Modern applications are increasingly built as vast, intricate, distributed systems. These systems comprise various software modules, often developed by different teams using different programming languages and deployed across hundreds to thousands of machines, sometimes spanning multiple data centers. Given the ir scale and complexity, these applications are often designed to tolerate failures and performance issues through inbuilt failure recovery techniques (e.g., hardware or software redundancy) or extern al methods (e.g., health check - based restarts). Computer systems experience frequent failures despite every effort: performance degradations and violations of reliability and K ey Performance Indicators (K PI s) are inevitable. These failures, depending on their nature, can lead to catastrophic incidents impacting critical systems and customers. Swift and accurate root cause identification is thus essential to avert significant incidents impacting both service quality and end users. In this complex landscape, observability platforms that provide deep insights into system behavior and help identify performance bottlenecks are not just helpful -- they are essential for maintaining reliability, ensuring optimal performance, and quickly resolving issues in production. The ability to reason a bout these systems in real - time is critical to ensuring the scalability and stability of modern services. To aid in these investigations, observability platforms that collect various telemetry data t o inform about application behavior and its underlying infrastructure are getting popular .

Much has been made of the potential for people to lose their jobs to machines but, according to a senior tech executive, it's all about having employees use artificial intelligence themselves. "AI is not going to replace managers but managers that use AI will replace those that do not," Rob Thomas, senior vice president of IBM's cloud and data platform, told CNBC's "Squawk Box Europe" on Monday. "This really is about giving our employees, our executives, superpowers … One of the biggest things we saw take off with the pandemic was virtual assistants, so how do you care for employees, how do you care for customers in a distributed world and that's why we've seen hundreds of different organizations going live with things like Watson Assistant," Thomas added, referring to the company's AI customer service software. Technology is set to have a significant effect on employees. Machines and automation are set to eliminate 85 million jobs by 2025, according to the World Economic Forum's Future of Jobs Report 2020, published in October, although overall WEF expects 97 million new jobs to be created.

IBM today acquired Instana, a German-American software firm that specializes in developing application performance management software. The acquisition represents IBM's continued investment in hybrid cloud, big data, and AI capabilities. Terms of the deal weren't disclosed. As workflows evolve, organizations are moving away from monolithic apps toward more complex distributed systems. With this evolution, application performance monitoring and system observability have become key areas of investment.

The potential for Machine Learning to make DevOps faster, better and smarter has been hotly contested as one of the main areas to watch in the future of technology for 2018 and beyond. The rise in enterprises, of all sizes, adopting DevOps methodologies has risen in parallel to the prevalence and accessibility of Machine Learning, therefore it only logical that there has been a trend towards considering how these two areas can collide to produce successful outcomes in the endeavour to further streamline workflows. On 29 - 30 November, RE•WORK is hosting the Machine Learning for DevOps Summit in Houston, Texas, to bring together influential industry experts, disruptive startups and leading researchers to discover how to optimize DevOps and enhance automation capabilities with Machine Learning. The summit will be an opportunity to learn the best practices for implementing Machine Learning tools in DevOps to ultimately deliver more value to your business and achieve better automation through more efficient problem solving reduced operational complexity, and increased collaboration. In the run-up to the summit, we want to keep you informed on the up-to-date news surrounding Machine Learning, it's latest effects on DevOps methodologies, and why organizations should waste no time in exploring how Machine Learning can benefit their DevOps strategy.

June 6, 2018 – Berlin at the AWS Summit – Instana, the leader in APM solutions for monitoring dynamic containerized microservice applications, today announced the extension of performance monitoring support to a broad range of Amazon Web Services (AWS) products including AWS Lambda, Amazon's premier Serverless Computing platform. In addition to the release of the new monitoring sensors for AWS native platforms, Instana also announced that their AI-powered APM solution is now available through the AWS Marketplace. "More business applications are operating in a hybrid environment, incorporating traditional monolithic applications, wrappered with a new microservice stack, and using native AWS services. It's now also common to see customers starting to use AWS Lambda Functions for specific microservices as well," said Mirko Novakovic, Instana CEO. "This level of complexity requires the ability to monitor the whole environment with a single solution that can give DevOps the required observability to see and address problems, no matter where they reside."

June 6, 2018 – Berlin at the AWS Summit – Instana, the leader in APM solutions for monitoring dynamic containerized microservice applications, today announced the extension of performance monitoring support to a broad range of Amazon Web Services (AWS) products including AWS Lambda, Amazon's premier Serverless Computing platform. In addition to the release of the new monitoring sensors for AWS native platforms, Instana also announced that their AI-powered APM solution is now available through the AWS Marketplace. "More business applications are operating in a hybrid environment, incorporating traditional monolithic applications, wrappered with a new microservice stack, and using native AWS services. It's now also common to see customers starting to use AWS Lambda Functions for specific microservices as well," said Mirko Novakovic, Instana CEO. "This level of complexity requires the ability to monitor the whole environment with a single solution that can give DevOps the required observability to see and address problems, no matter where they reside."