Monitoring Azure Service Bus (SB) comes with its own set of challenges, primarily due to the distributed nature of the service and the complexities involved in message processing and delivery. Some of the most common challenges associated with monitoring Azure SB include: Message Flow Monitoring: Tracking the flow of messages through various queues or topics, including understanding where bottlenecks might occur or where messages might be delayed.

Leon takes a look at how to further modify SNMP metrics in Kentik NMS. Because sometimes, you want to modify data before displaying it in your network monitoring system. Ready? Let’s get mathy with it!

When an organization attempts to reduce costs immediately, one of its go-to options is to look into the Azure advisor recommendations and take action on them. However, the biggest challenge for many customers is that they often do not know there are saving insights available to take advantage of and reduce thousands of dollars per year in Azure bills. This is because of a few reasons, as defined below;

Data volumes are soaring. Environments are increasingly intricate. The risk of applications and systems encountering breakdowns is sky-high, and the mean time to recovery (MTTR) for production incidents is moving in the wrong direction. Disruptions not only jeopardize critical infrastructure but also have a direct impact on the bottom line of organizations. Swift recovery of affected services becomes paramount, as it directly correlates with business continuity and resilience.

Jenkins pipelines play a pivotal role in achieving continuous delivery in software development processes. Continuous delivery (CD) is a software delivery approach aimed at ensuring that code changes are systematically and automatically prepared for release to production. In modern software development practices, CD pipelines streamline the process of building, testing, and deploying software, enabling organizations to accelerate software delivery and provide value to its customers.

The 2024 SRE Report highlights a pivotal shift in how organizations approach the reliability and monitoring of their services, especially those that extend beyond their direct control. According to the report, 64% of organizations now recognize the importance of monitoring productivity or experience-disrupting endpoints, even beyond their physical control.

As the automation of processes and deployment becomes more prevalent in the manufacturing industry, the need for IT services grows further. The use of complex systems and technologies, such as AI and robotics has become the new normal for manufacturing organizations.

Endpoint Management is so inherent to IT that it is canon in this industry, especially now that remote work is the new normal. Setting a robust system is paramount for any organization that relies on digital devices. These devices are connected to the corporate network and can access its resources, so the goal is to ensure that these devices are secure, compliant with company policies, and operating efficiently.

🚨 To read the full findings from this research, visit The Machine Learning State of Play 2024 white paper. Are the challenges of deploying machine learning (ML) overshadowing its true potential in the modern workplace? Through our recent white paper , we spoke to 500+ developers who have experience working with ML systems to gain an understanding of the pain points faced by developers when using ML solutions.

March was a fun month for OnlineOrNot. I spoke to more customers than ever before, developed a long roadmap for OnlineOrNot's status page functionality (it's going to be an even better stand-alone product), heartbeat checks are going to support cron expressions, and more.