In the ever-evolving landscape of cloud computing, Azure stands out as a powerhouse for businesses seeking scalable, reliable, and efficient solutions. One of the fundamental aspects of Azure’s appeal is its vast array of resources catering to diverse needs. Azure offers a rich ecosystem of resources, ranging from virtual machines (VMs) and storage accounts to databases, networking components, and beyond.

In the last years, Kubernetes has grown tremendously and is considered by most companies to be the best platform to run applications today. In simple words, Kubernetes is an open-source container orchestration platform that allows you to run and manage containerized applications at scale. In this article, I will explain how you can run Kubernetes on AWS in 3 different ways. But before getting down the road, let me explain why it does make sense to run Kubernetes on AWS.

The economy and businesses closely rely on network infrastructures functioning efficiently. Minor network bottlenecks and snags can cost companies a good chunk of money and negatively affect their reputation. When there is so much to lose, the natural reaction of organizations is to throw more people and, in turn, more money at the problem.

In the context of IT service management, Service Level Agreements (SLAs) have long been the cornerstone for measuring and ensuring the quality of services provided to customers. However, as technology evolves and incidents become more complex, relying solely on SLAs may not be sufficient. This is where Service Level Objectives (SLOs) come into play, offering a more nuanced approach to Incident Response.

No matter how good a new teammate is, a lot of their success is in your hands.

When discussing reliability, we tend to focus on the things that we have control over: applications, virtual machine instances, deployment patterns, etc. But this ignores a significant and ever-growing part of nearly all modern software: dependencies. Dependencies are services that provide extra functionality for other services and applications. For instance, many websites depend on databases, caches, payment processors, and similar services in order to function.

With the possibilities for increased productivity, reduced costs, and improved customer experiences, organizations are embracing automation across multiple areas of their operational activities. However, navigating the complexities of automation requires a structured approach. This is where frameworks such as Resolve Systems’ Automation Capability Framework and the TM Forum Automation Maturity Model come into play.

A highlight of the SRE Report is the insightful analysis based on the organizational ranks of respondents. The 2023 installment exposed significant misalignment between practitioners and management in several key areas, including the benefits of AIOps, the challenge of tool sprawl, and attitudes towards blamelessness. While the 2024 SRE Report showed a rare consensus on the importance of monitoring external endpoints, it uncovered yet more ongoing differences. Let’s dive in.

Recently, we added powerful new K8s features to HAProxy Fusion Control Plane—enabling service discovery in any Kubernetes or Consul environment without complex, technical workarounds. We've covered the headlining features in our HAProxy Fusion Control Plane 1.2 LTS release blog. But while service discovery, external load balancing, and multi-cluster routing are undeniably beneficial, context helps us understand their impact.

Modern monitoring systems depend heavily on ‘Alerting’ to reduce the Mean Time to Detect (MTTD) faulty systems. But, alerting hasn’t evolved to meet the demands of modern architectures. We’re changing that with Alert Studio.