Operations | Monitoring | ITSM | DevOps | Cloud

At first glance, AWS Config seems like a no-brainer for tracking changes, catching misconfigurations, and proving compliance. But beneath the surface, Config pricing can get surprisingly intricate. Costs don’t just depend on the number of resources you monitor. They also hinge on how often those resources change, how many rules you evaluate, and how you manage historical data. In this guide, we’ll demystify AWS Config pricing.

In our post, 9 Continuous Delivery Tools For Reliable Releases, we explored why continuous delivery is critical to building robust development pipelines — and how it helps teams deliver customer value while boosting the bottom line. Today, we’re diving into the next evolution of that pipeline: continuous deployment. Today’s technology companies need to release quality features quickly and put them in users’ hands even quicker.

We recently explored what the cloud is and how it has evolved over 60 years. Yet, cloud computingWe recently explored the cloud and how it has evolved over 60 years. Yet, cloud computing emerged into what it is today in 2002, when Amazon, the e-commerce giant, sought a more efficient way to expand its online marketplace. So, it is unsurprising that the company’s cloud services subsidiary (AWS), which launched in 2006, is today’s largest Cloud Service Provider (CSP).

It came as a pleasant surprise. CloudZero recently discovered over $1.7 million in annualized savings. And, all from our own infrastructure. Otherwise, we would have spent $1.7 million on cloud resources we didn’t actually need. Cloud savings stories like this are common with CloudZero customers, and we often find companies spending more than they should in the cloud. If your team is also struggling with managing and controlling the cost of cloud computing, then this guide is for you!

Amazon Web Services (AWS) powers everything from scrappy startups to Fortune 500 giants. So, AWS interview questions are relevant for all kinds of roles, from infrastructure design to cost governance. Now, while some interviews test definitions and acronyms, the best ones dig deeper. They explore how well you understand AWS trade-offs—think of performance vs. cost, scalability vs. complexity, or security vs. usability.

Cloud computing empowers organizations to access IT resources on demand, over the Internet, and on a pay-per-use basis. Thus, your company does not need to purchase, install, operate, and upgrade hardware for physical data centers. Instead, you can rent resources as needed from cloud service providers such as Amazon Web Services (AWS). For instance, AWS provides compute, storage, database, networking, machine learning, data lake, analytics, security, and IoT resources/services.

We all want growth, but often find ourselves unequipped to deal with it. It’s a bit like going to the gym, lifting weights, and seeing real results, only to realize that you no longer fit into your old clothes. Now you have to decide whether to modify them or buy new clothes. We can use this very simple analogy to understand horizontal vs. vertical scaling.

Google Cloud Platform (GCP) might not always be the loudest name in the cloud room. But it’s gradually become a powerhouse for organizations running data-intensive, AI/ML, and global-scale applications. We also can’t ignore that GCP offers a backbone powered by Google’s own infrastructure (the same one that runs YouTube, Gmail, and Search).

Cloud computing was already booming before 2020. But in the following two years, remote work flourished, and cloud adoption soared. The trend continues to accelerate — even faster now. Some companies have since returned to the office. Others are adopting hybrid models, balancing work-from-home and in-office. Yet, there’s more to the rise of cloud computing than remote working.

As AI adoption increases, the race to real, durable AI value intensifies. Almost every organization that can use AI is using AI — but one of the most troubling trends I’ve observed revolves around talent. Right now, most organizations use AI to increase internal efficiencies — do quick research, write quick emails, start a new project at the 50% mark rather than the 0% mark, etc. But some executives I’ve talked to are taking a more aggressive approach.