Network closets, often referred to as IDF closets or telecommunications closets, are small yet vital spaces that house important networking equipment, acting as the hubs that connect various parts of an organization's IT infrastructure. Despite their significance, network closets are often overlooked and undermanaged. Poorly managed network closets can result in network downtime, reduced efficiency, and increased maintenance costs.

Startups face unique challenges in their journey, including tight budgets, rapid development cycles, and limited resources. In this high-pressure environment, DevOps practice emerges as a crucial framework. Contrary to the misconception that DevOps is only suited for large enterprises, it offers significant advantages for startups by streamlining processes, enhancing product quality, and accelerating time-to-market.

Most of us are aware that generative AI offers opportunity for innovation and efficiency where it is revolutionising how businesses operate. However, its impact is not fully understood. Earlier this year, Console Connect conducted a survey by Arlington Research which engaged 1,000 global CTOs and senior leaders to gain a better understanding of the challenges and demands associated with gen AI adoption.

The proliferation of managed LLM services like OpenAI, Amazon Bedrock, and Anthropic have introduced a wealth of possibilities for generative AI applications. Application engineers are increasingly creating chain-based architectures and using prompt engineering techniques to build LLM applications for their specific use cases.

A few months ago, we implemented support for exception profiling in PHP. One of the key justifications for building this functionality into Continuous Profiler was to show the hidden costs of exceptions in PHP, especially when they are used for flow control in hot code paths. Once this feature was built, we naturally wanted to know if it surfaced these kinds of flow control problems in customer production systems.

If you bet on end-to-end testing or even synthetic monitoring, there’s a high chance that you use Microsoft's Playwright. And if you have Playwright in your toolchain, you probably adopted TypeScript, too. It's an easy choice because of its rock-solid auto-completion and type safety. With this setup, you can enjoy the beautiful DX (developer experience) and safely refactor your ever-growing code base without worrying about runtime exceptions because of TypeScript's type checking, right? Wrong!

Persisting to flash is a necessary evil for many embedded devices. Let’s take a look at some of the pitfalls and how they may be avoided.

Dynatrace and New Relic are popular monitoring and observability tools for monitoring your applications and infrastructure. In this post I have compared both Dynatrace and New Relic based on important features like application performance monitoring, log management, and infrastructure monitoring. Even though both tools offer a lot of similar features, they have some key differences. We’ll explore these differences to help you choose the tool that best fits your needs. Let's get started.

The current landscape of open-source software (OSS) in enterprises is characterized by a strategic shift towards open-source solutions for critical infrastructure and development needs. Enterprises increasingly rely on OSS to power their applications, manage data, and automate their deployment pipelines, making OSS an integral part of the software development lifecycle.

Lack of communication between IT operations and ITSM teams results in data silos. And data silos make it challenging, if not impossible, to solve problems efficiently. One-third of ITOps professionals say that gathering business context is the biggest challenge to effective incident response and management, according to EMA Research.