Multi-cloud is a cloud computing strategy that uses two or more different cloud services. This can be a combination of Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), or Infrastructure-as-a-Service (IaaS) solutions running in a public or private cloud environment. Multi-cloud offers a number of benefits including greater reliability and availability, less vendor lock-in, and potentially lower costs.Today, 86% of enterprises use a multi-cloud strategy. Of these organizations, 64% use an internal private cloud, while 54% and 59% use public and private hosted clouds respectively. The key benefits these organizations found by adopting a multi-cloud approach is improved IT infrastructure management, better cost management, and improved security and compliance.
Multi-cloud is often confused with hybrid cloud, and while the two concepts are similar, there are key differences. A hybrid cloud combines public, private, and on-premise infrastructures using a single platform or technology stack. Applications running on-premise can scale to and share data with applications running on public clouds seamlessly. For example, an organization running a high traffic website might host its backend services on-premise and scale up to a public cloud under periods of high demand.The multi-cloud model is similar to the hybrid cloud model, but where a hybrid cloud uses a single technology stack, a multi-cloud uses different technology stacks, platforms, and services. Instead of using multiple clouds for the same task, multi-cloud uses multiple clouds for different tasks. The same organization using a multi-cloud architecture might host its backend services on AWS EC2, its database on Google Cloud SQL, and static content on Azure CDN.
There are several reasons for choosing a multi-cloud architecture.
Organizations have more options than ever for choosing where and how to deploy applications. Public cloud vendors offer many of the same technology and software stacks, but differentiate on their features, toolsets, integrations, and price. This competition gives organizations more freedom to evaluate vendors based on their merits, rather than out of necessity. And with a multi-cloud architecture, organizations can pick and choose the individual services that best suit their needs.
Relying on one vendor to host all of your applications and data can lead to significant problems if you decide to switch vendors or migrate to an unsupported stack later on. While vendor lock-in is still a reality, many vendors are embracing open standards and portability. For example, all major cloud providers support Kubernetes, making it almost trivial to deploy the same containerized applications to AWS, Google Cloud, and Azure.Multi-cloud greatly reduces the risk of vendor lock-in from the start. By hosting only a small number of services with each vendor, the cost and time commitment of changing vendors is much lower than it would be otherwise.
Spreading out your applications across multiple vendors is an effective way of improving availability. Unexpected downtime costs companies an average of $5,600 per minute, and no one provider can guarantee 100% availability. Load balancing your application across multiple vendors lowers the risk of an outage taking down your entire application, while also letting you improve performance.
Despite the average global Internet speed steadily increasing, location still plays an important role in web performance. Deploying applications closer to users can reduce latency and increase throughput, and a multi-cloud approach gives you more freedom to choose vendors with data centers located near your users.A multi-cloud architecture also helps with compliance with location-specific laws, such as data export regulations. Using different vendors gives you greater control over where data is transmitted and stored, preventing unintended leaks. All major cloud vendors provide tools and support for complying with regulations, but using different cloud platforms to host regulated services can greatly reduce the risk of a violation.
Observability in a multi-cloud environment is a challenge. Public, private, and on-premise infrastructures are all somewhat different and often use platform-specific monitoring tools. Services like AWS CloudWatch and Google Stackdriver are necessary for collecting and analyzing telemetry data from other services, but they offer little if any interoperability with outside services.Fortunately, logs are somewhat easier to manage than metrics. Logs generated by cloud services can be captured and stored in the platform's monitoring service, or even forwarded to an outside destination. For example, AWS CloudWatch Logs can automatically collect logs from EC2 instances, S3 buckets, Lambda functions, and other AWS resources. From here, DevOps teams can reroute their logs to another destination such as LogDNA in order to parse, analyze, and monitor logs.While parsing multi-cloud logs can be difficult due to the wide range of formats, LogDNA automatically parses AWS ELB logs, AWS S3 logs, and most common log formats. You can create custom parsing rules for unsupported log types to ensure all of your logs are properly parsed. This lets you index, search, and graph logs from your multi-cloud applications no matter where they're deployed.If you're ready to start logging your multi-cloud applications, sign up for a free account. You can also host LogDNA on your infrastructure of choice. To learn more, contact us or visit logdna.com/self-hosted.