11 Key Observability Trends for 2022 - Part 2

Buddy Brewer
New Relic
Learn more about New Relic

These are the trends that will set up your engineers and developers to deliver amazing software that powers amazing digital experiences that fuel your organization's growth in 2022 — and beyond. This is Part 2.

Start with: 11 Key Observability Trends for 2022 - Part 1

6. Usage-based pricing tips the scales in the customer's favor

The pricing structures of many monitoring tools actually discourage IT leaders and engineers and developers from ingesting all of their data because their pricing is confusing, difficult to predict and scale, and generally just too expensive. As a result, organizations compromise on visibility. In fact, according to the Observability Forecast, 60% of global respondents still monitor telemetry data at the application level only, leaving massive amounts of data unmonitored in their software stack.

The move to modern observability and increasing its adoption includes shifting from legacy subscriptions to usage-based consumption and pricing models that align with customer success. With modern consumption-based pricing, organizations get full visibility into all of their telemetry, and only pay for what they use. With digital businesses relying on increasingly complex software systems, IT leaders will start demanding this pricing model from their observability vendors because it's easy to understand, predict, and scale. Plus, usage-based pricing will be given preference as it promises to remove upfront guesswork on usage and the shelfware frustrations and overage penalties that often follow.

How to Seize the Trend

Learn how you might be able to achieve even more value while making your observability platform (and your organization's data) available to more engineers and developers across the software lifecycle. It's a great first step to seize all of the first six trends of this Observability Trends report.

7. Observability shifts from "it's complicated" to an "open" relationship

Having a variety of tools to choose from creates challenges in telemetry data collection. Organizations find themselves managing multiple libraries for logging, metrics, and traces, with each vendor having its own APIs, SDKs, agents, and collectors. An open source, community-driven approach to observability will gain steam in 2022 to remove unnecessary complications by tapping into the latest advancements in observability practice.

With continued innovation and investment, observability will work out-of-the-box by default and use open standards to make it even more accessible to all. In fact, Gartner predicts that by 2025, 70% of new cloud-native application monitoring will use open source instrumentation rather than vendor-specific agents for improved interoperability. Open source standards such as OpenTelemetry and OpenMetrics are converging in the industry, preventing vendor lock-in and bringing us a step closer to unified observability.

How to Seize the Trend

Encourage your engineering teams to tap into open source technologies like OpenTelemetry to advance their observability practice and capabilities.

8. The rising tide of Kubernetes and containers floats observability boats too

With the Observability Forecast highlighting that 88% of IT decision makers are exploring Kubernetes, with 25% of respondents conducting research, 25% evaluating, 29% in development, and 10% in production, the popularity of Kubernetes continues to explode. This growth also brings challenges and gaps from the necessary cultural shift to technology trends and advancements. As the next wave of microservices and more stateful applications are deployed on Kubernetes and container-based platforms, there is a need for more visibility into operations, as well as tools for self-defense and self-healing against malicious applications (both intentional and inadvertent).

Looking forward, as teams use more microservices and serverless architectures, they will reduce the amount of interaction with the underlying infrastructure. This allows more focus on the application and other business needs, and will lead to an improved developer experience in 2022.

How to Seize the Trend

It's no secret that most Kubernetes monitoring solutions, including amazing tools like Prometheus, are designed primarily for operations teams, which made sense in the early days. However, that's not the case anymore. When your team is looking for an actionable observability platform, make sure they request tools that are purpose-built for developers to identify performance bottlenecks faster with code-level insights. This will help your engineering teams to seamlessly drill down into both application-level and infrastructure-level behavior, so they can correlate the impact that application changes are having on the infrastructure and vice versa.

9. Increasing adoption of a DevOps mindset for observability

By adopting a DevOps mindset and embracing agile rather than waterfall development, engineering teams will be able to shift from a culture of blame and finger-pointing to one of empathy and ongoing improvement. This will position engineers and developers to release better software, faster, and meet the growing expectations of their organizations. Just as digital companies have updated the way they plan, build, deploy, and operate software, they will now look to modernize their approach to monitoring that software with observability tools that benefit not only the DevOps team, but the entire organization.

