Operations | Monitoring | ITSM | DevOps | Cloud

In many organizations, developers, SREs, network engineers, and security teams work in specialized domains, which can make it hard to establish a shared view of network health. As a result, engineers often struggle to determine when a network problem that originates outside of their domain of expertise is the root cause of an incident. This lack of visibility slows investigations and delays remediation.

AI innovation has accelerated faster than most organizations’ ability to monitor and manage it. The shift from experimentation to production-scale workloads has driven a new class of operational challenges: rising GPU costs, opaque model performance, and the difficulty of linking spend to business value. As AI investments grow, executives need a unified way to measure efficiency and return without slowing down innovation.

Over the past few months, we’ve seen incredible adoption of our AI Investigations and Insights reports. Teams are using them to automate the deep, thoughtful analysis required for complex post-mortems, capacity planning, and performance optimization. These comprehensive reports are fantastic when you need a well-researched, shareable document. But what about the moments during an investigation?

What remains of the 2025 AI hype? After a year of “AI will fix everything” promises, engineering teams in 2025 hit a wall of reality: AI is a tool, not a magic bullet. We’re now seeing a more practical approach: identifying broken workflows and tasks where AI can help and leveraging AI strengths like data analysis at speed and scale to derive meaningful, valuable insights. Looking ahead, 2026 will reward organizations that combine AI innovation with a practical approach.

In today’s age of continuous delivery, a failed deployment or a drop in performance can affect thousands of users in just a few minutes. Traditional testing happens before deployment, but what about after the code is live? This is where app synthetic monitoring becomes a critical part of your CI/CD pipeline. Integrating synthetic monitoring into CI/CD transforms your pipeline from a simple delivery mechanism into a proactive quality and performance gatekeeper.

If you’re running a SaaS business today, you’ve probably noticed the alarms never really stop. Logs. Alerts. Tickets. They pile up faster than many teams can triage them. Add multiple clouds, microservices, and AI-driven workloads, and suddenly, your “always-on” infrastructure feels like it’s always on fire. AIOps platforms promise to connect dots that human teams struggle to see fast enough. For engineers, these include surfacing root causes and outwitting outages.

“Invisible IT” might sound like a marketing slogan, but it captures something every IT leader has quietly wanted for what feels like eons: a world where technology does its job without slowing anyone down. A world where support is proactive instead of reactive and where digital friction disappears before employees ever feel it. Invisible IT is about removing interruptions without disappearing IT teams.

Shifting security left shouldn't slow you down. Discover how to achieve "Zero-Friction DevSecOps" by automating secrets, compliance, and governance directly within your PaaS pipeline.

This blog is based on Thomás Di Luccio's talk "Bulletproofing for Black Friday" from the Symfony 2024 conference. Thomás is a Developer Relations Engineer at Upsun. We utilized AI tools for transcription and to enhance the structure and clarity of the content. Picture this: You're a small ticketing startup that just landed a major deal with a large venue. After months of building features and preparing for launch, the big day arrives—season ticket sales go live.

The CNCF reported that between 39% and 56% of organizations surveyed are now ingesting traces as part of their observability strategy. Tracing has become a cornerstone of any modern observability operation. Customers are regularly handling 10s of billions of spans every day, but with billions of spans, how can teams quickly figure out what is changing, what’s breaking, or what’s slowing down?