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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Container Management - Decoding Kubernetes Management Platforms Part 1

This is the first article of a series of two covering the advantages and disadvantages of hosted and non-hosted Kubernetes management platforms. First, let’s introduce hosted what is hosted Kubernetes management platform (KMP) and provide a broader view of hosted KMPs.

7 Ways DCIM Software Provides a Fast ROI

As a global leader in second-generation Data Center Infrastructure Management (DCIM) software, we have the opportunity to speak with a lot of data center professionals. One of the most common stories we hear is that they are still using Excel, Visio, open-source software, and homegrown tools to manage their data centers and that these tools are causing them a lot of pain. They're manually intensive, inaccurate, hard to use, and not integrated.

Securing Your Cloud Data with Azure Storage Private Endpoints

Are you storing your data in the cloud? If yes, then you must be aware of the various security challenges that come with it. One of the biggest concerns in cloud computing is securing data from unauthorized access. However, with Azure Storage Private Endpoints, Microsoft has introduced a solution that can help organizations secure their data in the cloud.

4 Elements to Create an Effective IT Automation Strategy

As more and more organizations undergo digital transformation, IT automation is becoming more important and essential to implement. A report by Smartsheet found that more than 40% of those surveyed spend about a quarter of their time working on repetitive tasks, and almost 70% of them say that automation’s biggest opportunity would be that it significantly reduces the amount of time spent on these tasks.

Transforming Monitoring with a Machine Learning-First Approach

Unlocking the full potential of monitoring through ML integration, anomaly detection, and innovative scoring engines. Machine Learning has been making waves in various industries, but its adoption in the monitoring and observability space has been slower than expected. Many “ML” features remain gimmicky and do not provide actual real world value to users that encourages their further use.