Operations | Monitoring | ITSM | DevOps | Cloud

High-quality cloud cost allocation has become an existential issue for businesses. In order to get as much out of their (mounting) cloud investments as possible, business leaders need to know how much they’re spending in the cloud, what/who they’re spending it on, and whether there’s a good reason for it. In its ideal form, cost allocation answers all these questions.

For a successful business, you need to introduce an effective monitoring system covering all areas of your business and infrastructure - servers, databases, services, overall traffic, and even revenue collected. The users of this monitoring system can be system administrators, software engineers, information engineers, as well as all sorts of analysts.

In this podcast, our panellists discuss the foundations that any team needs to put in place when designing their incident management process. Starting from the basics of defining what we really mean by an incident, to how to set your severity levels, roles and statuses, Chris and Pete share their tips for building solid foundations to run your incidents.

Why do some organizations excel in streamlining their database operations and applications development while others find it immensely challenging? Why can some database teams embrace agility while others take months of cycles to deploy even a single line of code? What secret sauce can allow some database teams to work smarter (not harder), streamline database development lifecycles better, get to deployment faster, and create an overall stronger alignment across departments?

As a former incident responder and now as a responder advocate for FireHydrant, I’ve seen the “build vs. buy” debate play out many times. In fact, I even supported the tool that former employers used for managing incidents for years before they decided to buy (more on that in a future blog post).

History will look back on this period of the 21st century as a pioneering, resilient, and excitingly disruptive time. We’re deep into a dynamic era as the cloud, Artificial Intelligence (AI), IT automation, and digital transformation converge to drive challenges and dazzling opportunities. The sheer force and potential of AI—coupled with unprecedented security risks and ongoing infrastructure advances will shape enterprises for years to come.

Distributed denial of service (DDoS) attacks are an ongoing issue for communications service providers, putting critical systems at risk, undercutting service level agreements, and bringing unwanted headlines. In the first half of 2022 6 million of these attacks were reported. Some metrics of DDoS attacks in 1H2022 compared to 2H2021.

DevOps is the modern convergence of people, processes and tools to create a continuous software delivery stream. Much like the code it produces, the concept of DevOps itself is continuously adapting to encompass new ideas, methods, and technologies. So what can we expect from the DevOps cultural shift in the future? The delivery stream of yesterday was a segmented process, often separating key teams and concepts into silos where people focused on their individual tasks.

Most well established data teams have a clear remit and a well defined structured for what they work on and when: from the scope of their role (from engineer to analyst) to which part of the business they work with. At incident.io, we have a 2 person data team (soon to be 3) with both of us being Product Analysts.