The Azure Cloud platform processes an extensive variety of data including Eventhub Diagnostic Logs, Kubernetes Metrics, SQL Logs, Activity Logs, Container Activity Logs, and Azure Metrics. Depending on the requirements of your organization these logs offer various levels of importance and priority. But it’s more than likely that you will be monitoring a large variety of these logs.

The FinOps Foundation states that “For the first time, Reducing waste was the highest key priority for FinOps practitioners across all spending tiers. This may be influenced by macroeconomic trends, with businesses looking for ways to reduce spending without reducing the value they are getting from their cloud investments.”

Serverless is an incredible paradigm, but performance tuning sometimes feels like a black box. You have no control over the infrastructure, but that doesn’t mean you can’t optimize. In this post, let’s look at five ways to take serverless performance to the next level.

On-premises communication systems often require managing separate platforms for phone, email, video conferencing, and instant messaging. This fragmentation creates operational inefficiencies that slow down workflows. Employees waste time switching between tools, leading to delays in communication and collaboration. The risk of staying with outdated systems is that your team will continue to operate with these silos, ultimately reducing productivity and making it harder to compete in fast-paced markets.

Observability is crucial for maintaining complex systems’ health and performance. In its traditional form, observability involves monitoring key metrics, logging events, and tracing requests to ensure that applications and infrastructure run smoothly. The emergence of Artificial Intelligence (AI) promises to revolutionize the way organizations approach observability.

Data drives decisions forward. Every insight leads to action. A 2024 Gartner report revealed that organizations utilizing analytics and AI are better positioned to manage complexity, build trust in data, and empower their teams. This underscores the critical role of data intelligence. It involves collecting and analyzing data to uncover patterns and trends that help businesses take action. As a result, they can make informed decisions, optimize performance, and gain a competitive edge.

Cloud costs can pile up quickly, and often behind the scenes. We explain how you can help your business keep cloud spend under control. Enterprises—including small- to medium-sized—often find themselves struggling to manage costs and predict their cloud storage. And it’s not necessarily because we’re acquiring more things – it’s because the things we have are getting bigger.

In cloud-native environments, autoscaling and optimization are often confused, yet they serve different purposes. While Kubernetes offers several built-in autoscaling features, these are often mistaken for optimization. In reality, autoscaling is reactive, responding to changing demands, whereas optimization is proactive, focused on configuring workloads efficiently from the start.

BigQuery’s pipe syntax introduces an intuitive, top-down syntax for understanding data transformations, and is used in Cloud Logging Log Analytics.

Azure monitoring involves tracking and analyzing the health and performance of your cloud infrastructure hosted on Microsoft Azure. It involves gaining real-time insights into the performance of Azure resources, such as virtual machines, databases, and applications, enabling you to identify and resolve issues before they impact your operations. With a plethora of options available in the market, choosing the right Azure monitoring software can be a daunting task.