Dynatrace
JANUARY 23, 2024
AI-enabled chatbots can help service teams triage customer issues more efficiently. Deriving business value with AI, IT automation, and data reliability When it comes to increasing business efficiency, boosting productivity, and speeding innovation, artificial intelligence takes center stage. What is explainable AI?
Dynatrace
SEPTEMBER 13, 2023
This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.
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Adrian Cockcroft
NOVEMBER 26, 2023
SUS101: Sustainability innovation in AWS Global Infrastructure AWS is determined to make the cloud the cleanest and most energy-efficient way to run customers’ infrastructure and business. This includes providing the efficient, resilient services AWS customers expect, while minimizing their environmental footprint.
KeyCDN
FEBRUARY 22, 2023
Chatbots and virtual assistants Chatbots and virtual assistants are becoming more common on websites and web applications as they provide an efficient and convenient way for users to interact with a business. The main benefits of serverless architecture are cost savings and scalability.
Percona
FEBRUARY 24, 2023
Making the use of resources efficiently and ensuring that this does not impact the budget available for cloud computing is not a one-time fix but a continuous cycle of picking properly sized resources and eliminating over-provisioning. Figure 5: Experimental PostgreSQL Vacuum Monitoring What about serverless?
Adrian Cockcroft
FEBRUARY 13, 2023
The keynotes didn’t feature anything new on carbon, just re-iterated the existing path to 100% green energy by 2025. We also may choose to support these grids through the purchase of environmental attributes, like Renewable Energy Certificates and Guarantees of Origin, in line with our Renewable Energy Methodology.
The Morning Paper
JUNE 13, 2019
.” If we want an increasing number of applications to use machine learning, we must automate issues that affect ease-of-use, performance, and cost efficiency for users and providers… Despite significant research, this is missing right now. We’d like to pack models as efficiently as possible on the underlying infrastructure.
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