The push for efficient observability solutions is more critical than ever, driven by the complexity of modern IT environments, microservices and distributed systems. As our businesses depend on digital services, the need for reliable, always-available systems makes observability essential to minimize downtime and maximize customer experience.
Today’s technology teams must make data-driven decisions to meet system performance and user standards.
With that said, I believe that our traditional observability methods, heavily reliant on instrumentation, fall short of meeting the challenges of operating in today’s digital economy. Sure, they have long been the backbone of monitoring and diagnosing systems, but as technology and complexity advance, the major limitations of these methods are becoming increasingly apparent.
In this blog, I’ll share my thoughts on why today’s observability solutions, which depend on logging, traces and metrics, are lacking and how a non-instrumented approach is an IT team’s dream.
My Beef With Instrumentation
As I mentioned, instrumentation relies on logging, traces and metrics, with the intent to provide comprehensive insights into system operations. However, this approach has glaring drawbacks. First, it is inherently time-consuming. Setting up and maintaining extensive instrumentation requires significant effort and resources. Second, it is expensive. The costs of integrating and managing these tools can quickly escalate with the proliferation of monitoring tools in IT Ops environments. Lastly, in my experience, instrumentation is invasive by nature, often leading to performance overheads and potential disruptions in system operations.
With instrumentation at its core, today’s observability methods tend to be slow and prone to errors. The sheer volume of data generated is overwhelming, leading to delayed responses and missed anomalies.
In an era where speed and accuracy are paramount, such inefficiencies are detrimental, to say the least.
Real Challenges for IT Ops Teams
The drawbacks of instrumentation are no joke. The time and resources spent setting up and maintaining instrumentation divert focus from more strategic initiatives. Also, the invasive nature of instrumentation leads to fear of making necessary changes, as, in many cases, it creates new problems. This stagnation stifles innovation and adaptation, which is the purpose and goal of every technology team.
Intelligent Canaries to the Rescue
For context, I founded Cloud Canaries for two reasons: 1) I led teams at a large public cloud providers and saw firsthand the lack of value and costly complexity of traditional observability, and 2) during a client call to deal with a customer-facing problem, a pivotal discovery was made: a simple Python app, or "canary," deployed by an internal DevOps team quickly provided the exact information we needed to resolve a mystery outage. This revelation highlighted how customer insights can uncover solutions that expensive cloud monitoring tools miss.
I experienced a profound moment of clarity and inspiration the first time I saw canaries work their magic.
Relating to its name, Intelligent Canaries act like when miners used to bring along a little yellow canary to detect dangerous gasses like carbon monoxide. If the canary stopped singing, it was a warning sign to get out quickly.
Fast forward and think of Intelligent Canaries playing a similar role. While rolling out new updates or features, developers can use Intelligent Canaries as an early warning system to detect and resolve issues before something goes wrong, like a bug or a crash.
Simply put, Intelligent Canaries use AI and machine learning to analyze data patterns and user behavior to ensure system stability and resilience without disrupting operations. Unlike observability solutions that depend on instrumentation and log file-based approaches, our technology provides a more efficient and cost-effective alternative.
Here are three foundational reasons I believe Intelligent Canaries are real game-changers:
Observability Without Instrumentation: The Future
Observability without instrumentation is a true paradigm shift in monitoring and managing IT infrastructure. At Cloud Canaries, we’ve removed any dependency on instrumentation by harnessing the power of AI to provide rapid and unbiased predictions. Our AI models can process vast amounts of data at incredible speed to provide real-time insights that were previously unattainable.
We address the challenges of time, cost, and invasiveness and better align with the future of IT operations. As your organization embraces digital transformation, the ability to predict and respond to changes with unprecedented speed is not a “nice to have” but essential to gaining a competitive advantage.
While traditional observability methods have served well in the past, the future belongs to approaches that remove instrumentation constraints. Observability without instrumentation, promises a smarter, more efficient path forward.