Systems | Development | Analytics | API | Testing

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Running Apache Kafka at the Edge Requires Confluent's Enterprise-Grade Data Streaming Platform

Modern edge computing is transforming industries including manufacturing, healthcare, transportation, defense, retail, energy, and much more—pushing data management to far-reaching data sources to enable connected, low latency operations and enhanced decision making. These new use cases shift workloads to the left—requiring real-time data streaming and processing at the edge, right where the data is generated.

Enhance User Scalability and Response Time | Cigniti's Cloud Performance Testing Services

A prominent utility provider faced challenges with client-facing applications, requiring assessing system capabilities under significant loads. Accommodating 50,000 concurrent users within an infrastructure reliant on SQL and IIS, the need for a robust yet cost-effective load-generation setup became paramount.

3 Strategies to Supercharge Developer Operational Efficiency

Developer operational efficiency is crucial for streamlining API management processes and empowering development teams to work more effectively. In this blog post, we'll explore three key tips to unlock developer operational efficiency — leveraging API documentation and self-service credential management, automating API lifecycle management, and optimizing resources and performance — using Kong Konnect and Kong Kubernetes Ingress Controller (KIC).

Unlocking the Edge: Data Streaming Goes Where You Go with Confluent

While cloud computing adoption continues to accelerate due to its tremendous value, it has also become clear that edge computing is better suited for a variety of use cases. Organizations are realizing the benefits of processing data closer to its source, leading to reduced latency, security and compliance benefits, and more efficient bandwidth utilization as well as supporting scenarios where networking has challenging constraints.

Using Swift as a Backend Technology

Swift is a powerful open source programming language created by Apple in 2014 for the iOS, iPadOS, macOS, watchOS, and tvOS, known for its modern syntax, safety features and fast performance. Designed as a successor to Objective C, Swift has become a hugely popular choice for frontend and mobile app development, and it’s also shaping up to be an excellent choice for server-side development.

Embedded Snowpark Container Services Set RelationalAI's Snowflake Native App on Path for Success

Despite the seemingly nonstop conversation surrounding AI, the data suggests that bringing AI into enterprises is still easier said than done. There’s so much potential and plenty of value to be captured — if you have the right models and tools. Implementing advanced AI today requires a solid data foundation as well as a set of solutions, each demanding its own tools and complex infrastructure.

Manage Resource Utilization and Allocation with ClearML

Written by Noam Wasersprung, Head of Product at ClearML Last month we released the Resource Allocation & Policy Management Center to help teams visualize their compute infrastructure and understand which users have access to what resources. This new feature makes it easy for administrators to visualize their resource policies for enabling workload prioritization across available resources.