How to Seize the Trend

With increasing pressure mounting on engineering teams across industries, observability is key to delivering a positive user experience in the face of ever-expanding software applications. Adopting a DevOps culture will enable your teams to cut through the noise and focus on the performance issues that have the biggest impact on your business, customers, and employees.

10. Observability cultivates collaboration among engineering teams

Observability is quickly becoming the industry gold standard to help software engineering teams and developers through the inevitable times when something goes wrong in the continuous integration/continuous deployment (CI/CD) pipeline. The reasons are clear: When the CI/CD pipeline is observable, engineering teams have more confidence in their code, and they can move faster to implement fixes when needed. And when observability platforms enable collaboration on code directly within the developer environment (IDE), asking questions for better understanding, highlighting potential errors, and partnering on code becomes second nature — as does delivering even better outcomes as a matter of engineering practice.

Looking forward, modern observability will enable and cultivate a culture of collaboration across software engineering and development disciplines by allowing teams to better collaborate. The result will be stronger teams, procedures, and alert systems that improve the way engineers handle monitoring and incident detection throughout the software lifecycle.

How to Seize the Trend

As you build your observability team in today's distributed workplace, make sure all your SREs and developers have access to your observability tools. This will enable all your engineers around the world to have access to real-time data for decision making, and make cross-functional collaboration more efficient and easier.

11. Observability continues to improve service and reliability

As organizations work in a world that increasingly relies more on digital services — due to COVID-19 or otherwise — the data from these applications can give us greater detail into real-world performance. For example, an increase in web traffic or application demand will usually be linked to higher levels of transactions and business. This increase can be seen and tracked across application components, but it can also be seen in revenue too. That's why observability data has a greater purpose beyond just showing us how well our app components are performing over time. Instead, moving forward this data will be used to improve both the ability to handle risks and show where business results are affected.

How to Seize the Trend

It's far more common today for your engineering teams to tackle service and reliability issues on a regular basis. When planning for next year's IT infrastructure, think about observability from a reliability perspective. This will ensure that your applications are better able to handle issues like a cloud outage or service failure.

Buddy Brewer is GVP and GM at New Relic

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11 Key Observability Trends for 2022 - Part 2

Buddy Brewer
New Relic
Learn more about New Relic

These are the trends that will set up your engineers and developers to deliver amazing software that powers amazing digital experiences that fuel your organization's growth in 2022 — and beyond. This is Part 2.

Start with: 11 Key Observability Trends for 2022 - Part 1

6. Usage-based pricing tips the scales in the customer's favor

The pricing structures of many monitoring tools actually discourage IT leaders and engineers and developers from ingesting all of their data because their pricing is confusing, difficult to predict and scale, and generally just too expensive. As a result, organizations compromise on visibility. In fact, according to the Observability Forecast, 60% of global respondents still monitor telemetry data at the application level only, leaving massive amounts of data unmonitored in their software stack.

The move to modern observability and increasing its adoption includes shifting from legacy subscriptions to usage-based consumption and pricing models that align with customer success. With modern consumption-based pricing, organizations get full visibility into all of their telemetry, and only pay for what they use. With digital businesses relying on increasingly complex software systems, IT leaders will start demanding this pricing model from their observability vendors because it's easy to understand, predict, and scale. Plus, usage-based pricing will be given preference as it promises to remove upfront guesswork on usage and the shelfware frustrations and overage penalties that often follow.

How to Seize the Trend

Learn how you might be able to achieve even more value while making your observability platform (and your organization's data) available to more engineers and developers across the software lifecycle. It's a great first step to seize all of the first six trends of this Observability Trends report.

7. Observability shifts from "it's complicated" to an "open" relationship

Having a variety of tools to choose from creates challenges in telemetry data collection. Organizations find themselves managing multiple libraries for logging, metrics, and traces, with each vendor having its own APIs, SDKs, agents, and collectors. An open source, community-driven approach to observability will gain steam in 2022 to remove unnecessary complications by tapping into the latest advancements in observability practice.

With continued innovation and investment, observability will work out-of-the-box by default and use open standards to make it even more accessible to all. In fact, Gartner predicts that by 2025, 70% of new cloud-native application monitoring will use open source instrumentation rather than vendor-specific agents for improved interoperability. Open source standards such as OpenTelemetry and OpenMetrics are converging in the industry, preventing vendor lock-in and bringing us a step closer to unified observability.

