Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
A significant risk associated with cloud migration is overspending. For years, zombie-like obedience to AWS has resulted in price lock and escalating fees at many organizations – this is a tale for fighting the cloud zombies.
Cloud costs around data egress or application bandwidth are often not transparent and thus highly unpredictable. Complicating this problem is the need to rapidly develop and scale large application ecosystems, leading to snap judgments by project engineers to buy tools. Or, cloud purchasing decisions fall to the CFO, who may not be qualified to understand technical nuances. Without cloud spending forethought, it’s easy to enter unsavory pricing commitments.
However, all of this is changing. As cloud service providers (CSPs) mature their offerings, competitors have risen to take on AWS, unlocking more consumer choice throughout the cloud landscape. In a multi-cloud world, cloud economists are leveraging lift and shift capabilities to optimize performances. Ironically, companies are also seeing cost benefits in retaining some on-premises servers.
I recently spoke with Scott Leatherman, chief transformation officer at Virtana, to get his take on preventing cloud cost escalation and how IT should streamline multi-cloud environments to stem the cloud budget.
Zombies in the Cloud
When the cloud arrived, it promised high performance at a low cost. Companies were happy to offload on-premises servers for the ease of cloud arrangements. For years, there was a “zombie-like loyalty” to cloud platforms, said Leatherman.
Not much was thought about costs rising in parallel with the astronomical growth of the web, mobile and IoT. Executives penned long-term pricing contracts without a second thought. Then eventually, reality hit. And it came with a hefty price tag.
Spooky Cloud Expenses
As cloud-enabled businesses took off, they encountered many hidden fees. To name a few:
- Egress: Fees for moving data in and out of the cloud.
- Application: Fees for moving applications to new instances.
- Workloads: Mounting costs for increasing bandwidth and workloads.
These and other add-ons could quickly raise a cloud bill from $200 to $200,0000 a month. Complicating this was the fact that many large organizations purchased multi-year cloud subscriptions locked at a specific price.
Counterintuitively, such cost-savings guarantees are “completely backward,” Leatherman said. As computing power increases exponentially per Moore’s Law, servers become cheaper to maintain.
“You’ve literally committed yourself to something that is depreciating in cost,” he said. Yet, those savings don’t trickle down to consumers and SLAs have remained pretty flat. “What’s the most frustrating thing for me is that the best way to run this business is to lock people in.”
The Zombies Become Aware
In the wake of COVID-spurred digital transformation, cloud zombies are waking up to slash the budget, finding cost-effectiveness in multi-cloud strategies. Some companies are even reaffirming ties with on-premises servers.
If performance isn’t worth the cost, it defeats the benefits of moving to the cloud entirely. So, how can we smartly optimize our environments for quality performance with leaner financial margins? Leatherman shared some steps to become cloud-smart:
1. Baseline Your Footprint
The first step toward reducing cloud costs is maintaining a baseline of all cloud dependencies and private data centers. This should cover a deep cost and performance analysis.
“You need a baseline in your data center—what can I move? what should I move?” said Leatherman. Unless you have a baseline of what your data center is doing (both private and public), you can never understand what resources should move to the cloud. Powerful apps for monitoring the public cloud could help audit architecture.
2. Optimize, Optimize, Optimize
Only after mapping topologies can you can begin to optimize performance. Since usage differs depending on the season, cloud optimization should respond to yearlong application usage trends. For example, ERP software may pull significantly more requests at the end of the quarter and e-commerce spikes during the holidays.
Organizations should ensure the elastic cloud truly scales to application needs, but only when needed. Ensure systems of orchestration and routing function properly, and diligently search for hidden fees. “The cost that sneaks up on you in the elastic cloud always comes up,” said Leatherman.
Heavy computation processes, such as machine learning over big data, will require enormous server consumption. For resource-intensive scenarios, Leatherman recommended keeping code lean. Whereas CPU relies on the laws of physics, “application developers are only limited by creativity,” he said.
