New Ways to Integrate Multi-Cloud Ecosystems
For on-premises IT teams, adapting to the public cloud and using it efficiently has been a challenge. As organizations move from working with a single public cloud provider to a multi-cloud approach, remaining efficient becomes even more complicated.
Traditionally, multi-cloud strategies were deployed because organizations want to keep costs down. Today, multi-cloud is being used because organizations want to be able to take advantage of multiple services, each of which is only available at specific public cloud provider. These Bulk Data Computational Analysis (BDCA) tools include Machine Learning (ML), Artificial Intelligence (AI), Business Intelligence (BI), machine vision, natural language processing, and much more.
The major public clouds are not completely interchangeable. Each public cloud provider has different infrastructure, security considerations.and costing structures. Making workloads portable between these different environments — and doing so efficiently — requires careful planning.
So what should organizations eager to make the multi-cloud leap focus on? Here’s what to take into account when building multi-cloud ecosystems:
Composability and Deployment Tools
The key to all things cloud is composability. Workloads that are composable separate the data from the application and its environment. The application and its environment are defined in code. This means that — so long as the data can be made available–the workload can be instantiated on any cloud that offers access to the right applications.
Composable workloads are most common when working with containers, however, the concept is technology-agnostic.
Also, no technology guarantees composability. Success with composable workloads requires attention to best practices and the use of deployment tools.
Inexperienced administrators or developers may make changes to settings for running workloads in order to solve an immediate problem and forget to integrate this back into the deployment chain. This can lead to the loss of those changes if the workload is recomposed or moved to a different provider.
Minimize the chances of human error by finding deployment tools that your team is comfortable with and creating business processes that ensure the tools are appropriately used.
Predominantly on-premises IT teams are strongly advised to put the effort into making their workloads composable before moving to the public cloud, let alone attempting multi-cloud. Composable workloads are more easily turned off when no longer needed, and far easier to set up to burst as needed. Both can save organizations a lot of money, and prevent initial sticker shock when moving to the cloud.
Identity and Access Management
Identity and Access Management (IAM) is a serious consideration when talking about the public cloud. IAM is the basis of all modern IT security. It determines who gets access to what, where, and for how long.
On-premises, virtually every organization uses Microsoft’s Active Directory. If operating entirely within one cloud, there are typically a few options made available by the public cloud provider. Most are based on LDAP or SAML 2.0 authentication.
When looking to move towards a multi-cloud infrastructure, organizations typically investigate third party IAM solutions specifically designed for multi-cloud deployments. There is nothing that prevents use of Azure Active Directory in a multi-cloud environment, but the more cloud services are added, the more likely it is that an IAM solution which can speak multiple protocols will be required.
An increasingly popular option for multi-cloud deployments is to place persistent storage with a trusted third party solution. This is largely a cost-saving measure.
Rather than repeatedly move workload data from one cloud to another, organizations choose a vendor with resources in a large tier 1 colocation facility. These colocation facilities have low-latency, high speed fibre optic links to all four major public cloud providers. NetApp’s Private Storage for Cloud is a popular example.
Workloads execute within a public cloud, but use the storage provided by the third-party storage provider. Organizations only pay network egress fees for new writes sent to third-party storage. This is significantly less than paying egress fees on the entirety of the storage every time it is moved between clouds.
This sort of solution is critical to efficiently and practicably creating applications that utilize the proprietary BDCA tools from multiple providers to act on the same dataset.
Single Pane of Glass for Multi-Cloud Ecosystems
Realistically making use of multiple cloud providers is about more than the technical solutions.
Organizations need monitoring, best practice analysis, and alerting solutions that cover all the cloud services under management, regardless of the public cloud on which they are located. Organizations need to have best practices that call for regular security assessments and cost rationalization.
Investing in a multi-cloud management solution is thus the last major consideration for any organization that aims to span multiple clouds. The ability to pull reports encompassing all resources under management is critical capability.
Ultimately, multi-cloud deployment requires a shift in thinking about how infrastructure is designed, deployed, analyzed, and rationalized. It can be as big a jump as that first move from on-premises to the public cloud. For organizations making the jump to the cloud today, multi-cloud may be the only cloud they ever know.
Schedule a demo to learn how CloudCheckr helps effectively manage multi-cloud ecosystems, or try a 14-day free trial.
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