November 2, 2022
Updating and implementing your technology roadmap is critical to meeting ever-changing client demands, reducing costs, increasing security, and keeping ahead of competitors. The top three trends are optimizing (resilience, operations, or trust), scaling (vertical, product delivery, or everywhere), and pioneering (customer engagement, accelerated responses, or opportunities). This blog covers the optimization trend, with future blogs covering the other two topics.
Optimize trends bring together capabilities to optimize IT systems for better reliability, improve data-driven decision-making, and ensure that AI systems retain optimum value in production.
Creating digital immune systems brings together multiple modern practices around the application development lifecycle for software design, development, automation, operation, and analytics to optimize resilience in your systems. By reducing system downtime and security risk, you create a superior customer and user experience without defects or system failure, increasing business performance and translating into higher revenue.
Your organization already monitors the system’s performance using automated tools to collect and analyze system data and translate it into actionable insights to improve system performance. On the other hand, observability measures how well the system’s internal states can be inferred from knowledge of its external outputs. It uses the data and insights that monitoring produces to provide a holistic understanding of your system, including its health and performance.
The observability of your system depends partly on how well your monitoring metrics can interpret your system’s performance indicators. Observability is crucial because it gives you greater control over complex systems. Applied observability involves harnessing the value of observability data to meet the needs of different roles across business and IT. For example, customer observability data will benefit application teams responsible for customer experience. Shortening the latency of your organizational decision-making by moving it from “monitoring” to applying observability results in a competitive advantage by utilizing active and passive metadata to optimize operations rapidly.
In simple terms, make AI trustworthy. Most AI models do not make it into production due to security, ethics, or privacy issues. Resolving these challenges requires a focused approach. An AI Trust, Risk, and Security Management (AI TRiSM) typically requires organizations to implement a best-of-breed tool portfolio approach, as most AI platforms will not provide all the required functionality.
AI TRiSM approaches actively deal with issues that can compromise AI models and data throughout the model’s lifecycle rather than waiting for these to occur in production. It combines methods for explaining AI results, rapidly deploying new models, actively managing AI security, and controls for privacy and ethics issues. The result is reduced AI risk leading to greater user acceptance and more successful delivery of your business goals.
It may be time to evaluate your IT organization to determine where to make changes that can help you optimize your environment. Dewpoint can help you quickly analyze where you are, offer recommendations to improve, and, if needed, support your staff in implementing the recommendations. Contact us today.