Operations | Monitoring | ITSM | DevOps | Cloud

More than 17 million developers use Docker to build, ship, and run applications separate from their infrastructure in order to deliver software faster and more efficiently. With the rising popularity of containerized applications, however, it has become increasingly more complex and difficult to observe and monitor applications running across multiple containers.

Website uptime is one of the most crucial metrics to monitor, particularly if your website is essential for generating revenue. If no one can access a website, all the work and effort you put into getting a website up and running can be gone. With website uptime monitoring, you can keep track of when and how long your website is unavailable. Website uptime monitoring is a crucial component of website management.

Our latest webinar shows how you can put IT process automation to work for your enterprise.

Power has a way of flowing towards people managers over time, no matter how many times you repeat “management is not a promotion, it’s a career change.” It’s natural, like water flowing downhill. Managers are privy to performance reviews and other personal information that they need to do their jobs, and they tend to be more practiced communicators.

One of my favorite consulting questions to ask when dealing with a scalability problem is, “If you could change the system design with the knowledge you have today, what would/wouldn’t you change and why?” Sometimes it’s best to ask this question on a one-on-one basis with different developers, DBAs, report writers, and architects to get honest answers that aren’t intimidated by the other people sitting in a meeting or to avoid potential debating and arguing over a solution.

Today’s blog post will give an insight into one of the many things that improved with Icinga DB: how host and service history is written to the database, both by the old IDO feature, as well as what has changed with Icinga DB and how this leads to more reliable results.

Systems and applications alike have become progressively distributed as microservices, open-source tools, and containerisation have gained traction. In order to actively monitor and respond quickly to issues that arise in our environment, distributed tracing has proven to be vital for businesses such as Uber, Postmates, Hello Fresh and TransferWise. It is, however, important to clarify what distributed tracing actually means.

Machine learning has crossed the chasm. In 2020, McKinsey found that out of 2,395 companies surveyed, 50% had an ongoing investment in machine learning. By 2030, machine learning is predicted to deliver around $13 trillion. Before long, a good understanding of machine learning (ML) will be a central requirement in any technical strategy. The question is — what role is artificial intelligence (AI) going to play in engineering?