Organizations already on their way to the cloud may understand the challenges well. Others will surely face them soon. Gartner recently reported that spend on public cloud services is forecasted to grow 18% in 2021 to over $300 billion. It seems like a lot of companies are leveraging cloud computing as a key ingredient to their digital transformation.
Here are nine common challenges along the way to cloud transformation that can derail or stall your efforts.
1. Lift and shifting servers but not shifting mindsets
When we look at organizations, there are generally three different categories for assessing their maturity in terms of how they are approaching cloud adoption: Tactical > Strategic > Transformational
While eliminating the anchor of your data center is a major priority, we see that companies who are myopically focused on eliminating capital expenditures tend to fall into the “tactical category.”
I spent a lot of time in data centers in my career, and they are absolute marvels of modern infrastructure with miles of cables, millions of gallons of water, and physical security. But realistically, I haven’t met a single customer who cared about our data centers (or for that matter, which tools we used to build our CI/CD pipeline).
What customers do care about is the value they’re getting from your product or service. And that is really the strategic and transformational approach to cloud computing: how can we safely deliver more innovative products to our customers with speed and scale?
So yes, it’s critical to get out of the “undifferentiated heavy lifting” and high capital costs associated with data centers — lift and shift migrate if you must — but it’s far more critical to shift the mindset of organizations to how to leverage cloud computing to generate business value.
2. Cloud Center of Excellence: Not allowing it to evolve
Cloud migrations get stuck or stall out for many reasons. One of the biggest lessons learned as a leader in Capital One’s cloud center of excellence is the importance of evolving how the team operates as the organization matures.
When first starting out, it’s understandable that the CCoE is truly the “experts” within the organization as you’re trying to define the guidelines for operating in the cloud. There’s a lot to unpack in the early days of cloud adoption in terms of how services can be rolled out at scale across an enterprise.
Once the initial boundaries are established and you begin to focus on scale, the cloud center of excellence should really shift toward a cloud center of enablement. The goal is to drive the right skills and knowledge into the hands of federated teams, and then curate best practices when teams deviate from what you originally thought.
Eventually, the CCoE becomes a cloud center of operations focused on the common services across the teams like compliance and controls — and the goal is to remove barriers from dev teams versus introducing friction to flow.
3. Adopting a multi cloud strategy for the wrong reasons
As a purist, my preferred definition of multi-cloud is AWS US-East region and AWS US-West region. I say that because too many organizations are using multi-cloud for the wrong reasons — like the hope of avoiding vendor lock-in.
The rationale to go multi-cloud should be rooted in the customer. How can we get them the most value with our products and services as quickly as possible?
But with the way some companies are approaching this, they’re basically saying to their customer, “Here’s a really crappy app . . . but it runs on three different clouds so we can port it to any cloud at any time.” (Again, your customer doesn’t care.)
Ideally, you get good at one cloud and understand how to operate in the new world. Then, you can make informed decisions based on the alignment of a cloud provider’s strengths and the form and function of the application. It just needs to be very intentional, because keeping up with the skills and changes of a single cloud provider is hard enough.
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4. Letting cool tools pull focus from essential tools
There are a lot of cool services being introduced by the cloud providers at a steady clip these days. This massive amount of innovation is a ton of fun for technologists.
For example, one service that I love is AWS Ground Station. It allows you to control satellite communications, process data, and scale your operations without having to worry about building or managing your own ground station infrastructure. My first job was working on systems that ingested satellite data, so I continue to geek out on the industry a bit.
So my first inclination for AWS Ground Station would be to search for a problem to apply this solution — because I want to build something cool! For example, my hypothesis is that there’s a correlation between certain weather patterns and an interest in learning cloud computing. So I’m going to use AWS Ground Station to ingest that satellite data and integrate it with our Salesforce. Why? I’m guaranteed a talk at next year’s AWS re:invent conference!
