Klien: RedHat UK
Format: E-Buku
Saiz: 1.74 MB
Bahasa: Bahasa Inggeris
Tarikh: 25.07.2024
Accelerate your IT automation with AI: Realize the value of mission-critical automation with Red Hat Ansible Lightspeed
To overcome these challenges, platform engineering and developer teams need to rely on enterprise-wide automation to operate more reliably and efficiently. The productivity, consistency, and reliability afforded by automation is no longer a nice-to-have—it’s now mission critical to every modern organization.
Accelerating an automation content pipeline can be challenging, even when relying on solutions as intuitive as Red Hat®Ansible®®Automation Platform. Organizational skill gaps persist, leaving automation content creation in the hands of a few, making it difficult to democratize content creation across users and improve adoption of automation. Busy operations teams have limited time to learn new skills or train to improve existing skills, while developers find code maintenance repetitive and mundane.
Currently, artificial intelligence (AI) technologies are on the rise. A plethora of new applications are flooding the market, each promising to make modern businesses more efficient, improve time to value, and enhance productivity. Yet the publicly available, non-enterprise AI tools that generate automation content are fraught with inherent challenges that make them unpalatable for many businesses. These challenges include contending with inaccurate or malicious code from unverified sources leading to concerns about trust, reliability, and accuracy. Over time, code maintenance becomes even more problematic and time consuming.
Accelerating an automation content pipeline can be challenging, even when relying on solutions as intuitive as Red Hat®Ansible®®Automation Platform. Organizational skill gaps persist, leaving automation content creation in the hands of a few, making it difficult to democratize content creation across users and improve adoption of automation. Busy operations teams have limited time to learn new skills or train to improve existing skills, while developers find code maintenance repetitive and mundane.
Currently, artificial intelligence (AI) technologies are on the rise. A plethora of new applications are flooding the market, each promising to make modern businesses more efficient, improve time to value, and enhance productivity. Yet the publicly available, non-enterprise AI tools that generate automation content are fraught with inherent challenges that make them unpalatable for many businesses. These challenges include contending with inaccurate or malicious code from unverified sources leading to concerns about trust, reliability, and accuracy. Over time, code maintenance becomes even more problematic and time consuming.
