Data centers are some of the most critical pieces of infrastructure on the planet. Without them, many of the biggest companies would not be able to operate as they do. That’s why it is so crucial to make sure you are keeping a close eye on your data center’s performance. Data centers and server rooms are, according to some sources, getting smaller. Cloud computing, too, is moving things off-site. However, that doesn’t make them any less critical.

Up to 90% of businesses are now using cloud computing to some extent. These companies are also conducting up to 60% of their work via the cloud. This data clearly shows us that cloud environments are, at last, in the mainstream. However, there is still some confusion over the different types of cloud environment. While it is easy to assume that one cloud ‘fits all,’ different types serve differing purposes.

In the modern age, all businesses rely on technology. Any company based in an office will depend on networking, too. But how can you be sure that your network is working hard enough for you? No matter the size or shape of your business, it pays to be careful. Without some form of monitoring solution, you, your team, and your revenue are at the mercy of your technology. For many companies, managed network monitoring solutions are essential. It is an industry that is worth $207 billion worldwide.

Monitoring your network is essential if you want to make sure you are protecting your productivity. However, knowing where to start is a challenge. That’s why there are multiple network monitoring tools available. But how do you necessarily know which are likely to work best for you? In this guide, we will look at some of the most popular network monitoring software available. We will also consider what each model does to help support network management in real-time.

When it comes to data centers, what is ‘peak performance’? Is it a case of using a data center monitoring system so that it works to full capacity? Or, is it more a case of maximizing its potential? Data centers are complex but integral, which is why, for the average business, achieving the best results can be difficult. Challenges for data center operations will differ from firm to firm.

The data center is a remarkably complex structure. However, they are crucial to the everyday running of even the smallest businesses and enterprises. Whether in-house, cloud, or hybrid, the average data center management requires specialist knowledge and meticulous oversight for max efficiency. That is one reason, at least, why machine learning is emerging as an ideal partner for centers of the future.

Growth for an enterprise is an exciting thing, but it often presents a unique challenge for IT professionals. There are common roadblocks that are encountered when trying to upscale an IT management environment. In this second blog of our Managing IT Infrastructure at Scale series, we discuss how to find the happy medium between monitoring software scalability and ease of use.

An application is not just a small part of any business. It would be wise enough to say that an application itself is a company’s business in today’s digital world. This is the reason why application performance monitoring problems are the biggest hurdle for IT Teams and the growth of any business. Customer expectations from the application’s performance are changing every day. Today, customers don’t have patience and want to use any application flawlessly.

What an amazing year it has been at Netreo! We’re honored to have been able to support your IT monitoring and management efforts in 2020 – and here are some highlights of the product releases, news, and content from Netreo throughout the year to support you in your IT monitoring needs!

Now, more than ever, Information Security is a topic that should not be taken lightly. All organizations are vulnerable through technology and it is imperative that risk is managed on a daily basis. Netreo realizes the only way to safeguard against threats is to take a holistic approach to managing our technology, people, and processes.