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90% Report Reducing Engineering Toil to Scale Tools Puts Focus on Business Bottom Line

Stela Udovicic
Era Software

Modern IT and security organizations often need to manage petabytes of observability (logs, metrics, traces) data in real time. The adoption of cloud, modern application architectures, Kubernetes, and edge is behind this massive growth in observability data volumes. And for some organizations, log data volumes are approaching the exabyte range.

IT teams face many obstacles when managing massive amounts of observability data, from siloed tooling to prolonged incident resolution and security risks such as accidental exposure of personal identifiable information (PII) or credential data.

To shed light on key trends, challenges, and approaches these teams take to resolve those challenges, in Feb 2022, we ran a survey of professionals across various industries and roles within IT organizations. We are excited to share today the results of our 2022 State of Observability and Log Management report.

Over 315 IT executives, cloud application architects, DevOps, and site reliability engineers (SRE) took the survey, sharing perspectives on the current state of exploding data and the struggle to gather valuable insights from the data. These professionals are responsible for managing the availability of cloud application and infrastructure environments with at least 10 TB of log data, and their companies have at least 100 employees.

The survey results show that IT teams have difficulty with the massive growth of log data and use various methods to manage data volumes and their associated costs. These include only storing the most critical data to prematurely deleting log data. However, according to 78% of the respondents, attempts to manage volumes of log data have had mixed or unwanted results, such as increased incident response times or inability to access needed data.

Two-thirds of IT organizations require engineering time to manage their log management tools; larger organizations with more log data are more likely to have dedicated teams for tool management.
For the purposes of our survey, we defined observability as an evolution of traditional monitoring towards understanding deep insights from analyzing high volumes of log, metrics, and trace data, collected from a wide variety of modern applications and infrastructure environments.

Compared to similar research conducted in 2021, organizations report that observability adoption jumped by 180%. In addition, as organizations mature in implementing observability, the value of critical insights from their log data is more significant.

Participants also shared details about their current streaming data use. Streaming data connects, filters, processes, and routes log data between different observability tools (commercial or open source) or offline cold storage (S3, Google Cloud Services, etc.) and is sometimes called observability pipeline or observability data management. According to responses, streaming observability pipelines adoption is a work in progress, with 20% of organizations reporting full deployments while 36% are evaluating or considering options.

Report findings also reveal:

■ Observability log data is critically important for organizations. 83% of respondents report that business stakeholders outside of IT use insights from log data. In addition, 68% say log data is necessary, but it's tough to work with.

■ IT continues to struggle to keep up with data volumes. 78% work to reduce volumes and costs, but they miss needed data or troubleshooting, and security analyses are impacted.
■ Existing log management tools present challenges and risks related to scalability, 97% of respondents report.

■ Log data is key to observability, and innovation is needed. 79% of respondents believe the overall cost of observability data management, including log management activities, will skyrocket in 2022 if current practices and tools don't evolve.

■ Problems are beyond storing data. For example, 96% report the need also to use the data to solve business problems.

■ 90% report reducing engineering toil to scale tools helps IT focus on more important work.

■ Volumes of log data in organizations are exploding, according to 96% of IT professionals surveyed.

Survey Demographics: Roles include a third IT executives, a third enterprise (cloud or application) architects, and a third in DevOps/SRE/Ops roles. Companies are in the following regions: AMER (77%), followed by EMEA (20%) and APAC (3%), and include a variety of industry verticals, including financial, technology, healthcare, service, retail, manufacturing, etc.

Stela Udovicic is SVP, Marketing, at Era Software

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90% Report Reducing Engineering Toil to Scale Tools Puts Focus on Business Bottom Line

Stela Udovicic
Era Software

Modern IT and security organizations often need to manage petabytes of observability (logs, metrics, traces) data in real time. The adoption of cloud, modern application architectures, Kubernetes, and edge is behind this massive growth in observability data volumes. And for some organizations, log data volumes are approaching the exabyte range.

IT teams face many obstacles when managing massive amounts of observability data, from siloed tooling to prolonged incident resolution and security risks such as accidental exposure of personal identifiable information (PII) or credential data.

To shed light on key trends, challenges, and approaches these teams take to resolve those challenges, in Feb 2022, we ran a survey of professionals across various industries and roles within IT organizations. We are excited to share today the results of our 2022 State of Observability and Log Management report.

Over 315 IT executives, cloud application architects, DevOps, and site reliability engineers (SRE) took the survey, sharing perspectives on the current state of exploding data and the struggle to gather valuable insights from the data. These professionals are responsible for managing the availability of cloud application and infrastructure environments with at least 10 TB of log data, and their companies have at least 100 employees.

The survey results show that IT teams have difficulty with the massive growth of log data and use various methods to manage data volumes and their associated costs. These include only storing the most critical data to prematurely deleting log data. However, according to 78% of the respondents, attempts to manage volumes of log data have had mixed or unwanted results, such as increased incident response times or inability to access needed data.

Two-thirds of IT organizations require engineering time to manage their log management tools; larger organizations with more log data are more likely to have dedicated teams for tool management.
For the purposes of our survey, we defined observability as an evolution of traditional monitoring towards understanding deep insights from analyzing high volumes of log, metrics, and trace data, collected from a wide variety of modern applications and infrastructure environments.

Compared to similar research conducted in 2021, organizations report that observability adoption jumped by 180%. In addition, as organizations mature in implementing observability, the value of critical insights from their log data is more significant.

Participants also shared details about their current streaming data use. Streaming data connects, filters, processes, and routes log data between different observability tools (commercial or open source) or offline cold storage (S3, Google Cloud Services, etc.) and is sometimes called observability pipeline or observability data management. According to responses, streaming observability pipelines adoption is a work in progress, with 20% of organizations reporting full deployments while 36% are evaluating or considering options.

Report findings also reveal:

■ Observability log data is critically important for organizations. 83% of respondents report that business stakeholders outside of IT use insights from log data. In addition, 68% say log data is necessary, but it's tough to work with.

■ IT continues to struggle to keep up with data volumes. 78% work to reduce volumes and costs, but they miss needed data or troubleshooting, and security analyses are impacted.
■ Existing log management tools present challenges and risks related to scalability, 97% of respondents report.

■ Log data is key to observability, and innovation is needed. 79% of respondents believe the overall cost of observability data management, including log management activities, will skyrocket in 2022 if current practices and tools don't evolve.

■ Problems are beyond storing data. For example, 96% report the need also to use the data to solve business problems.

■ 90% report reducing engineering toil to scale tools helps IT focus on more important work.

■ Volumes of log data in organizations are exploding, according to 96% of IT professionals surveyed.

Survey Demographics: Roles include a third IT executives, a third enterprise (cloud or application) architects, and a third in DevOps/SRE/Ops roles. Companies are in the following regions: AMER (77%), followed by EMEA (20%) and APAC (3%), and include a variety of industry verticals, including financial, technology, healthcare, service, retail, manufacturing, etc.

Stela Udovicic is SVP, Marketing, at Era Software

Hot Topics

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Industry experts offer predictions on how AI will evolve and impact technology and business in 2025. Part 2 covers the challenges presented by AI, as well as solutions to those problems ...

In the final part of APMdigest's 2025 Predictions Series, industry experts offer predictions on how AI will evolve and impact technology and business in 2025 ...

E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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Imagine a future where software, once a complex obstacle, becomes a natural extension of daily workflow — an intuitive, seamless experience that maximizes productivity and efficiency. This future is no longer a distant vision but a reality being crafted by the transformative power of Artificial Intelligence ...