Cloudops and cloudops tools (such as AIops) are important, but you can have too much of a good thing Credit: rclassenlayouts / Aleksei Derin / Getty Images Cloud operations, or cloudops, is becoming the problem to solve as enterprises operationalize their cloud and multicloud deployments. The ideal pattern of management involves a pragmatic approach to operations by leveraging tools to automate predetermined procedures and runbooks. Right now, many overwhelmed managers toss cloudops tools at the problems and hope for the best. The issue is one of balance. To put cloudops solutions and tools to their best uses, you need to define why and what before you determine how. It’s not that the tools are unimportant; rather, the tools should meet specific requirements, such as performance, security, cost management, governance, automation, and self-healing. The operational aspects of cloud computing are the highest-priority concepts in my mind. Almost all other components of cloud computing have dependencies into cloudops. For example, security breaches can be spotted by process saturation monitoring from an AIops tool. I’ve defended against breach attempts in the past. The first indications came from cloudops tools, not from security systems. The focus needs to be on the optimal suite of cloudops tools that will best meet the optimal requirements. I’ve been calling this a “minimal viable cloudops toolset,” or MVCOT. The ideal MVCOT is a streamlined collection of tools that are optimized for the cloud and noncloud systems under management. How do you find this MVCOT nirvana? I would suggest the following: Define the current, short-term future, and long-term future state of the systems that will be under management. This seems like a no-brainer, but traditional on-premises systems are often left out of the mix and lack representation in the growth of system capacity. This will give you 65 percent of what you need to pick a MVCOT. Define the runbooks for each system. These will explain how each system needs to be managed to provide optimal service levels and minimize outages. If you think this is a lot of work, it is. You need to think about business continuity and disaster recovery issues, maintenance, scaling, security processes, etc. Now it’s time to select the right tools to make up your MVCOT. As your knowledge and experience evolves, you’ll have to replace or update tools on your initial optimal tools list. Although cloud architects and cloudops engineers are getting more informed about the use of cloudops tools, the temptation to never see a cloudops tool you didn’t like is still enticing. I urge you to put some additional thought into your purchase strategy for cloudops tools. Bonus: The rework you do will be minimal. See what I did there? Related content analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing analysis All the brilliance of AI on minimalist platforms Buy all the processing and storage you can or go with a minimum viable platform? AI developers and designers are dividing into two camps. By David Linthicum Jul 09, 2024 5 mins Generative AI Cloud Architecture Artificial Intelligence analysis The next 10 years for cloud computing Despite AI's explosive growth, the industry still needs to face facts that customers are unhappy about costs and vendor lock-in. By David Linthicum Jul 05, 2024 5 mins Amazon Web Services Google Cloud Platform Microsoft Azure analysis Serverless cloud technology fades away Serverless was a big deal for a hot minute, but now it seems old-fashioned, even though its basic elements, agility and scalability, are still relevant. By David Linthicum Jul 02, 2024 4 mins Serverless Computing Cloud Computing Software Development Resources Videos