Day: December 2, 2023

When we introduced the concept of data observability four years ago, it resonated with organizations that had unlocked new value…and new problems thanks to the modern data stack. 

Now, four years later, we are seeing organizations grapple with the tremendous potential…and tremendous challenges posed by generative AI. 

The growing importance of AI in business is undeniable, with more than 50% of businesses employing artificial intelligence for security and combating fraud. Additionally, beyond the practical applications for businesses externally, AI can be used internally to deliver better customer experiences through competitive tools and features. As the role of AI within an API business’ operations expands, so do the associated AI infrastructure costs. These expenses can quickly become a significant financial burden if left unchecked. Like all outward facing API-based tools, the key to success is API governance.

That’s where API governance steps in as a way of managing infrastructure costs and avoiding financial setbacks of monumental proportions. API governance allows an organization to regulate and optimize how AI resources and services are accessed and utilized, ensuring that businesses can offer an AI solution and features without breaking the bank. Governance serves as a strategic framework for controlling expenses in an effort to maintain the quality and reliability of offered AI implementation within services and solutions.

You probably are here because you leaked a secret somewhere and want to get straight to rotating the secret. If you are a solo developer or you know for sure you are the only user of the secret and understand what rotating the secret might disrupt, start here: Rotate the secret and store the new credential safely.

If you work in a team and are not sure who uses this secret, what it gives access to, or what outages might occur from rotating it, then please read on.

In the realm of professional pursuits, there exists a common misconception that managing software development is akin to riding a bike – a static skill that, once acquired, can be smoothly pedaled forward with minimal adjustments. However, in the fast-evolving landscape of technology, such a comparison is not only overly simplistic but can lead to profound misjudgments in leadership. Unlike the steadfast predictability of a bicycle ride, software development is a dynamic and ever-changing process that defies the static nature of traditional analogies.

As we celebrate the first birthday of our software endeavors, it's imperative to address the fallacy that managing software projects is as straightforward as steering a two-wheeler down a familiar path. This misapprehension often stems from leaders who, having once mastered coding or project management, find themselves trapped in a mindset that underestimates the fluidity of the software development journey. In this article, we unravel the intricacies of why software development is fundamentally distinct from riding a bike, shedding light on the pitfalls that managers and CTOs may encounter when they cling to static paradigms in a world that thrives on adaptability and innovation. Join us as we explore the dynamic nature of software development and challenge the notion that it can be steered with the simplicity of a handlebar.

The U.S. Securities and Exchange Commission (SEC) recently announced its new rules for public companies regarding cybersecurity risk management, strategy, governance, and incident exposure. Some requirements apply to this year—for example, disclosures for fiscal years ending December 15, 2023, or later have new annual reporting requirements. As a result, organizations are wondering about how these new rules impact them. 

In this post, we’ll help unpack the new rules, what they mean to you, and what your DevOps and DevSecOps teams might need to implement in response.