5 and 6: Neglecting cloud security
Security can be really hard — especially with some of the ambiguity around the shared responsibility model. Where it gets especially tricky is the space between the operating system and the actual application. There’s a lot to learn when it comes to the correct configuration of services that includes NACLS, Security Groups, IAM Policies, and bucket policies.
There are two critical elements to this.
- Reinforcing that security is everyone’s responsibility — and not outsourced to a central team that’ll magically make it happen. There’s a need for awareness in terms of understanding not only the service but how to secure the service in terms of encryption of access.
- Automation of security is key. The concept of “continuous compliance” and “compliance as code” are a couple of emerging trends that I’m happy to see being discussed. While at Capital One, we actually open-sourced a policy rules engine called Cloud Custodian that helped to drive a lot of this automation. But ideally, it should be a standard feature on all cloud providers. Until then, security continues to be a major area of focus for cloud adoption.
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7. Developers that aren’t mindful of cost
I think this is actually a good problem to have if you can get developers to think about their instances as ephemeral. Cloud computing is really utility compute — very similar to the utility grid for distributing electricity. Just plug into an outlet, and pay as you go. And when you’re not using it, just turn it off.
Of course, I’d have to yell at my kids all the time to turn off their lights. Why? Because they weren’t paying for the bill. Of course, now when they’re paying rent and their own utility bills, guess who all of the sudden cares about turning off their lights?
With cloud, you just plug into an API to access compute service and pay as you go. But it’s really the same problem in many organizations: developers don’t see the bill, so they aren’t aware of the impact to the bottom line when only 2% of CPU is being used across thousands of instances.
Again, automation is a wonderful weapon in the cloud — and this is another way we used policy rules engines in Cloud Custodian at Capital One to automatically shut down instances based upon how long they’ve been idle.
8. Putting cost above all else
I was so focused on the wasted cost of idle instances early in our adoption. I spent a lot of time working on policies to automatically shutdown instances in dev environments across all the divisions.
I found out that a lot of developers were coming back into work on Monday and didn’t understand some of the basics of shutting down instances, and were creating help desk tickets with our data center environment support saying that their servers where gone!
While I thought my efforts were a public service to move us forward, I got called into a senior executive office who wasn’t too happy with the friction that I was creating with his development teams. He asked me if I lived near other houses and could see the neighbors. He asked if the neighbors were gone for vacation and I noticed they left their lights on, would I break into their house and turn them off. I said, “No…” And then he said, “Well, then get out of my house!”
That was a really important lesson for me, and it taught me two things.
- First, the cloud allows for the blast radius to be limited and establish clear boundaries for divisions for ownership.
- Second, cost optimization isn’t everything. Imagine if the compliance and regulatory agency came to you and said “Congrats on your awesome cost optimization! We’re shutting you down because you’re not compliant — but nice work.” That’s not a good look.
Focus on moving things to the cloud in a well architected manner first — and then you can worry about the cost optimization as a fast follower.
9. Not investing in your existing talent
Back in 2011, Marc Andreessen famously wrote his article about how software is eating the world. He talked about how industries like oil and gas, financial services, retail, and healthcare were all levering software to disrupt the status quo. He warned that incumbent software companies would be increasingly threatened with irrelevance by new software offerings. (For context, Amazon stock was about $225 in 2011.)
The biggest challenge in 2011? He said too many people lack the education and skills required to participate in the software revolution, and that many workers and companies will be stranded on the wrong side of the disruption. “There’s no way through this problem other than education, and we have a long way to go.”
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Now it’s 10 years later, and many companies have focused their efforts on digital transformation programs to capture their share of revenue and market share from innovating and optimizing.
So what are the big challenges in 2021? Gartner just reported that insufficient cloud IaaS skills will delay half of enterprise IT organizations’ migration to the cloud by two years or more.
You already have the talent to succeed. The focus should be on how to unleash that talent on cloud computing to drive business value for your customers.
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