Kibana vs Grafana vs Prometheus vs LogDNA

Data Visualization Tools Compared

In today’s environment, nearly every company needs its own information technology (IT) system to collect vast amount of data, monitor it, store it, and lastly, analyze it to gain insights and mitigate risks. Whether you need this information for troubleshooting, security and threat detection, alerting, or reporting, a centralized log monitoring tool is crucial for your organization. If you don’t know a problem has occurred, it can be difficult — if not impossible — to fix the issue. Log monitoring acts as your eyes and ears to sift through log data and files when manual reviewing is impractical. The visual processing of the results produced by log monitoring is referred to as log visualization. Log visualization enables information gained by log aggregation tools to be displayed in a human-friendly format.

Read more on the Benefits of Log Management

Three popular solutions for log visualization are Kibana, Grafana, and Prometheus. Each one has its own strengths and weaknesses. In general, log visualization solutions vary from plug-ins that beautify existing reports to full logging solutions with comprehensive and already-attractive graphical reporting features. The solution you choose may depend on what solutions you already have in place. Right up front, Kibana is the “K” in ELK. It’s meant to work with the Elastic Stack.

What is Kibana?

Kibana is an open source solution that allows visualization of Elasticsearch data. In this instance, we’ll be referring specifically to log data. Many different types of graphs are available including the traditional bar, line, and pie charts. If you want something that’s not already offered, you can add it in yourself using Vega grammar. This makes Kibana a flexible option that’s both usable without a lot of customization and customizable as your needs grow.

If your organization has several different locations, you’ll be able to use any geospatial data associated with your logs to generate location-based reports. For example, you might use a map of the U.S. to display how many high-priority alerts your system administrator has received in the last month at each location. Visualizing your log file information geographically can provide additional insights into how best to deploy your resources and equipment. Geographical models can also aid in estimating future hiring needs at each location if you are monitoring increases or decreases in your average number of high-priority log events over time.

Kibana supports several other different reporting functions. The time series is one. You can visualize how important log events occur across days as well as during different times of the day. This is another important way to identify trends impacting resources and staffing requirements. You can also analyze relationships between data by combining search engine relevance capabilities with Kibana’s graph exploration features. Finally, you can look deeper into possible abnormal occurrences with machine learning features that don’t need to be closely managed by your IT personnel. If you’re looking for fancy reports, take a look at Canvas as well. Kibana does a great job on detail and, when combined with Canvas, you’ll be able to provide reports that both your technical team and executives will love.

Kibana – Pros & Cons

Pros
  • As the "K" in the ELK stack, Kibana is designed to be used with Elasticsearch. The Elasticsearch functionality provides full support and a lot of horsepower to the Kibana visualization capabilities. LogDNA can help you upgrade your existing Elastic Stack or deploy a new one.
  • A great selection of reporting functions is available without customization.
  • There is an option to customize with Vega grammar if you find you need more.
Cons
  • Kibana must be used with an Elasticsearch node of the same version. Minor steps in the Elasticsearch version may be temporarily used to facilitate the upgrade process.
  • Kibana is not the best for marketing and non-technical, executive-style reporting. Take a look at Canvas for this type of branded graphics with Elasticsearch.

Kibana Setup, Installation, and Configuration

  • The full instructions on setting up Kibana are available on the Elastic.co website.
  • Kibana must be configured and run against an Elasticsearch node with the same version number.
  • If your Elasticsearch instance is running somewhere other than localhost you’ll need to update the Elasticsearch URL in the kibana.yml configuration file.
  • Explore your data through the Discover, Visualize, and Dashboard pages. If you’d like some help, Elastic.co offers an in-depth Kibana tutorial.

What is Grafana?

Grafana is an open source platform used for metrics, data visualization, monitoring, and analysis. Its purpose is to provide a visualization dashboard for displaying Graphite metrics. As such, it’s similar to the relationship between Kibana and Elasticsearch in that Graphite is the data source and Grafana is the visual reporting software. The main difference between these two relationships is that Grafana touts the ability to source from a wide range of data storage, including Elasticsearch. One of the main goals is to bring all of your data together to achieve a better context. This is an essential feature for enterprise organizations with a wide variety of different storage solutions.

The primary focus of Grafana is time series analytics. These analytics are processed with the intention of displaying them on a wide variety of graph options. Heatmaps, bar graphs, and line graphs are all available options for displaying your data in a comprehensible way. An alert system is available to let you know when the metrics you’re actively monitoring wander out of pre-determined thresholds.

Grafana – Pros & Cons

Pros
  • Broad compatibility and support are two of the main project goals. If you plan to hook into multiple data sources and collaborate across different solutions, Grafana is created to make that as straightforward as possible.
  • Grafana includes support for Elasticsearch and Prometheus.
  • It offers a great selection of reporting functions, which are available without customization.
  • An active developer community contributing to the code base ensures new functionality and compatibility options are added on a continuous basis.
Cons
  • Natural complexity occurs with such a wide variety of features and interfaces.
  • Grafana was primarily built to perform time series analytics. Functionality may be limited if you need other reporting types.

How to Install Grafana

  • There are instructions for installing Grafana on a variety of platforms. The process isn’t trivial, but it’s not awful. The documentation is clear and specific.
  • Each data source has its own instructions for linking it into Grafana.
  • Once you’ve followed the instructions, you’ll be able to log in via http://localhost:3000/ or on whichever port you’ve configured Grafana to operate.

What is Prometheus?

