Remove Auto-complete Remove Automation Remove DevOps
article thumbnail

Unleashing real-time insights: Monitoring SAP BTP cloud-native applications with IBM Instana

IBM Journey to AI blog

Introducing the SAP Business Technology Platform The SAP Business Technology Platform (BTP) is a technological innovation platform designed for SAP applications to combine data and analytics, AI, application development, automation and integration into a single, cohesive ecosystem. Why SAP BTP + IBM Instana?

DevOps 231
article thumbnail

Modernizing child support enforcement with IBM and AWS

IBM Journey to AI blog

Automate routine tasks to free up time to provide personalized services and build relationships with families. IBM Operational Decision Manager (ODM) enables businesses to respond to real-time data by applying automated decisions, enabling business users to develop and maintain operational systems decision logic.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Application modernization overview

IBM Journey to AI blog

Application modernization is the process of updating legacy applications leveraging modern technologies, enhancing performance and making it adaptable to evolving business speeds by infusing cloud native principles like DevOps, Infrastructure-as-code (IAC) and so on.

article thumbnail

Boost employee productivity with automated meeting summaries using Amazon Transcribe, Amazon SageMaker, and LLMs from Hugging Face

AWS Machine Learning Blog

They are designed for real-time, interactive, and low-latency workloads and provide auto scaling to manage load fluctuations. Limitations This solution has the following limitations: The model provides high-accuracy completions for English language. Mateusz Zaremba is a DevOps Architect at AWS Professional Services.

article thumbnail

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning Blog

Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. AWS also helps data science and DevOps teams to collaborate and streamlines the overall model lifecycle process. The suite of services can be used to support the complete model lifecycle including monitoring and retraining ML models.

article thumbnail

Deploy Amazon SageMaker pipelines using AWS Controllers for Kubernetes

AWS Machine Learning Blog

DevOps engineers often use Kubernetes to manage and scale ML applications, but before an ML model is available, it must be trained and evaluated and, if the quality of the obtained model is satisfactory, uploaded to a model registry. SageMaker simplifies the process of managing dependencies, container images, auto scaling, and monitoring.

DevOps 117
article thumbnail

Top 25 AI Tools for Software Development in 2025

Marktechpost

AI-powered tools have become indispensable for automating tasks, boosting productivity, and improving decision-making. It suggests code snippets and even completes entire functions based on natural language prompts. It automates code documentation and integrates seamlessly with AWS services, simplifying deployment processes.