Operations | Monitoring | ITSM | DevOps | Cloud

Today’s higher education institutions operate complex digital ecosystems that were unimaginable a decade ago. Behind every college lies a portal of interconnected systems for registration, financial aid, course management, and campus services. The students using those systems are digital natives who can order food in seconds on their phones or have packages delivered the same day they order them.

You’ve optimized your code, implemented caching strategies, and configured your CDN perfectly. Your analytics dashboard shows respectable load times, and your development team reports everything is running smoothly. Yet, conversion rates remain stagnant, bounce rates climb during peak hours, and your competitors consistently outperform you in user experience metrics. What’s missing?

This blog is based on Haylee Millar's talk at the Symfony 2024 conference. Haley is a Product Engineer at Upsun. We utilized AI tools for transcription and to enhance the structure and clarity of the content. When faced with an aging system that needs new features, many development teams find themselves at a crossroads. Do you patch the old system and risk technical debt, or do you take the leap into microservices architecture?

I am thrilled to share that Observo AI has been named InfoWorld’s 2025 Technology of the Year Award winner in the Observability category. This honor recognizes the products that are defining the future of enterprise technology, those pushing AI from theory into meaningful, practical impact. “Artificial intelligence is reshaping products across the technology landscape, often in surprising ways,” said Executive Editor Doug Dineley, InfoWorld.

Traversing the Gap Between Sparse and Dense Vector Spaces.

Introducing Aiven’s New PG AI Editor - A simpler, faster, developer-friendly way to work with PostgreSQL.

AI tools have seen a meteoric rise in the workplace. What was once the domain of highly specialized tech roles is now commonplace: Ivanti’s 2025 Technology at Work Report found that 42% of office workers say they’re using gen AI tools, like ChatGPT, at work — up 16 points from the previous year. The catch? These productivity gains happen under the table. Among those who reported using gen AI tools, 46% say that some (or all) of the tools they use are not employer-provided.

So you've built a client application and you've started sending telemetry. The information sent back by this client is vital to you, and one of the first things you care about is capturing and reporting errors. There are at least two ways to report error details in OpenTelemetry. Web applications generally place exceptions in trace spans as span events, and mobile applications send exceptions as log messages instead.

Once more in this series, we’re moving into areas where I’m not entirely comfortable. I haven’t built a PHP plugin and web page, ever. However, we’re going to put the LLM/AI and associated agents to work on this task. As with so much else when working with AI, it all starts with the prompt, so let’s go there.

Picture this, your observability tool already nails the basics like request rates, latency and memory usage, but you need more insight. Think user churn rates, engagement spikes, or even how many carts get abandoned mid-checkout. That’s where OpenTelemetry steps in, providing a way to track those critical custom metrics with ease.