How to Seize the Trend

Encourage your engineering teams to tap into open source technologies like OpenTelemetry to advance their observability practice and capabilities.

8. The rising tide of Kubernetes and containers floats observability boats too

With the Observability Forecast highlighting that 88% of IT decision makers are exploring Kubernetes, with 25% of respondents conducting research, 25% evaluating, 29% in development, and 10% in production, the popularity of Kubernetes continues to explode. This growth also brings challenges and gaps from the necessary cultural shift to technology trends and advancements. As the next wave of microservices and more stateful applications are deployed on Kubernetes and container-based platforms, there is a need for more visibility into operations, as well as tools for self-defense and self-healing against malicious applications (both intentional and inadvertent).

Looking forward, as teams use more microservices and serverless architectures, they will reduce the amount of interaction with the underlying infrastructure. This allows more focus on the application and other business needs, and will lead to an improved developer experience in 2022.

How to Seize the Trend

It's no secret that most Kubernetes monitoring solutions, including amazing tools like Prometheus, are designed primarily for operations teams, which made sense in the early days. However, that's not the case anymore. When your team is looking for an actionable observability platform, make sure they request tools that are purpose-built for developers to identify performance bottlenecks faster with code-level insights. This will help your engineering teams to seamlessly drill down into both application-level and infrastructure-level behavior, so they can correlate the impact that application changes are having on the infrastructure and vice versa.

9. Increasing adoption of a DevOps mindset for observability

By adopting a DevOps mindset and embracing agile rather than waterfall development, engineering teams will be able to shift from a culture of blame and finger-pointing to one of empathy and ongoing improvement. This will position engineers and developers to release better software, faster, and meet the growing expectations of their organizations. Just as digital companies have updated the way they plan, build, deploy, and operate software, they will now look to modernize their approach to monitoring that software with observability tools that benefit not only the DevOps team, but the entire organization.

How to Seize the Trend

With increasing pressure mounting on engineering teams across industries, observability is key to delivering a positive user experience in the face of ever-expanding software applications. Adopting a DevOps culture will enable your teams to cut through the noise and focus on the performance issues that have the biggest impact on your business, customers, and employees.

10. Observability cultivates collaboration among engineering teams

Observability is quickly becoming the industry gold standard to help software engineering teams and developers through the inevitable times when something goes wrong in the continuous integration/continuous deployment (CI/CD) pipeline. The reasons are clear: When the CI/CD pipeline is observable, engineering teams have more confidence in their code, and they can move faster to implement fixes when needed. And when observability platforms enable collaboration on code directly within the developer environment (IDE), asking questions for better understanding, highlighting potential errors, and partnering on code becomes second nature — as does delivering even better outcomes as a matter of engineering practice.

Looking forward, modern observability will enable and cultivate a culture of collaboration across software engineering and development disciplines by allowing teams to better collaborate. The result will be stronger teams, procedures, and alert systems that improve the way engineers handle monitoring and incident detection throughout the software lifecycle.

How to Seize the Trend

As you build your observability team in today's distributed workplace, make sure all your SREs and developers have access to your observability tools. This will enable all your engineers around the world to have access to real-time data for decision making, and make cross-functional collaboration more efficient and easier.

11. Observability continues to improve service and reliability

As organizations work in a world that increasingly relies more on digital services — due to COVID-19 or otherwise — the data from these applications can give us greater detail into real-world performance. For example, an increase in web traffic or application demand will usually be linked to higher levels of transactions and business. This increase can be seen and tracked across application components, but it can also be seen in revenue too. That's why observability data has a greater purpose beyond just showing us how well our app components are performing over time. Instead, moving forward this data will be used to improve both the ability to handle risks and show where business results are affected.

How to Seize the Trend

It's far more common today for your engineering teams to tackle service and reliability issues on a regular basis. When planning for next year's IT infrastructure, think about observability from a reliability perspective. This will ensure that your applications are better able to handle issues like a cloud outage or service failure.

Buddy Brewer is GVP and GM at New Relic

Related Links

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Related Vendors

The Latest

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

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