This August while the total solar eclipse was taking the US by storm, another – albeit less astronomical - event was also inspiring conversations amongst IT professionals everywhere. The Gartner Catalyst Cloud and IoT Conference, an event focused on giving technical pros real-world practices and hands-on advice on how to implement the latest technology solutions, took place in San Diego on August 21-24. While the event did indeed focus on cloud and IoT, three key themes stood out above the rest: Figuring out which applications and how to migrate them to the public cloud was still top of mind among attendees, AI and machine learning continues to be a hot topic, and more and more IT professionals are considering serverless computing.
This year, Gartner kicked off the conference with a Cloud “Bake-off.” Each participating vendor, which included Oracle, Microsoft, IBM and Google, demonstrated how to deploy and scale their database as a service. Cloud database performance and availability were a big focus. Most also gave a short tour of their IaaS consoles, showing how users can manage and monitor their service usage. During the Q&A session, many of the questions focused on how to even start migrating to the cloud. There were concerns about compliance and data integration. Attendees asked analysts for advice on which applications to migrate. Others wondered why enterprises haven’t migrated every workload to the cloud yet.
Oracle Cloud Infrastructure’s VP of Product Management and Strategy, Kash Iftikhar, presented in a session on how to easily migrate enterprise workloads to IaaS. He pointed out that many enterprises haven’t migrated critical enterprise workloads, such as database applications to the cloud, because enterprise IT need assurances that their cloud provider can offer the performance they need. I would add that they may also want to avoid the hidden costs that many vendors charge for high performance scenarios. Oracle Cloud Infrastructure enables enterprises to create database applications on bare metal servers with local NVMe flash or SSD block storage, delivering consistently fast performance. In additional, Oracle’s block volumes scale linearly at $0.05/GB/month, without charging extra for performance.
AI and machine learning are popular topics of conversation in the digital world, and it was no different at Gartner Catalyst. One of the most popular tracks was on AI, Machine Learning and IoT-driven Data and Analytics Architecture. There were sessions on how AI informs data management, machine learning as a service (MLaaS), and on how cloud vendors are building machine learning into their tools and services. During the Cloud Bakeoff, Oracle demonstrated how their aPaaS tools can be used to easily develop a chatbot that uses intelligence to respond to end customers via a Facebook Messenger app. Using Oracle’s services, companies can provide better customer experiences by adapting and offering services and products based on a customer’s responses.
Many of the sessions at Gartner Catalyst also focused on application development and building cloud-native applications. There was a roundtable on how enterprises can build Docker into their environments, and on choosing the right platforms for microservices architectures. There were also many discussions around serverless computing or function as a service, allowing developers to code without needing to manage cloud resources. Attendees asked Gartner analysts which apps were ideal for serverless computing. Gartner analyst Richard Watson recommended treating serverless computing as an addition to an app developer’s toolbox, and not as a replacement for existing tools. Ideal types of apps include those that are event-driven such as responding to a tweet or applications that operate on a scheduled basis.
The Gartner Catalyst event provided a great platform for in-depth conversations between analysts, vendors and technical end-users alike. Unlike other events that may talk about technology trends and considerations at a high level, I believe this event enabled participants from all sides – vendor and customer – to walk away with a better understanding of real-world cloud use cases.