Prometheus is first and foremost, a monitoring solution. It’s designed to function best for multi-dimensional data collection and querying. It’s also implemented to be reliable, functioning during outages to assist with diagnostics. To achieve this goal, the Prometheus server is its own standalone unit that doesn’t rely on network storage or external services. As an isolated unit, it doesn’t require a lot of additional infrastructure or software to serve its intended purpose. Grafana and Kibana reach out to incorporate data from across the enterprise. Prometheus stores its own.

As a contained unit, the most likely use case is for Prometheus to be deployed alongside whatever you wish to monitor. This may be limiting for some applications, but it has a lot of upsides for log analysis. High reliability and no reliance on other capabilities allow Prometheus to perform log data analytics on log files of any system on your network without risking the loss of analytic capabilities when you need them most.

Prometheus has their own list of Prometheus Alternatives, which drills down the details of each specific solution they measure themselves against. When comparing it to Grafana and Kibana, we’re primarily looking at its graphing and visual capabilities. Prometheus supports basic graphing functions on its expression browser. It recommends using Grafana for graph support outside of ad-hoc queries and debugging situations.

Prometheus – Pros & Cons

Pros
  • Prometheus has a powerful, self-contained monitoring and alert solution.
  • It is fully functional and highly reliable even when other services on your network or in the cloud are unavailable.
  • Prometheus integrates well with Grafana.
Cons
  • Graphing features are primarily intended for ad-hoc queries and debugging. Prometheus recommends Grafana for comprehensive graphing capabilities.
  • If you’re looking to visualize existing log information that’s already stored in a functioning database, Prometheus would be functionally redundant in some ways. You may still wish to use Prometheus for its high reliability during service outages.

Prometheus Setup, Installation, and Configuration

  • Download the latest release of Prometheus.
  • Extract and run it:
    • tar xvfz prometheus-*.tar.gz
      cd prometheus-*
  • Find complete Prometheus documentation, which covers everything you’ll need to do to get it up and running.
  • Information about how to integrate with other services is available on the website. This information is not as comprehensive as the installation documentation. Some integration details are missing and there are others still in progress.
  • TLS connections to Prometheus aren’t supported, but they can be used to connect from Prometheus to what the website calls “scrape targets.”

Key Differences and Use Cases

Kibana, Grafana, and Prometheus all have their own strengths and weaknesses. At the end of the day, each has a different use case.

  • Kibana is great for environments that rely on Elasticsearch for their log data storage. Using the ELK stack is a tried and true method of managing your log file information.
  • Grafana has a broader appeal and a wider array of support options. Using it won’t limit you to a single type of database. If you need more than Kibana offers and don’t need a high-reliability solution, Grafana is a great choice.
  • Prometheus is a high-reliability, all-in-one system for those who need that capability.

Leaning toward Kibana is good for small organizations or large, homogeneous networks using Elasticsearch. Grafana is great for organizations ranging from large to small and shines brightly when the need arises to support many different data sources. Prometheus’ high reliability functions well in any situation where that need is present. For a better visual display of Prometheus’ data, it’s a great idea to use both Grafana and Prometheus. That way you can benefit from the performance of Prometheus while benefitting from the visual capabilities Grafana is known for providing.

Cost of Implementation

The highest cost solution for implementation and maintenance will be Prometheus. Prometheus isn’t a cloud service. It will need to be co-located with whatever it’s monitoring. Your own team will need to manage any deployments, maintenance, and upgrades necessary to keep it up and running. The cost will vary widely depending on how many instances of Prometheus you deploy. It is 100-percent open source and its development is driven by the community that supports it. You won’t have to deal with licensing fees. There may be times when you need to contact someone who is familiar with Prometheus to help your IT team come up to speed on its management and capabilities. Grafana Cloud comes with a Prometheus endpoint from Grafana.com.

Grafana can be deployed in your enterprise or used as a cloud service. There are many options available for cloud hosting. It’s a good idea to shop around and see which rates are best for your organization. Grafana itself is flexible. You’ll find it paired with different underlying database solutions for that reason. For example, Corlysis is a named solution based on Grafana with the InfluxDB solution.

Kibana is a free, open-source tool that will be your least expensive choice in almost all cases where Elasticsearch is already present. If you’re a small organization, on a tight budget, or both, Kibana is a great option. Kibana works best for large organizations, too, as long as you’re looking to create visuals based only on Elasticsearch stored data. If you’re looking for an alternative to managing your own ELK setup, LogDNA is the best Elastic alternative for upgrading your Elastic Stack. LogDNA provides both a cloud service option and an on-premises option depending on your specific needs.

The LogDNA Difference

Whether you need an on-premise or cloud-based logging solution, LogDNA has you covered. LogDNA provides a full suite of tools, from log aggregation, monitoring, and analysis, to visualizations and reporting features with full scalability while providing frustration-free setup and configuration.

Exceptionally suited to enterprise-wide integration, you can centralize log data from unlimited hosts, sources, applications, and platforms into a single pane.

While data visualizations are an important part of log management, LogDNA also provides the search, filtering, alerts, and graphs to help you gain real-time insights, as well as streamline your DevOps team and mitigate risks. It’s also fully compliant and secure.

The LogDNA solution comes with 24/5 support and a modern infrastructure. Both help keep costs down while still providing top quality service and support. You’ll be in control of costs with flexible deployment and ingestion controls with this hassle-free solution. Contact LogDNA today through LogDNA.com to find out more, or sign up for the free plan, or a free trial with no credit card required.