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IBM is increasing developer capabilities in the era of open hybrid cloud


As we’re hearing at Think 2021, we are at an inflection point for enterprise developers, with more responsibility shifting to you and your work as the critical success factor for hybrid cloud environments. You already face the dilemma of needing to create and deploy new features as quickly as possible while maintaining high availability and resiliency for existing applications, and those challenges will only increase as more critical workloads move to the cloud.

A recent IBM Institute for Business Value study found that a typical enterprise uses nearly 8 clouds from multiple vendors, and in the next three years, hybrid cloud adoption is expected to grow by 47%. The average organization will be using nearly 6 clouds. To help ease this transformation, my team’s goal is to help you build together: increasing capabilities for developers and lifting burdens that have previously hindered your innovation.

Automating Tasks

Our enterprise customers are looking for AI solutions that will scale with trust and transparency to solve business problems. As applications are modernized and microservice architectures are adopted with more services being created and deployed in production, more points of potential failure are introduced. Addressing these challenges and building together requires a team approach across disciplines.

IBM’s comprehensive automation platform can give your team an edge by combining operational data from your applications and alerts and logs from your IT infrastructure into a single model that can be leveraged by AI and machine learning to understand relationships and derive deep insights. Here are a couple examples of how this comprehensive platform can help you:

  • IBM Cloud Pak for Watson AIOps provides feedback loops for predictions and process improvements at every phase of the lifecycle. This is key for DevSecOps processes, which need foresight and hindsight for effective end-to-end process optimization. The goal is to go from reactive management of symptoms to the predicting of incidents before they happen and proactively avoiding them. To achieve this, you need to look carefully at the software development lifecycle at each step, including design, code, test, deploy, operate, and monitor. Examples of process improvements include code provenance (code), test coverage (test), change risk (deploy), and log/metric anomaly detection (operate) to name just a few.

  • IBM Cloud Pak for Integration is delivering AI-powered automation to help you deliver solutions in less time with greater resiliency. As a developer, you’re being asked to connect and coordinate business processes that run in different parts of IT environments that are now hybrid and multi-cloud in nature. AI-powered automation can help you build these integrations faster by delivering dynamic analysis of operational and developer data. For example, test generation creates insights into missing tests through analysis of logs, tracing, and OpenAPI files to understand what’s going on behind the scenes. Mapping assist leverages natural language processing and machine learning to automate mapping of source to target data structures.

To learn more about how AI-powered automation can help you build together, check out video replays from IBM’s AIOps & Integration conference along with our new IBM Cloud Pak for Watson AIOps hub on IBM Developer.

Mono2Micro

Also featured in the news from Think 2021 is Mono2Micro, a new capability added into WebSphere Hybrid Edition to enable enterprises to optimize and modernize their applications for hybrid cloud. Mono2Micro is another fantastic tool that helps developers build together in the era of hybrid cloud.

IBM Mono2Micro uses AI developed by IBM Research to analyze large enterprise applications and provide recommendations on how to best adapt them for the move to cloud. Check out this learning path to learn more about moving to microservices to enable greater collaboration across your team, with consistency across reusable components and functions.

CodeNet

Our colleagues in IBM Research also announced the release of CodeNet: a very large open source dataset and set of technologies engineered to drive research breakthroughs for AI to understand code. This is an exciting step in the next frontier of AI, that is particularly relevant to developers: making it easier to understand, develop, and deploy code as we build together. Project CodeNet consists of approximately 14M code samples, and roughly 500M lines of code in 55+ different programming languages. You can read more about CodeNet from IBM’s Ruchir Puri here and check out Project CodeNet on GitHub.

IBM Cloud Pak for Data with AutoSQL

Another milestone for developers in AI comes with the next generation of IBM Cloud Pak for Data, which will help our customers operationalize AI faster while removing complexity. This is next generation infrastructure and new set of capabilities are key to how we help you use data across the hybrid cloud landscape, and build together. Learn more about it here.

Next steps

My biggest takeaways from Think 2021 are that in the era of hybrid cloud, investing in our skillsets and building together collaboratively are fundamental to our work. My role at IBM is to ensure we’re equipping you with the tools and capabilities to help you meet the increasing demands you face each day.

In addition to the resources I’ve mentioned here, I encourage you to visit IBM Developer to explore all the code, content, and community resources we offer. And if you’re interested in learning more about building together, check out IBM’s Hybrid Cloud Build team, which supports the migration and modernization of ecosystem partner products, services, and other offerings across open hybrid cloud environments.