Operations | Monitoring | ITSM | DevOps | Cloud

Choosing the best network monitoring tool can be mind boggling. Today, network admins need more than a bare-bones network management system (NMS). They need a tool that includes auto-discovery, node and device inventorying, automatic and configurable warning notifications—all joined through a centralized management interface. Today’s buyers of a NMS need to consider their interactions with the product vendor is. Is the vendor trustworthy? Are their policies client-friendly?

First, let’s address the question of “What is TIBCO EMS?”. TIBCO Enterprise Message Service (EMS) is designed to bring together computing services and assets in order to reduce the cost, time investment, and effort of integrating disparate services across cloud and locally based platforms. TIBCO EMS is one of the market-leading enterprise messaging systems that enable businesses to exchange information in real-time.

Data loss events frequently occur, but it seems that a good portion of companies are not fully prepared for these damaging events. An Avast report states that 60% of all backups performed are incomplete and restores fail 50% of the time. An increasing number of organizations depend on digital data, so data backup and recovery should be a top priority to potentially minimize both downtime and loss of data and ensure continuity of business operations.

One of the easiest transport layer protocols available in the TCP/IP protocol suite is the User Datagram Protocol (UDP). The communication mechanism involved is minimal. With UDP, neither the receiver nor the sender receives any acknowledgements of packets received. This protocol's shortcoming makes it unreliable and easier to process than many other protocols. Although UDP is considered an unreliable transport protocol, it uses IP services to ensure the best attempts are made to deliver data.

Lots of organizations do not invest in any type of asset management software as a result frequently business problems occur such as operations are not streamlined, required assets are not found or sudden equipment failure occurs, and so on. These types of problems only lead to delayed operations, unnecessary expenses, and business loss. When an organization utilizes any asset management software then the expected results are also not achieved.

“Too many cooks spoil the broth.” It’s an old saying we’ve heard many times in childhood. If we put it in today’s IT monitoring context, we could change it to “too many tools spoil the insights and efficiency.” IT teams across organizations have deployed multiple tools over the decades to monitor and track the performance of networks, databases, and applications and to ensure the smooth running of the business.

In the era of technology defined by cloud computing, features evolve at the blinding speed of continuous deployment. When large software development organizations like Microsoft deliver semi-annual releases of products, like SQL Server, the volume of new features can be so large they can be hard to grasp. Microsoft continues to push the boundaries on what’s possible, both in on-premises and cloud data platforms, and they aim to make the life of data professionals much more manageable.

The continuous debate around artificial intelligence (AI) has led to a lot of confusion. There are many terms around it that appear to be similar, but when you take a closer look at them, that perception is not entirely accurate. For that reason, here we take our best shot and oppose AI vs. machine learning vs. deep learning vs. neural networks to set them apart once and for all. In short, we’ll look at how they all relate to each other, and what makes them different in their particular way.

One of the best features of the public cloud is that it utilizes a model that enables multiple organizations to share cloud resources. This approach leverages economies of scale, ensuring each tenant sharing those resources receives a lighter bill than if they utilized a private cloud dedicated to just them. Likewise, multi-tenancy in cloud computing is cloud architecture that enables multiple organizations/customers/users to share resources like virtual machines, storage, and server components.

Kelverion have put together this Azure Automation Best Practices Guide to support the creation of automation process in Azure Automation. Our consultants work with Azure Automation every day and have substantial experience with Azure Automation and IT automation built using other tools. It’s important to recognize that these are recommendations rather than hard and fast rules.