Welcome to the engineering metrics guide for team success. Engineering metrics are data that teams can use to make informed decisions and operate at maximum efficiency. Don’t use CI on your team? Learn why continuous integration is key to increasing deployment frequency.
In our blog we have posted a few articles about data centers. We like them. They have grown on us. It is a branch of technology that interests us as much as bitcoin interests brothers-in-law or neighborhood projects interest retirees. For that reason, today, in our blog, we will deal with data management as a service or DMaaS.
As more and more businesses and individuals choose to store their data online, ensuring the safety of information is becoming exceptionally crucial. According to recent statistics from the Hosting Tribunal, over 95% of IT professionals use cloud storage. This number is expected to grow steadily.
Network downtime opens the gates to productivity loss and customer attrition and can affect business growth moderately or even severely. Usually, the reasons behind a network outage are the following: Errors in network endpoints: Things like a network bottleneck or a spike in temperature can interrupt a client’s network operations and then snowball into an outage. Operational slip-ups: According to research done by Uptime Institute, 70% of data center and service downtime is due to human error.
The concept of AIOps is simple: Infuse artificial intelligence(AI) into IT to make operations speedier and more efficient. In theory, AIOps at its best should lead to an autonomous IT environment in which functions can run themselves with little or no human intervention. In practicality, the path to this nirvana state is anything but straightforward and raises several questions. Where should you start? How do you measure the value? Is AI ready to scale across production environments?
