Cloud migration vs modernization – What are the nuances? Cloud migration involves moving applications and data to the cloud often with minimal changes to their architecture. Cloud migration projects usually aim to leverage cloud infrastructure for benefits such as scalability, flexibility and reduced on-prem maintenance.

IT teams are the invisible engines powering every modern organization. Yet they battle constantly to ensure the availability and reliability of applications and services across fragmented, hybrid-cloud infrastructures. In particular: Fragmented tools, siloed workflows, and inconsistent manual processes create an IT nightmare. Despite investing millions in observability and ITSM platforms, teams face alert fatigue, reactive incident response, and persistent outages.

Kentik NMS has the ability to collect multiple SNMP objects (OIDs). Whether they are multiple unrelated OIDs, or multiple elements within a related table, Leon Adato walks you through the steps to get the data out of your devices and into your Kentik portal.

We’ve been exploring new approaches to make Sentry issues more actionable. Read on to learn how we’re using machine learning to improve issue creation (i.e. grouping) and alerts, with as little configuration as possible, so you can focus on fixing the most important issues.

Sentry knows a lot about the inner workings of an application’s codebase. So we got to thinking, how can we use this rich dataset to make debugging with Sentry even faster? Many generative AI (GenAI) tools (e.g. GitHub Copilot) improve developer productivity in their dev environment, though few have the contextual data Sentry has to help fix errors in production.

In the rapidly changing world of technology, effective monitoring is critical for maintaining your infrastructure and ensuring it performs effectively. While traditional monitoring methods are effective, they can fall short as systems scale and become more dynamic and complex. This article aims to bridge the gap by introducing software engineers to the power of machine learning (ML) in infrastructure monitoring, outlining not just the ‘how’ but the ‘why’ of its application.

The term “data mesh” isn’t especially new, but the definition of what it is and does is perhaps not widely agreed upon, so let’s explore it a bit.

Slow code is everywhere—or maybe "anywhere. "Slowness" is a spectrum. Sometimes, you triumphantly move performance bottlenecks so that the bar for "slow" always gets lower. In our experience, though, things often trend in the other direction.

Software deployment, a critical process in software development, refers to all the activities that make a software system available for use. It’s the stage where all the hard work of creating software culminates into something tangible that users can interact with. But before we delve into its complexities, let’s first understand the basics of software deployment.

The evolution of public cloud over the past few years has been remarkable. Digital transformation, remote work, and AI have created breakneck growth. Back in 2018, before anyone uttered the words COVID or ChatGPT, there were already big drivers for public cloud. The global digital transformation market size was valued at $320 billion, and set for 18% annual growth, to reach a projected $695 billion by 2025.