Streamlining Observability: The Journey Towards Query Language Standardization | Logz.io

The article discusses the need for a standardized query language for observability data and the formation of a working group under the CNCF to develop this standard. The diverse range of query languages currently used in observability creates challenges for DevOps professionals, such as switching between languages and maintaining consistency. A unified query language would enable interoperability between different observability providers and simplify the development of tools and frameworks. The working group aims to compile feedback from the community to create a recommendation similar to SQL for databases. Interested individuals are encouraged to join the working group to contribute to the development of observability query standards. #observability #querylanguage #standardization #softcorpremium

The Dynatrace Platform Subscription model enables broad Infrastructure Monitoring

Dynatrace has launched a subscription model that enables customers to scale their observability and security needs on demand. The Dynatrace Platform Subscription offers a flat rate for infrastructure monitoring and metrics are pooled. This allows for broader deployments, faster reaction times, and better availability, resulting in improved customer satisfaction. The subscription model is designed for auto-scaling infrastructure, allowing for precise usage tracking and billing. The new subscription is available for both new and existing Dynatrace SaaS customers. #DynatracePlatformSubscription #ObservabilityOnDemand #AutoScalingInfrastructure #softcorpremium

Olive: A user-friendly toolchain for hardware-aware model optimization - Microsoft Open Source Blog

Microsoft has introduced Olive, a toolchain for hardware-aware model optimization that streamlines the process of optimizing machine learning models to efficiently use specific hardware architectures. Olive composes effective techniques in model compression, optimization, and compilation, and intelligently tunes the most appropriate optimization techniques to generate highly efficient models for inference. It currently supports a range of optimization techniques, including model quantization tuning, transformer optimization, and ONNX Runtime performance tuning. Olive also considers various constraints such as accuracy and latency to ensure the optimized models meet specific requirements. The toolchain is easy to use and handles the complex optimization process, ensuring the best possible performance without the hassle. #MicrosoftOlive #HardwareAwareOptimization #EfficientMLModels #softcorpremium