The manufacturing sector is at a crossroads. Industry 4.0 brought with it a wave of innovation, with the industrial internet of things (IIoT), advanced automated, and AI-driven analytics. Now, we’re experiencing the onset of Industry 5.0, where humans work alongside smart machines to create more sustainable products, services, and supply chains.

Facing rising technical complexity and pressure from regulators, these are challenging times for financial services organizations. Given the near- and long-term uncertainties, organizations must focus on what’s coming next. That includes navigating technological disruption and the way it’s shaping experiences and expectations for employees and customers alike. Now, 73% of banking interactions happen over digital channels.

Editor’s Note: This is the second installment of a series of blog posts previewing our State of Observability 2024 survey report. In the first episode of this blog series, we looked at where IT organizations are in their observability journeys and found, rather surprisingly, that most enterprise IT organizations and MSPs were just getting started in observability. Yet 96% of respondents told us their observability solution was delivering the value they expected.

Observability in IT refers to the ability to measure a system's internal functioning by studying its signals from the outside. Modern IT observability is achieved through three kinds of telemetry: metrics, traces, and logs. Metrics aggregate events to gauge a system’s current state. Tracing tracks the progress of each transaction to not only measure performance but also debug the problem. On the other hand, logs record each event, which can help during troubleshooting.

This is the third and final post in a series of blog posts about the disconnect between modern IT and security teams and the vendors they’re forced to work with. If you’re looking for the first and second posts, you can find them here and here.

Observability systems are designed to keep tabs on key metrics, identify unusual patterns, and alert teams when things go awry. Despite best efforts, however, these systems are not infallible, and sometimes they send out alerts for issues that don’t exist. This is what we call a false positive. These false alarms can wreak havoc on team efficiency, lead to alert fatigue, and obscure genuine problems. Let’s delve into what false positives are and why they matter so much.

Amperity required an observability partner to facilitate their transition into the modern engineering era as their previous tooling struggled to support their growth strategy. When customer data is scattered everywhere, how do you put the pieces together to get an accurate customer 360° view? That’s the power of Amperity’s customer data platform (CDP), and the company has been driving customer data innovation for nearly a decade.

In technology, having “modern” capabilities is standard. Staying ahead of the curve is critical, and keeping outdated technology or processes going can be a recipe for disaster in a complex, ever-changing landscape. Ensuring the smooth functioning and performance of software systems is paramount. This is where modern observability—a sophisticated approach to monitoring and understanding the inner workings of applications and infrastructure—is required.

In my February 2024 piece The Cost Crisis in Observability Tooling, I explained why the cost of tools built atop the three pillars of metrics, logs, and traces—observability 1.0 tooling—is not only soaring at a rate many times higher than your traffic increases, but has also become radically disconnected from the value those tools can deliver. Too often, as costs go up, the value you derive from these tools declines.