For most enterprises, multi-cloud has become the new normal.
RightScale’s 2018 State of the Cloud Report found that 81 percent of enterprises are using multiple public or private clouds. In fact, on average, they are using 4.8 different clouds.
In some ways, this greater reliance on the cloud — particularly the public cloud — has made life easier for IT professionals. After all, it reduces the need to research, select, deploy, and maintain their own IT infrastructure.
But in other ways, multi-cloud has introduced new challenges for enterprise IT. As complexity increases — as it inevitably does with multi-cloud — monitoring what is happening in all the different cloud environments becomes much more difficult.
Here are five of the top challenges in multi-cloud monitoring:
1. Constant change
Many enterprises decide to pursue multi-cloud strategies because of the flexibility and scalability this approach promises. However, the biggest advantage of the cloud also turns out to be one of its biggest disadvantages.
In an email interview, Dave Anderson, digital performance expert at management and monitoring vendor Dynatrace explained that biggest challenge in multi-cloud is “keeping up with what is running, where and how on earth are we going to instrument this when the environment keeps changing every second.”
2. Siloed cloud vendor tools
To keep tabs on what is happening in their cloud environments, many organizations rely on the free or low-cost tools provided by the vendors themselves. In fact, in the Interop ITX 2018 State of the Cloud report, 37 percent of respondents said that they rely on the monitoring services provided by their public cloud vendors.
Unfortunately, these tools have a big drawback: they can only monitor and manage workloads running on that one vendor’s infrastructure. If IT is monitoring workloads for multiple vendors — and they are — they have to use multiple tools to get the job done.
That also doesn’t include the workloads running in private clouds or traditional infrastructure in their own data centers. Anderson told the story of a customer who said, “We have a hybrid cloud monster made up multiple clouds, and yet we still have a mainframe." Monitoring tools provided by public cloud vendors can't provide a consolidated view of all those different environments.
3. No cloud support in legacy tools
Most organizations already have monitoring tools that they use for their in-house data centers. In a perfect world, they might want to extend their use of these tools into the cloud.
However, most legacy tools weren’t designed for cloud monitoring. While some legacy vendors have updated their monitoring tools to provide some cloud support, most fall short of providing the level of detail and comprehensive capabilities that many enterprises are seeking.
4. Challenges in selecting multiplatform monitoring tools
In response to all these challenges, enterprises frequently start shopping for a hybrid or multi-cloud monitoring and management tool. But these tools can be expensive. In addition, they offer such different and wide-ranging feature sets that comparisons can be difficult. For example, Gartner’s Evaluation Criteria for Cloud Management Platforms and Tools identifies 215 different criteria that IT decision makers need to consider when selecting multi-cloud monitoring tools. That level of research and evaluation takes a significant level of effort.
5. Lack of skills
When enterprises do deploy a new multiplatform monitoring tool, they often have to retrain staff. In addition, the tight labor market and the rapidly changing technology make it hard for enterprises to find staff with the multi-cloud skills they need. In the Forrester Wave report on Hybrid Cloud Management, Lauren E. Nelson noted, ”Platforms and best practices evolve rapidly. Even [infrastructure and operations] professionals who actively try to keep their knowledge up to date find that their knowledge is lagging, which has financial implications.”
However, while the lack of skills and other challenges may pose obstacles to enterprises with multi-cloud strategies, those challenges are not insurmountable. Anderson recommended that organizations try to consolidate their monitoring tools by using best-of-breed tools the provide real-time visibility across their entire environment. In addition, he said they should rely on automation and “utilize AI. Why spend time manually searching for performance issues, when the answers could be served up to you? These environments now are far too complex, hyper dynamic, and impossible for DevOps teams to understand fully.”