Operations | Monitoring | ITSM | DevOps | Cloud

On May 7th and 8th, 2026, Amazon Web Services (AWS) experienced an outage affecting Amazon Elastic Compute Cloud (EC2) in the dreaded US East 1 region. The original region of AWS located in Northern Virginia, us-east-1 or just “US East” as it is known, has been the subject of some of the internet’s most high profile and destructive outages and remains Amazon’s least reliable region.

Key takeaway: Granting AI agents unrestricted access to cloud infrastructure is an unacceptable security risk. Upsun provides a "zero-trust" framework by utilizing isolated, production-perfect preview environments that allow AI to be productive without the risk of a hallucinated production outage.

Today, roughly 94% of enterprises are projected to use some form of cloud service, with 82% adopting hybrid models that combine cloud and on-premises infrastructure. By 2030, around 60% of all corporate data is expected to be stored in the cloud, highlighting a major shift away from traditional storage systems toward distributed, on-demand infrastructure. With such a huge amount of data, companies need a scalable, affordable, and secure method to store 1 PB.

If an AI agent in your development workflow needed to spin up a test environment tonight, how many manual steps would stand between the request and the environment being ready? By early 2026, AI agents have transitioned from simple code assistants to first-class platform citizens. They are running test suites, analyzing performance, and triggering deployments.

A few weeks ago, a group of engineering leaders I trade notes with got into it over a question none... A few weeks ago, a group of engineering leaders I trade notes with got into it over a question none of us has a clean answer to: How much should you let an engineer spend on AI? One SVP at a company of similar size and stage is in calibration mode and capping engineers at $200 per month. Hit the cap, you can self-bump by $100. Hit that, you need your manager. I told the thread our number. $5,000.

Feature pricing or per-feature pricing is a common SaaS pricing model for good reasons. Here’s how it works, including real examples and how to do it. The best pricing strategy for your SaaS business will depend on your specific business model, target market, and competition. You’ll also want to test different pricing strategies to see which one works best for you. That said, feature-based pricing can be a very profitable way to price SaaS products. Here’s how it works.

Cloud cost data is most useful when teams can adapt it to their own reporting and planning needs. In addition to viewing cost breakdowns, FinOps teams often need to calculate forecasts, reshape datasets, and present tailored views to finance and leadership teams. In many workflows, those steps happen outside the observability platform. Once the data is exported, it quickly becomes outdated and requires repeated manual updates.

Over the past decade, cloud computing has evolved from an emerging technology into the foundation of modern digital infrastructure. However, the latest industry research shows that the industry has now crossed a critical threshold. The conversation is no longer about whether to adopt cloud, cloud-native technologies, or AI. Instead, it has shifted toward operational efficiency, economic predictability, and infrastructure at scale.

When was the last time you asked a developer if they actually use the platform you built for them, or whether they’ve found a faster way around it? We talk with companies every day who deal with this exact scenario. They spend months or even years building their IDP. Then a new project requires a stack or workflow that the IDP doesn’t support. The developer is under pressure to deliver, so they spin up their own solution. This is why most IDPs fail quietly.