Another year has flown by and another time of reflection has come. Some topics in 2024 that have been hot include Generative AI, monitoring and observability efficiencies, and telemetry pipelines. Here are our my top five articles I think you should read:

Forbes: How to Break Down Silos to Get More Benefit From Your Data

Silos are easy to build, but breaking them down is not. This article offers snippets of advice from various leaders across the tech industry. Whether you’re a seasoned veteran or a newbie, it’s nice to have a list that lays out what principles and practices can ensure your organization is getting the most value out of your data. Learn more at Forbes.

The New Stack: 7 Principles for Improving Software Delivery

While this article highlights 7 principles that UST, a consulting firm, uses, it also highlights the importance of living and embodying such principles. It’s like the old saying, “Do as I say, not as I do” can really make a difference in a company’s culture. Details at The New Stack.

siliconANGLE: Data Observability’s Crucial Role in the AI Era

Data observability is as essential as application performance monitoring falls short in today’s data landscape. Organizations now manage a wide range of data sources and formats. Reliable, clean data is critical for minimizing delays in decision-making and enabling timely, effective business outcomes. See it at siliconANGLE.

Forbes: Three Reasons Why Implementing And Monitoring OpenTelemetry Is Hard—And How To Make It Easier

OpenTelemetry’s intention as an open-source project to serve as a standard for telemetry data and observability tools is promising on paper but challenging to implement, especially when existing vendor-specific standards are already in place. So how do you make it easier? Don’t try to do everything at once. Instead, take a staggered approach and focus on what works best for your organization. More at Forbes.

The New Stack: Key Trends Shaping the Observability Market

Of course, it wouldn’t be right not to include a trends article about the observability market, but similar to my own thoughts, the four called out here are: 

1. AI and LLMs are changing the way we observe services–Resource management, performance monitoring, and model drift detection are important areas of observability needed to perform well. 
2. Data lakes need to converge–Metrics, trace, and logs can’t always be separate.
3. OpenTelemetry is becoming more top of mind–Adoption is growing and so is the contributions to this open-source project, and will likely take a bigger role in driving innovation and observability. 
4. Private deployments to save costs–I’d call this the bring-your-own storage revolution, and it is upon us. 

Read at The New Stack.

Looking ahead to 2025

We’ll likely continue to hear more about observability in various ways, such as generative AI, data quality, and how different roles use the same data. Today, you can see how Mezmo helps you with these things by trying Mezmo telemetry pipeline.