Operations | Monitoring | ITSM | DevOps | Cloud

For good or for ill, technology is constantly shifting and with it, the roles of those who manage that technology also shift. This is no different for a DBA than it is for a developer, an admin, or analyst. As new technology, like the adoption of the cloud, changes the role, people start to question whether or not there’s even a need for a DBA. The shortest possible answer to that question, in my opinion, is “Yes”.

Businesses both small and large require agility in how they handle device firmware and network configurations. For large networks especially, manual monitoring and change implementation can be inefficient. As such, more and more IT departments turn to automated network configuration management tools with bulk change capabilities.

One of the most common questions database professionals are asked by their systems and virtual machine (VM) administrators is “Why does the database server need so much memory?” You’ll get a more detailed answer to that question later in this post, but it’s important to understand a database engine is almost like a server within a server.

Chia cryptocurrency is based on Proof Of Space, and distribute tokens according to a mechanism called plotting. In the last weeks, we've seen a lot of new accounts trying to launch and operate Chia miners from FlashDrive's infrastructure. Most of those accounts where created with fake/stolen credit cards for the sole purpose of getting Chia coins for free.

Datadog’s infrastructure list provides a central, high-level view of every host in your environment and pulls together metadata and relevant metrics from across Datadog to help you get the full picture of each one. You can easily filter and sort the list using any host tags, letting you quickly view the status of the parts of your infrastructure you need.

Big data analytics help organizations use data to explore both new and improvement opportunities. Whichever cloud data platform you choose, there are two data storage technologies you will want to understand. Data warehouses and data lakes are the two dominant data solutions commonly used for defining how an organization stores, queries, analyzes, and reports on big data. This post will define what a data warehouse and data lake are, how they work, and their differences.

We’re happy to announce our integration with Google Meet to create incident bridges automatically. Using the power of FireHydrant Runbooks, a Google Meet can be added with fully customizable titles and agendas based on your incident details.