3 key differences of open source observability tools vs. proprietary observability tools

Enterprise adoption and confidence in open-source software (OSS) has been rising steadily in the U.S. and around the world. In 10 years of tracking open source, the 2022 Octoverse report found more than 90% of companies use open source, and 97% of applications use open source software. A full 96% of scanned codebases assessed in the 2023 Open Source Security and Risk Analysis Report contained open source.

Open source software is distributed with its source code so organizations can use, modify, and distribute it as part of new and existing applications. Because open source software is often viewed as collaborative, developers also trust it. Open source received the highest perceived positive and proven sentiment marks of all emerging technologies from more than 2,000 developers in the most recent Stack Overflow survey.

Companies are investing in open source because it’s driving innovation, improved customer experiences, and overall digital transformation, according to 2023 IDC Research. More than half (61%) of IDC survey respondents across 11 Asia-Pacific countries rated the performance of OSS as superior compared to proprietary software.

Open source observability is software that is built on open source code and integrates with other open source observability tooling, such as Prometheus — the de facto standard for open source metrics-based monitoring — and OpenTelemetry, an observability framework for generating, collecting, and transmitting telemetry data from cloud native software. Open source observability software also can look after open source environments, overseeing the management of it through dashboards and other controls.

Observability has become more important to development and operations teams as they adopt cloud native environments — comprised of microservices, containers, and Kubernetes. That’s because while cloud native technologies make applications easier to build, run, deploy, and scale, they also generate more data that’s ephemeral and challenging to harness for triaging and finding root-causes when applications underperform or become unreliable. Recently, organizations have come to rely on observability tools to gain deeper visibility into systems, applications, and components with the business goal of rapid remediation should something go awry. The right observability platform allows teams to proactively address problems before they negatively impact customer or employee experience.

With connected open source observability, teams simplify the aggregation and visualization of the most relevant data from their applications and infrastructure in a distributed environment. Moreover, they gain context into all of their data without having to pay extra to take advantage of high cardinality.

While early monitoring solutions typically designed before the dynamic and interconnected nature of cloud native architectures are inflexible, and thus become more costly over time. Observability solutions that operate seamlessly with OSS observability tooling in cloud native environments provide tremendous flexibility and other significant benefits to enterprises.

Compatibility with open source observability tooling ensures organizations:

• Avoid vendor lock-in – Users can easily keep the right data, gain accurate results, and migrate between compatible solutions on the market; incompatible systems make this challenging, if not impossible.
• Avoid user confusion and breakage – Users aren’t surprised or confused by a solution that doesn’t perform as expected.
• Avoid ecosystem fragmentation – Users benefit from vendors working together on software tools, documentation, and resources related to the open source implementation in place in a compatible ecosystem, helping prevent teams from missing important clues before an expensive outage due to broken monitoring or alerting.
• Lower costs with accurate comparisons – Organizations can reduce licensing costs by combining the use of different open source observability tools, recognizing performance and cost comparisons between vendors are only reliable when teams compare similar, compatible feature sets.
• Stay agile – Users enjoy greater flexibility with the ability to expand tool set options because of compatible open source technology.

There are three primary differences between open source observability tools and proprietary observability platforms.

1. 1. Commitment to compatibility

The best cloud native observability platforms on the market work seamlessly with the most popular open source observability tooling, including Prometheus and OpenTelemetry. Although these light-weight metrics and observability solutions offer quick time to value in cloud native environments, scaling up infrastructure and microservices requires adding multiple instances. That effort, in turn, introduces high availability and data locality issues that create significant management overhead. That’s why managed cloud native open source observability solutions are committed to compatibility. They interoperate and cut out complexity because the vendors offering them recognize the power of open source and prioritize compatibility with critical open source tool interfaces such as the Prometheus PromQL query language, metrics ingestion protocols, and alerting engines.

Proprietary observability platform vendors have not made equivalent compatibility and interoperability commitments. As a result, proprietary vendor implementations not only can cause a great deal of user confusion, but they also ensure non-portable observability solutions and non-standard application instrumentation solutions that grow into architectural pain for organizations over time.

