The latest News and Information on DevOps, CI/CD, Automation and related technologies.
From setting up new hires with everything they need to get to work to troubleshooting technical difficulties, IT teams often field the same kinds of requests over and over. And while each request might feel like a small task, collectively they can add up to a huge time sink in the long run.
Database backup protects your data by creating a copy of your database locally, or remotely on a backup server. This operation is often performed manually by database administrators. Like every other human-dependent activity, it is susceptible to errors and requires lots of time. Regularly scheduled backups go a long way to safeguarding your customers’ details in the case of operating system failure or security breach.
Software engineering teams that adopt “as-code” practices, like using configuration files and automated workflows instead of manual configuration and tools, gain major improvements in velocity. But even companies that enjoy the success of as-code practices for development and delivery lag behind in applying them to operational concerns like monitoring and observability.
Observability is a new term that’s slowly entered the mainstream over the last two years. Today it’s used in the context of monitoring, but it’s much more than that. And it also goes way beyond visibility. So, in this blog, we set out to explore observability vs visibility and find out, what’s the difference? In a recent podcast, our friends at Riverbed neatly explained that seeing and observing are two different things, and can be compared to hearing vs listening.
To supervise the behavior of distributed applications and track the origin of service failures and downtime, developers often use traditional monitoring technologies and tools. However, this approach can fall short in its ability to measure the overall health of modern cloud-native architectures, which can span multiple hosting environments and encompass hundreds of microservices.
In a perfect world, your Configuration Management Database (CMDB) acts as the single source of truth for all your IT device inventory and the relationships between those devices. However, maintaining accuracy is easier said than done. That’s because the traditional method for provisioning and maintaining a CMDB is complex, unwieldy, and outdated the second it's updated. To keep up with the needs of a modern CMDB, an automated discovery and dependency mapping (DDM) solution is a must.