Kong AI Gateway Demo: Streamlining Multi-Provider LLM Usage, Security & Monitoring
Timestamps: This demo showcases the latest features and enhancements in Kong's AI Gateway, as of the June 2024 release.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
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Simple, Sustainable, and Secure Storage for Mid-sized Enterprises
The mid-sized enterprise is the fastest-growing market opportunity for data storage. But not just any storage system will do. These days, mid-sized enterprises must handle the complexities of unremitting data growth and distributed infrastructure, meet sustainability goals, manage the diverse storage needs of mission-critical applications, and respond to user requirements. Oh, and they need uninterrupted access to their data no matter what.
An Introduction to Active Data Governance
The way that companies govern data has evolved over the years. Previously, data governance processes focused on rigid procedures and strict controls over data assets. But now, with the data-driven culture, modern enterprises are adopting an agile approach toward data governance that primarily centers around data accessibility and empowering business users to take responsibility for governing and managing data.
Where Does Data Governance Fit Into Hybrid Cloud?
At a time when artificial intelligence (AI) and tools like generative AI (GenAI) and large language models (LLMs) have exploded in popularity, getting the most out of organizational data is critical to driving business value and carving out a competitive market advantage. To reach that goal, more businesses are turning toward hybrid cloud infrastructure – with data on-premises, in the cloud, or both – as a means to tap into valuable data.
Down the AI Rabbit Hole: Leveraging AI in Your Projects Without Ending Up Lost in Wonderland
Generative AI is transforming the world around us, and is quickly becoming a part of the conversation as we greenfield new features and applications. It is very alluring to deliver AI features into our existing products, and think about new projects we might build around AI. However, you might have already found that the journey into the realm of AI often feels like tumbling down the rabbit hole into wonderland - a maze of complexity and uncertainty.
Build maps in the cloud with BigQuery DataFrames, Gemini, and CARTO
Using BigQuery DataFrames with CARTO visualization tools can help Python users access cloud-native analytics and generative AI services.
Using Moesif, AWS, and Stripe to Monetize Your AI APIs - Part 1: Integrating The Platforms
As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.
Find and Share Test Builds Faster and More Securely: Introducing New Artifact and Private Install Pages
Discover the new Artifact Details page and Private Install page from Bitrise, offering detailed artifact information that's easy to find, and secure to share.
Overcoming AI Adoption Challenges: A Fireside Chat with Marco Palladino
Timestamps: In this fireside chat, Marco Palladino, CTO & co-founder at Kong, takes questions from the audience.
Which Language Should Testers Use?
Should you design tests in the same language as the application you’re testing, or should you use the language you’re best at? @Hanson Ho recommends using the language that’s most popular in the application’s platform. This way, you’ll have more help available from the community. If you want more insights like this one, check out Test Case Scenario.