Operations | Monitoring | ITSM | DevOps | Cloud

Stakeholder analysis in software selection involves a systematic approach to identifying, analyzing, and managing the needs and expectations of stakeholders. Engaging diverse stakeholders, including end-users, IT staff, and executive sponsors, is crucial during the software selection process. This ensures a comprehensive understanding of requirements and impact.

Distributed systems allow projects to be implemented more efficiently and at a lower cost, but require complex processing due to the fact that several nodes are used to process one or more tasks with greater performance in different network sites. To understand this complexity, let’s first look at its fundamentals.

In the fast-paced world of technology, innovation is the key to staying ahead of the curve. As businesses strive for efficiency, speed, and real-time data processing, the spotlight is increasingly turning towards edge computing. Edge computing represents a paradigm shift in the way data is processed and analysed. Unlike traditional cloud computing, which centralises data processing in distant data centres, edge computing brings the processing power closer to the source of data.

In today’s data-driven world, the choice of data storage solution is crucial for businesses of all sizes. Microsoft SharePoint and Azure Blob Storage are two powerful services that cater to the diverse needs of storing, managing, and accessing data. But with different pricing models and features, deciding which service offers better value for money can be challenging. This post explores the cost structures of SharePoint and Azure Blob Storage to help you make an informed decision.

At Obkio, we frequently get asked the question by potential customers: "Which plan do I need?". So we decided to share the perfect use case to provide clarity. What better way to illustrate the capabilities of our Basic Plan than by showcasing a real-life scenario of a multi-site SMB taking advantage of it?

Curious about Gatling load testing for Kubernetes? Learn how it compares to Speedscale when it comes to functionality, setup, CI/CD integration & more.

Whether you’re a Data Engineer, DevOps, Cloud Architect, or a Business Intelligence Professional, Data Lakes are indispensable tools for harnessing the power of big data, enabling advanced analytics, and driving informed decision-making across your enterprise. Back in the 90s, the internet boom led to an unprecedented expanse of data. This led to a gaping demand for better data storage solutions.

Reliability risks are potential points of failure in your system where an outage could occur. If you can find and remediate reliability risks, then you can prevent incidents before they happen. In complex Kubernetes systems, these reliability risks can take a wide variety of forms, including node failures, pod or container crashes, missing autoscaling rules, misconfigured load balancing or application gateway rules, pod crash loops, and more. And they’re more prevalent than you might think.