    Complete Logs Report
  • 1
    Advanced integrations
  • 1
    Supports JMX (Java, Tomcat, Jboss, ...)
  • 1
    Perform website checking (response time, loading, ...)

Sign up to add or upvote prosMake informed product decisions

Cons of Elasticsearch
Cons of Prometheus
Cons of Zabbix
  • 6
    Resource hungry
  • 6
    Diffecult to get started
  • 5
    Expensive
  • 3
    Hard to keep stable at large scale
  • 11
    Just for metrics
  • 6
    Needs monitoring to access metrics endpoints
  • 6
    Bad UI
  • 3
    Not easy to configure and use
  • 2
    Requires multiple applications and tools
  • 2
    Written in Go
  • 2
    Supports only active agents
  • 1
    TLS is quite difficult to understand
  • 5
    The UI is in PHP
  • 2
    Puppet module is sluggish

Sign up to add or upvote consMake informed product decisions

What is Elasticsearch?

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

What is Prometheus?

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

What is Zabbix?

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

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What are some alternatives to Elasticsearch, Prometheus, and Zabbix?
Datadog
Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Solr
Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.
Lucene
Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Algolia
Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.
See all alternatives