Is Cloud Repatriation a Big Lie Server Vendors Are Shilling?
Is cloud repatriation just hype? Find out.
Cloud repatriation spotlights the need to avoid letting hype determine your analytics strategy. Paige Roberts, Open Source relations manager at Vertica, gets to the bottom of what reverse cloud migration is all about and the purpose it may serve.
For the past decade or so, businesses have been migrating to the cloud in droves. No surprises there, as cloud technology has been nothing short of revolutionary, bringing forth unimaginable opportunities even for the smallest of businesses. That said, not every cloud migration results in an outcome that is expected. Yes, it can be easy to get everything up and running; it can be easy to support and maintain; resources can be spun up on demand. But as businesses start to scale, some realize the cloud model isn’t working for them.
Three Main Reasons for Cloud Repatriation
Cloud repatriation or “reverse cloud migration” is a process of pulling back an organization’s applications, data, and workloads from a public cloud and putting them back onto a local infrastructure, such as an on-site or co-located data center or a private cloud. Studies show that 54% of organizations in 2022 repatriated some or all of their workloads or moved data away from the public cloud. Here are three main reasons why:
1. Cost, transparency and predictability
The idea of paying just a fraction of the cost upfront and moving away from a cap-ex model to an op-ex one is really hard to resist. This is why most organizations migrated to the cloud in the first place. Unfortunately, organizations are now realizing that the cloud isn’t as financially appealing as it once appeared to be. Cloud pricing is based on a pay-as-you-go model — the higher your utilization, the greater your cloud bills. What’s more, studies show over 90% of enterprises overshoot their cloud budgets because they either underutilize or overprovision resources or lack the ability to properly manage cloud environments.
Cloud providers also have non-standard pricing, which means that every cloud provider will have different cost definitions (usage limits, tiers, etc.) and charges will vary greatly based on services used (security and management of tools, database writes, etc.). There are also a number of hidden charges involved. For example, moving your data out of the cloud provider can attract egress fees.
Cloud providers can lock customers in long contracts or tweak their pricing suddenly, which can cause cloud bills to skyrocket. In contrast, on-premises or co-location offers simpler and more predictable pricing. You buy a server that costs X, and you pay your co-location fee Y per month and that pretty much sums it up. The hype machine makes two big statements about cloud computing, claiming it will save costs and require far less expensive skillsets to manage. The evidence counters both those statements.
2. Cloud performance
Although the cloud provides theoretically limitless scalability, it still loses some speed due to internet connectivity and virtualization overhead. In most cases, cloud performance issues like noisy neighbors in multi-tenant software don’t matter because it’s plenty fast enough to serve the use case. However, for certain use cases or for higher scales of data, workloads, or concurrency requirements, faster performance is essential.
Some real-time analytics workloads, like machine learning-based AI, can be sensitive to latency. Analytics applications can leverage caching and other network optimization methods to reduce latency. However, one of the easiest and most pragmatic fixes is to shorten the communication path. This means that unless the data was born on the cloud, bring the analytics back in-house.
3. Security, control and regulatory concerns
As long as security is set up correctly and best practices are followed, there is no reason why a public cloud would be any less secure than an on-premises environment. That said, one can never rule out the possibility of cloud misconfigurations, which are the number one cause of cloud data breaches globally. Even leading cloud providers like Amazon and Microsoft have been victims of leaks and breaches due to cloud misconfiguration issues.
Regulations regarding the geographical location or the sensitivity of data can be a major concern, requiring data processing outside a public cloud or requiring data to remain geographically contained. Businesses may find it easier to relocate that data back in-house, even in less regulated regions, to avoid potential problems from future regulatory changes. Transferring hundreds of terabytes, petabytes, or even exabytes of data from one location to another can be very expensive, and on-premises is the one location no regulation is likely to rule out.
See More: Why Colocation Is the Best Bet for Reliable and Cost-Effective Data Storage
Avoid Letting Software Limitations Determine Your Analytics Future
A strong analytics foundation is one that is built on business needs and not around hype or the limitations of the software. If you’re investing in a future-ready analytics strategy or foundation, below are three things to keep in mind:
- Deployment flexibility: Avoid analytics software that mandates that all data must be loaded in a specific format, theirs, before analysis. Avoid software that only works on one vendor’s cloud or the equivalent on-prem and that only supports one kind of hardware. Instead, opt for “infrastructure agnostic” – able to work on-premises, on one cloud, on multiple clouds, on a private cloud, in a containerized environment, on ARM processors or Intel processors, on commodity hardware or specialized flash hardware. Even cloud-native is good, as long as it means the software can be containerized, not that it doesn’t work anywhere but on the cloud. Give your future self some peace of mind by not limiting your options.
- Cross-technology compatibility: Choose an interoperable analytics foundation with various technologies that offers a wide range of ecosystem connectivity. This can make a big difference when large amounts of data need to be migrated or repatriated, but it also gives you a lot more freedom to choose other technologies for best of breed in every part of your architecture. Watch for analytics platforms to develop a single-pane-of-glass view of data and consistency in analytics, reporting, and management capabilities, regardless of whether databases are located in different clouds or in different regions.
- Transparent pricing and fungible licensing: Lack of cloud provider pricing transparency is one of the major reasons why businesses overspend their cloud budgets. Look for options that provide transparency and predictability in pricing. Take into account the possibility that your organization might opt for a different deployment strategy in the future. In such a scenario, it’s a big advantage to have fungible licensing, meaning the license you buy isn’t limited to one deployment location; you want the flexibility to deploy workloads anywhere.
Whether to stay in the cloud or repatriate is ultimately a business decision based on what works for the organization. Whether it’s cost, vendor lock-in, new technology, lack of skills, performance, security, or regulations, sometimes it just makes sense to move workloads elsewhere. That’s why it’s wise to accommodate asset mobility in your overall analytics strategy.
Are you considering cloud repatriation? Share your reasoning behind it on Facebook, Twitter, and LinkedIn. We’d love to hear from you!
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