Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

The biggest change in Cloud Managed Services 2.0 is how it unites domains that once operated in isolation. CloudOps, FinOps, DevOps, SecOps, and AIOps now work as a single, cohesive team instead of separate departments competing for resources and priorities. This matters because modern businesses operate at a pace that leaves traditional methods behind ...

When you build a distributed system with microservices, you embrace flexibility and scalability. But you also open the door to unexpected failures. Networks drop packets. Databases become slow. Code bugs slip through testing. Fault injection lets you surface those hidden weak spots before they surprise your users in production. By deliberately introducing failures into your system, you learn its breaking points, you build confidence in your recovery paths, and you make resilience part of your design rather than an afterthought ...

AI agents are already transforming the enterprise ... But while the models are advancing fast, most enterprise systems still aren't ready for agent-to-agent AI. The reason is simple but consequential: the environments we've built don't support autonomous action ...

In Part 12, the final installment in the series, the experts present some final predictions about AI's future impact on APM and Observability ...

What's in the future for APM and Observability? The experts have some ideas, and some of them even contradict each other. In the final installments of this series, the experts present their visions of the future for APM, Observability and beyond ...

AI plays a transformative role in both APM and observability by turning raw data into actionable insights, enabling faster, more accurate detection and resolution of issues ...

The story of the evolution of Observability to encompass APM and other IT performance management capabilities would not be complete without discussing the monumental impact of open source ...

So after all this discussion, what do the experts say about whether you need APM, observability or both? In today's complex digital landscape, organizations need both APM and Observability to not only react to issues but to anticipate and mitigate them proactively, ensuring robust performance and resilience ...

APM and Observability are often utilized by different teams within an organization, though there is considerable overlap ... In Part 7, the experts examine the different roles in IT and how they use either APM and Observability, or both ...

The experts say that APM and Observability serve fundamentally different use cases. Some of this was covered in earlier parts of this series, but the experts delve deeper into the differences of use cases here ...

APM remains a cornerstone in the toolkit for application performance management, crucial for pinpointing and resolving application-specific issues. Observability, however, is the evolution of this concept, expanding the scope to encompass distributed systems and cloud environments ...

Observability truly offers a wealth of capabilities that reach far beyond what we traditionally expect from APM. While APM excels at meticulously tracking application metrics and promptly alerting us when things go awry, observability empowers our teams to delve much deeper ...

While both aim to enhance system performance and reliability, observability offers a broader, more holistic approach and is designed for today's complex, distributed systems, as opposed to traditional, application-specific monitoring with APM ...

One of the key questions this APMdigest series seeks to answer: Is APM still relevant, or is it being replaced by Observability tools? APM remains a vital tool in the shed; it hasn't been replaced by observability ...

Application Performance Management (APM) and Observability are two of the most important tools in the ITOps and development toolboxes. Yet there seems to be confusion about them. What is the difference between APM and Observability? Does each offer different capabilities or serve different use cases? Do you need both, or is one enough? These are the questions this epic 12-part APMdigest series will attempt to answer over the next few weeks ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...