Observability Has a Complexity Problem
June 01, 2023

Dotan Horovits
Logz.io

Share this

The journey of maturing observability practices for users entails navigating peaks and valleys. Users have clearly witnessed the maturation of their monitoring capabilities, embraced DevOps practices, and adopted cloud and cloud-native technologies.

Notwithstanding that, we witness the gradual increase of the Mean Time To Recovery (MTTR) for production issues year over year. In this year's (2023) DevOps Pulse survey, conducted by Logz.io, 73% of respondents stated that it took multiple hours on average to resolve production issues.


In comparison, in 2022 only 64% of respondents said the same and only 47% cited this in the year prior. Why is that? The answer seems to lie within the growing overall system complexity, due to the adoption of Kubernetes and cloud-native technologies and practices, as practitioners reported on the survey.

The findings from the report indicate that DevOps practices show signs of maturity and growth within organizations. One such example is that 45% of users have fully adopted and embraced DevOps practices — a 7% increase compared to 38% the year before. Similarly, there has been significant uptake of cloud adoption, as evidenced by the fact that 78% of organizations have either partially or fully transitioned to the cloud this year.

However, as maturity advances, a notable trend is surfacing: the mean time to recovery (MTTR) for production issues has been steadily increasing year over year, as witnessed in the above survey results. A leading cause for the substantial increase in MTTR for organizations is the rising adoption of cloud-native technologies and their intricacies.

Technologies such as Kubernetes generate abundant and complex data, making it difficult to monitor and troubleshoot. As such, these technologies were cited by 46% of respondents as the most difficult obstacle for organizations to gain full observability of their environment.

Kubernetes specifically stands out as a challenging tool for observability users, both in terms of monitoring and running it in production. Over 40% of survey responses stated that monitoring and gaining full observability is one of the key challenges of running Kubernetes. This statistic has grown from 2022, in which only 31% of respondents cited this exact figure. Outside of observability, respondents also noted challenges with Kubernetes security and cluster networking functionality.

In the 2023 report, security was highlighted as another area of major focus for DevOps practitioners, with over 30% of respondents stating that a shared model is used for security and observability. As these teams take on the responsibility of security, they are running into issues with centralizing security data and outlining clear roles and responsibilities for their teams.

One of the most challenging factors of security implementation is tool integration for cloud-native technologies. In fact, nearly 50% of respondents highlighted that implementing security for Kubernetes is the most difficult aspect of running it in production. The dynamic environment, distributed architecture, and overall complexity and scale of these technologies can further compound the difficulty of implementing comprehensive security practices.

The escalating complexity within IT systems also led to a surge in telemetry data volumes, consequently driving up the expenses associated with observability. In response, organizations have implemented various strategies to mitigate observability costs, including the adoption of open source tools as part of their overall approach.

The report shows that roughly 53% of this year's respondents stated that half or more of their observability tools are open source. The uptick from last year is notable, as only 37% of 2022 survey respondents indicated that half or more of their tools were open source. Respondents cited the lower cost of ownership (36%), ease of integration (47%), and benefits of the open source community (33%) as some of the key reasons for open source tool adoption.

As organizations face increasing complexity in observability, collecting and gathering insights from observability practitioners remains paramount. By utilizing their expertise, organizations can navigate the evolving landscape and make informed decisions to optimize their observability practices.

Dotan Horovits is Principal Developer Advocate at Logz.io
Share this

The Latest

October 04, 2024

In Part 1 of this two-part series, I defined multi-CDN and explored how and why this approach is used by streaming services, e-commerce platforms, gaming companies and global enterprises for fast and reliable content delivery ... Now, in Part 2 of the series, I'll explore one of the biggest challenges of multi-CDN: observability.

October 03, 2024

CDNs consist of geographically distributed data centers with servers that cache and serve content close to end users to reduce latency and improve load times. Each data center is strategically placed so that digital signals can rapidly travel from one "point of presence" to the next, getting the digital signal to the viewer as fast as possible ... Multi-CDN refers to the strategy of utilizing multiple CDNs to deliver digital content across the internet ...

October 02, 2024

We surveyed IT professionals on their attitudes and practices regarding using Generative AI with databases. We asked how they are layering the technology in with their systems, where it's working the best for them, and what their concerns are ...

October 01, 2024

40% of generative AI (GenAI) solutions will be multimodal (text, image, audio and video) by 2027, up from 1% in 2023, according to Gartner ...

September 30, 2024

Today's digital business landscape evolves rapidly ... Among the areas primed for innovation, the long-standing ticket-based IT support model stands out as particularly outdated. Emerging as a game-changer, the concept of the "ticketless enterprise" promises to shift IT management from a reactive stance to a proactive approach ...

September 27, 2024

In MEAN TIME TO INSIGHT Episode 10, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Generative AI ...

September 26, 2024

By 2026, 30% of enterprises will automate more than half of their network activities, an increase from under 10% in mid-2023, according to Gartner ...

September 25, 2024

A recent report by Enterprise Management Associates (EMA) reveals that nearly 95% of organizations use a combination of do-it-yourself (DIY) and vendor solutions for network automation, yet only 28% believe they have successfully implemented their automation strategy. Why is this mixed approach so popular if many engineers feel that their overall program is not successful? ...

September 24, 2024

As AI improves and strengthens various product innovations and technology functions, it's also influencing and infiltrating the observability space ... Observability helps translate technical stability into customer satisfaction and business success and AI amplifies this by driving continuous improvement at scale ...

September 23, 2024

Technical debt is a pressing issue for many organizations, stifling innovation and leading to costly inefficiencies ... Despite these challenges, 90% of IT leaders are planning to boost their spending on emerging technologies like AI in 2025 ... As budget season approaches, it's important for IT leaders to address technical debt to ensure that their 2025 budgets are allocated effectively and support successful technology adoption ...