Application developers should whenever possible optimize code to avoid redundancies. Doing so yields a positive environmental impact, too—eliminating operational inefficiencies can decrease cloud server usage, which reduces carbon footprint.
3. Lift and Shift
GCP, Azure, Oracle and other CSPs mature, the zombie-like loyalty to AWS is fading. “Now that there is parity across cloud vendors, things are changing,” he noted. “The flexibility in the marketplace is really dynamic.”
In a multi-cloud world, organizations can leverage a hybrid cloud and “lift and shift” toward the best cost optimizations for their specific needs. This is where maintaining a strong baseline will help continually test cost efficiencies among cloud competitors.
4. Refine Your Tool Procurement Process
Another solution involves scrutinizing your cloud procurement process and the personnel involved. As mentioned above, new cloud tooling purchasing may occur at the DevOps level or large contracts may be escalated to the CFO office.
Unfortunately, neither side is in an ideal situation to make smart financial decisions—one faces an urgency to deliver and the other can’t see the trees from the forest (and especially not the termites eating the valuable wood). Many believe a new role is required—The Other CFO—to help optimize the cloud stack.
5. Retain and Optimize Private Data Centers
By now, most enterprises are accustomed to having both a data center and a cloud center team. Leatherman argued that ultimately these two teams must work together to avoid outages and reduce the exponential costs of moving to the cloud.
From a security perspective, there are still significant advantages to maintaining on-premises private clouds and data centers. By leveraging private assets, you aid data protection efforts and have increased control. “Datacenters have value,” he said. “Unless you started there, no one will be 100% cloud.”
Although cloud migration seems inevitable, through software automation and Moore’s law there is value in on-premises. As a result, Leatherman predicts a rise in private cloud data center optimization and management services by third parties.
6. AI for Cloud Cost Awareness: DevFinOps
Finally, AI soon may be available to automatically scan for cloud cost impacts before applications are even deployed.
Most DevOps teams use container security scanning or automated compliance validation as part of their DevSecOps process. Leatherman suggests future DevOps tooling will similarly evolve to display automated notices that estimate cloud costs for your actions in real-time.
For example, as engineers are pushing code, a popup could display server utilizations and a cost impact breakdown. Or, inline code validation suggestions could find redundancy to decrease waste. Perhaps we’ll need a new abbreviation for this Developer + Finance + Operation focus—DevFinOps, anyone?
Such an AI would likely not negate the need for a cloud economist to help manage multi-cloud complexity. “We’ll still need them,” said Leatherman.
Surprises in a Multi-Cloud World
COVID–19 is accelerating deployments tagged for much shorter timeframes, forcing many more instances to public clouds. Businesses need to get performance up and meet their SLAs. To reduce expenditures, they must quickly lift and shift to the most performant and cost-efficient environments.
The gravity is apparent, yet hasty moves now could be disastrous for security and data privacy in the future. Besides rising cloud costs, there are other risks associated with the cloud that increase exponentially with multi-cloud environments. “It’s not just the financial spend, but the security and risk that goes along with it,” Leatherman said. “It becomes really scary how many people have access.”
Not only must cloud spending decisions shift left, but security must arise earlier in the development cycle as well. Compliance with regulations such as GDPR or HIPPA should also influence how teams manage data between clouds.
The Cloud is Relatively New
An IBM-endorsed study found enterprises are only 20% of the way through their cloud journey. Many enterprises are still just at the beginning of their cloud transformations, and 90% plan to expand their cloud footprint in the next year.
The cloud journey is quite long, and many have quite a way to go. Knowing this, cloud economics will only rise in importance. As I recently covered, cloud expertise is now superior to a university degree.
Current forces, like the COVID–19 crisis, will no doubt continue to “drive people to the cloud,” said Leatherman. While responding to the imperative to deliver more and higher speeds, it’s essential to be smart, leverage existing assets, and optimize cloud usage at every level possible. “It shouldn’t just be cloud-first,” he said. “It should be cloud-smart.”
