Operations | Monitoring | ITSM | DevOps | Cloud

In the rapidly evolving world of cloud computing, network engineers often need to decide between serverless computing and containerization. Both technologies offer unique advantages and are suited to different types of applications. This article aims to provide a comprehensive comparison of serverless computing and containers, helping network engineers make an informed decision based on their specific needs.

As network engineers, you play a crucial role in managing cloud infrastructure that supports your organization’s applications and services. Cloud platforms offer immense flexibility and scalability, but without careful cost management, expenses can quickly spiral out of control.

Syslog servers are essential for centralized log management, helping network engineers monitor, troubleshoot, and secure network devices efficiently. This guide walks you through setting up a syslog server from scratch, focusing on practical steps using rsyslog on a Linux system—a common and robust choice for syslog collection. Windows does not have a native syslog server, so you need third-party software.

Traditional databases store data in structured tables, whereas NoSQL (non-SQL) databases use more flexible, non-tabular storage methods. NoSQL databases can store a wider range of data types, including document stores, wide columns, key-value stores, and graphs. These databases first emerged in the late 2000s to support massive horizontal scaling and high-throughput workloads for web applications.

If your organization isn’t focused on data security, it’s time to make some changes, particularly if you rely on SQL Server to manage and store valuable information. Cyber threats, data breaches, and malicious attacks are on the rise—and they are constantly evolving. That’s why it’s essential to have robust security measures in place. SQL Server has several built-in security features, but you must take a proactive approach to protect your data.

With the introduction of cloud services and microservices, applications have become more complicated due to their increased layers of complexity and distributed architecture. While microservices clearly offer speed, they also make things harder for the developers and operations teams. These teams need to plan for the reliable and efficient performance of such applications. To combat these challenges, application performance monitoring (APM) has surfaced as an indispensable discipline.