Tricentis - Where Quality is a Mindset
At Tricentis, we're a dynamic team of dreamers and doers, constantly pushing the boundaries of software quality. We embed quality into every platform, application, and step our customers take.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Keep Calm and Govern(ance) On
See how with the right governance, every team—from devs to data scientists—can build better, smarter, and faster, with confidence.
Choosing The Right LLM: Why Flexibility Is Key
In this Cortex AI roundtable, Snowflake's Arun Agarwal, Yusuf Ozuysal, and James Cha-Earley highlight why AI model flexibility is crucial for real-world applications. Recognizing that no single large language model excels at everything — coding, reasoning, extraction, or conversation — Snowflake Cortex AI brings the strengths of different LLMs together by integrating leading LLMs like OpenAI, Mistral, Anthropic, and Meta into one secure platform.
Hands-on with Apache Iceberg
As organizations move beyond traditional data lakes and warehouses, the need for scalable, performant, and reliable table formats has never been greater. Apache Iceberg is quickly becoming the go-to open-source table format for the modern data stack—bringing the features of SQL tables to the data lake with schema evolution, time travel, partitioning, and ACID transactions. In this exclusive Hevo Learning Lab session, join Alex Merced—Senior Developer Advocate at Dremio and co-author of Apache Iceberg.
Securing, Observing, and Governing MCP Servers with Kong AI Gateway
The explosion of AI-native applications is upon us. With each new week, massive innovations are being made in how AI-centric applications are being built. There are a variety of tools developers need to consider, be it supplying live contextual data via the Model Context Protocol (MCP) or leveraging the new Agent2Agent Protocol (A2A) to standardize how their agentic applications will communicate. The modern AI application can include communication between many different entities, including.
Maximizing GPU Efficiency with ClearML's Unified Memory Technology
AI builders deploying models into production focus on ensuring well-performing models are available for users. Once the model is live, the focus shifts to optimizing GPU usage for efficient deployment. While GPU machines offer the best performance, they are costly to run and frequently remain underutilized.
Test Parameterization Techniques
Test parameterization allows testers to run the same test case with multiple sets of input data, eliminating the need for duplicate test cases. Instead of hardcoding values, testers define variables that can be dynamically replaced during execution. This approach is essential for testing different scenarios efficiently, such as validating multiple user credentials or input combinations without creating separate test cases for each variation.
Data lakes vs. data warehouses: A cost comparison by GigaOm
Adopting a data lake in combination with the Fivetran Managed Data Lake Service reduces data ingest compute costs by 77% to 95% over traditional data warehouses.
#shorts - Your Data Has Something to Say... Are You Listening?
With data alerts in Qlik Cloud , you don’t have to refresh dashboards all day or dig for insights. Set custom alerts that notify you only when something meaningful happens — a dip in performance, a spike in sales, or a key KPI that needs attention.
20 Automation Testing Best Practices For 2025
I’ve been in the automation testing game long enough to watch trends come and go. The biggest lesson I gained after all those year is how going back to the fundamentals is usually the "best" best practice. Here’s the thing — buzzwords mean nothing if you can’t trust your test suite. At the end of the day, it’s not about chasing hype. It’s about doing the basics really, really well. So here are 20 automation testing best practices for 2025.