Comparing Six Top Observability Software Platforms

Comparing Six Top Observability Software Platforms

When it comes to observability, your organization will have no shortage of options for tools and platforms. Between open source software and proprietary vendors, you should be able to find the right tools to fit your use case, budget and IT infrastructure.

Observability should be cost-efficient, easy to implement and customers should be provided with the best support possible. We aim to provide this with the Open 360™ platform, but organizations should be aware of the full picture of options on the market.

Let’s take a closer look at six of the top observability software platforms as you weigh your decision.


Splunk was effectively the first company to provide centralized log management. They’ve been around since 2003 and are widely known for the advanced analytics and machine learning provided by their widely-adopted platform. 

For observability, Splunk provides a suite of tools including Application Performance Monitoring (APM), Infrastructure Monitoring, IT Service Intelligence, Log Observer Connect, Real User Monitoring, Synthetic Monitoring and On-Call, their automated incident response feature.

Splunk has a reputation for being an expensive service, which in some larger use cases may be warranted. However, it won’t be justified in all use cases and organizations are best served to determine  and their data filtering capabilities are limited. Organizations will pay for data that’s never needed. Plus, with Splunk, organizations will need to identify and remove unneeded data manually. 

Organizations have also reported notoriously slow and unresponsive customer service from Splunk. If you’re comfortable with running an observability apparatus in your organization, Splunk could be an option, but otherwise you may want to consider an option with better support.

New Relic

Providing an all-in-one observability solution, New Relic boasts a platform that contains many observability tools needed for success today.

This includes application monitoring, infrastructure monitoring, browser monitoring, application security, log management and a new generative AI assistant for observability called New Relic Grok.

New Relic takes an approach to data and storage optimization that doesn’t provide the best service for customers. They don’t simplify the process of identifying and de-prioritizing telemetry data that isn’t needed, and they lack a cold storage option that could reduce the cost of log data.


Datadog is a publicly traded cloud monitoring, observability and security company, with products serving many observability and security use cases. Their platform users deploy an agent that ships observability and security data to the Datadog platform, where it is stored and analyzed by the user. From there, customers decide which products they want to analyze the data on Datadog’s SaaS platform. 

Datadog provides support for infrastructure monitoring, log management, APM, and additional monitoring for database, network, synthetic, real user and security.

Datadog, despite its strengths, is expensive, mostly proprietary, lacks key administrative controls including manual data filtering, and customer support has been cited as a weakness.


Over the last decade, Prometheus has emerged as the most prominent open source monitoring tool in the world. It was originally developed by SoundCloud and later released to open source and accepted by the Cloud Native Computing Foundation.

Prometheus collects and stores metrics as time series data, or info stored with timestamp data so users can get a better understanding of metrics at a certain point in time. There’s no upfront cost or vendor lock-in and is a great place for organizations to jump into cloud monitoring quickly.

Prometheus contains the following main features for the collection of metrics:

  • A multi-dimensional data model, where time series data is defined by metric name and key/value dimensions
  • A flexible query language (PromQL)
  • Autonomous single server nodes with no dependency on distributed storage;
  • Data Collection via a pull model over HTTP
  • Time series data pushed to other data destinations and stores via an intermediary gateway
  • Targets discovered via service discovery or static configuration
  • Multiple support modes for graphs and dashboards, although the most commonly-used tool for prometheus metrics visualization is Grafana.
  • Federation-supported both hierarchically and horizontally

You’ll need to use third-party implementations for service discovery, alerting, visualization and export with Prometheus. The platform offers those integrations, but they don’t come natively with Prometheus. Customers often report issues with scaling Prometheus to meet their needs. 


OpenTelemetry (informally called OTEL or OTel) is an observability framework that generates and collects telemetry data from cloud-native applications OpenTelemetry aims to address the full range of observability signals across traces, metrics and logs. While they are working to solve issues around data collection for teams, data storage and analysis is still siloed in OTEL and requires further solutions.

OTEL is a community-driven open source project, which is the result of a merge between OpenTracing and OpenCensus projects. OpenTelemetry offers several components, most notably:

  • APIs and SDKs per programming language for generating and emitting telemetry
  • Collector component to receive, process and export telemetry data
  • OTLP protocol for transmitting telemetry data

OTEL offers SDKs for programming languages including Java, .Net, C++, Golang, Python and more. Some languages also have agents for auto-instrumentation which can help speed up instrumentation work, while others require more labor-intensive manual instrumentation.

As you can see, in many cases you as a customer have two choices when it comes to observability tools. You can use open source software tools that can be cumbersome to manage and scale with no unified way to analyze logs, metrics and traces, or you can use proprietary tools that can be extremely expensive. meets customers in the middle. Our Open 360™ platform helps customers unify data, extract meaningful insights from it quickly, and reduce costs at the same time. We provide support for the best-in-class open source observability tools while also being much less expensive than proprietary solutions. We’re committed to providing customers with a service that only charges them for the data they need and nothing else. provides unified observability for logs, metrics and traces in one platform for complete telemetry analysis and correlation. Open 360 features allow you to: 

  • Automatically discover every service running on your cluster with Easy Connect, while providing the option to collect logs, metrics, and or traces from each one. You can automatically instrument your applications to expose trace data with one click.
  • Unify the most critical telemetry data from Kubernetes-based infrastructure in a single view with Kubernetes 360.
  • Create graphs and dashboards directly from your log files with LogMetrics.
  • Inventory all of your incoming telemetry data to easily determine what you need, and what you don’t with Data Optimization Hub.
  • Collect your logs, metrics, and traces with a single agent with Telemetry Collector.

If you’re interested in seeing how our Open 360 platform for essential observability can meet your needs, sign up for a free trial today.

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