Cloud computing is a foundational platform for modern businesses, enabling digital transformation and supporting organizational agility. The benefits of putting applications in the cloud are well documented: flexibility, scalability, and reliability with a lower capex investment.

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we discuss the merits of going hybrid in this era of distributed workforces and remote working culture. While it has become imperative for organizations to implement remote work policies, the question of cloud adoption has become almost unavoidable.

Linux is one of the best known and most used open source operating systems. The key advantages of using Linux servers are that they are stable, secure, compatible, and customizable.

Following the release of Azure Monitor for VMs in January 2020, some changes have been made to how its performance data is stored in Log Analytics. The most significant of these changes is that this data is now stored in the InsightsMetrics table rather than in the Perf table, as we discussed in our ‘What is Azure VM Insights?’ article.

As all Papertrail fans know, sending logs to Papertrail using syslog is quick and easy. Generating and transmitting syslog packets usually involves just 2 – 4 lines of code, and you can see your logs flowing into Papertrail in minutes. There are times, however, when you just can’t use syslog or install a remote_syslog2 daemon. This is where the new support for sending logs via HTTP comes in. And the best news is, it’s just as quick and easy to set up.

Talk about performance monitoring to any system admin or IT manager and one of the first questions they will ask is whether the monitoring is agent-based or agentless. The moment you hear that question, you know that they are interested in an agentless monitoring solution. Such is the fear of having agents on critical servers in the infrastructure! In this article, we will discuss.

Edge computing – with its ability to help unleash the potential of smart cities and autonomous vehicles, is something often thought to exist “around the corner” as opposed to an industry already in motion.

This is part of a series of articles discussing strategies to implement serverless architectural design patterns. We continue to follow this literature review. Although we use AWS serverless services to illustrate concepts, they can be applied in different cloud providers. In the previous article (Part 1) we covered the Aggregator and Data Lake patterns. In today’s article, we’ll continue in the Orchestration & Aggregation category covering the Fan-in/Fan-out and Queue-based load leveling.

Technology has a way of circling around to the same ideas over time, but with different approaches that learn from previous iterations. Service Oriented Architecture (SOA) and Microservices Architecture (MSA) are such evolutionary approaches. Where lessons learned made sense, they were reused; and where painful lessons were learned, new methods and ideas were introduced.

Accessing Windows registry (local or remote) is a typical way of gathering useful data. However, there’s a typical pitfall that can cause unexpected scripts or programs behavior. Namely, accessing registry values across different architectures (say, 64-bit entries from 32-bit applications).