Operations | Monitoring | ITSM | DevOps | Cloud

For years, enterprises have been employing monolithic applications with complex functional frameworks. But today, with advanced solutions built ith API’s and Microservice architecture are putting an end to their realm. With ever-changing requirements in the IT world, enterprises are required to adopt advanced applications with sophisticated features and functions that can accommodate changes throughout.

Many IT professionals think of Graylog primarily as a security (SIEM) solution, and of course it can be used in that way to great effect. However, Graylog’s industry-leading log aggregation, search, visualization, and classification capabilities go far beyond that role alone.

Want to access your Splunk data on the go? We’re making it easier than ever to unlock value from your data anywhere at any time. Regardless of your role or level of technical expertise, you can use Splunk Mobile to view dashboards and take action from your mobile device.

New regulations like virtual banking licensing frameworks, advances in open banking and big techs rapidly gaining ground in financial services, are dramatically changing the banking landscape, forcing incumbents to reinvent themselves. To be successful, the bank of the future will need to embrace emerging technologies, focus on providing exceptional customer experiences and take a more holistic approach to ‘change’.

Many of you are familiar with Splunk’s Machine Learning Toolkit (MLTK) and the Deep Learning Toolkit (DLTK) for Splunk and have started working with either one to address security, operations, DevOps or business use cases. A frequently asked question that I often hear about MLTK is how to organize the data flow in Splunk Enterprise or Splunk Cloud.

The artificial neuron was first hypothesized in the 1930s, but only in the last decade have we seen the widespread application of artificial neural networks and machine learning to everyday technologies. Broadly speaking, machine learning describes a technical discipline defined by computer algorithms that improve automatically through experience and the use of data. These days, the combination of machine learning and "big data" power an increasing number of digital tools that we interact with daily.

For our latest specialist interview in our series speaking to technology leaders from around the world, we’ve welcomed James Kaplan CEO and Co-Founder of MeetKai. He founded the startup with his Co-Founder and Chairwoman, Weili Dai, after becoming frustrated with the limitations of current automated assistants. Kaplan has had a true passion for AI and coding since he was six. He wrote his first bot at only nine years old and wrote the first original Pokemon Go bot.