2. 2. Range of responsibility

Because most were architected before widespread cloud adoption, traditional infrastructure and application performance monitoring (APM) tools often concentrate on being best at delivering one output — logs (historical event records), metrics (numerical records of events), or traces (request behavior tracking). If a solution can produce all three, the data either may be skewed because the vendor has decided what data is most important or overwhelming because the proprietary tool collects so much data it is difficult — not to mention costly — for users to determine what is most important.

In contrast, open source compatible observability tools empower users to tame data growth and control costs while still enjoying consistent availability and reliability of their platform. Many are hosted or managed metrics and observability SaaS offerings that ensure smooth transitions between open source deployments.

3. 3. Focus on business outcomes versus straight data

While proprietary solutions’ range of responsibility (see #2) is limited to telemetry generation, open source observability solutions offer unlimited possibilities because they lean into answering key operational questions to improve results:

• How quickly is someone notified when there is a problem—before or after a negative customer or employee experience?
• How fast and easily can a team member triage the problem and understand its impact?
• How does an engineer find the underlying cause so they can fix the problem?

With open source observability, organizations can remediate faster because users quickly:

1. 1. Know there’s a problem – With open source observability, team members can go directly from an alert to remediation – even rolling a deployment back, as needed — without customers even knowing there was an issue.
   2. Triage the problem to prevent additional negative consequences – Open source observability allows engineers to work quickly with the highest-quality data to highlight and contextualize information for fastest diagnosis. In this stage, on-call engineers can effectively determine the severity of an issue and the best course of action to resolve it without waking everyone up at night or on weekends unless it’s absolutely necessary.
   3. Understand the problem and dive into the root cause — Open source observability gives engineers a direct path into understanding issues (as well as upstream and downstream effects) because it automatically links metrics and traces. Seeing trends and outliers in dashboards makes it easier to solve complex challenges, too.

At first glance, proprietary observability platforms can appear both easier to use and less expensive than open source observability platforms. However, first impressions can be deceiving. Organizations should be sure they are making accurate comparisons when evaluating open source against proprietary observability tools.

Every checklist should compare:

• Features and capabilities – Be sure to assess comparable features and consider the extra agility that comes from technologies such as dashboards that work across a large ecosystem of compatible open source solutions versus a proprietary solution.
• Scalability – Understand not only how large and fast a solution can scale, but also the costs associated with scaling a proprietary offering in a cloud native environment.
• Internal knowledge – Recognize what skills existing engineers may have that are portable in the open source world and what financial burdens are associated with skills to run proprietary solutions.
• “Soft costs” of hiring staff – Understand the expenses, other than direct labor, that it takes to run open source versus proprietary observability. Be sure to factor in whether solutions offer enterprise-grade service and support as part of the offering or as an additional fee.
• Community support – Be sure to factor in the collaboration and cross-training benefits of the open source community that may not be available with a proprietary solution.

A SaaS-based cloud native observability platform committed to open source compatibility, Chronosphere benefits organizations by driving innovation and improving user choice. Today, enterprises such as Robinhood and Abnormal Security rely on proven Chronosphere as part of their open source strategies.

With Chronosphere, organizations gain robust observability without vendor lock-in. Users aren’t surprised or confused because the platform performs as expected. Moreover, Chronosphere collaborates with open source ecosystem partners to decrease customer time from issue to remediation — without breaking budgets.

The Chronosphere platform reduces customer observability data volumes by an average of 48% while improving key metrics such as time to detection and time to remediation. It includes capabilities that benefit central observability teams and makes the lives of engineering teams easier by streamlining workflows, accelerating remediation, and improving both engineer efficiency and quality of life. In real-world customer environments, Chronosphere is reducing data volumes by 89% and giving organizations 99.99% availability.

An open source-compatible cloud native observability solution like Chronosphere can deliver tremendous competitive benefits to organizations of all types and sizes.

Learn more about open source observability and Chronosphere with a demo today.