Cloud modernisation continues to build rapid momentum, but the challenges are consistently stacking up.
A recent report by 451 Research reveals that 68% of organisations using Amazon Web Services (AWS) plan to become more reliant on cloud managed or professional services over the next 12 months alone.
The report, which surveyed 950 North American organisations using AWS, reveals that:
- 59% of respondents report using AWS to increase the speed and agility of launching applications;
- 48% of organisations see AWS’ broad range of cloud services a key driver for adoption; and
- 41% prefer AWS’s utility pricing model .
However, the talent and cloud knowledge needed to build, scale and optimise AWS environments has become a primary challenge for many organisations to reach their cloud goals.
Challenges In Cloud Performance Optimisation & Cost
And to top it off, 41% of respondents named cloud performance optimisation and cost one of their largest challenges.
As a result, many organisations opt for outside AWS expertise and services, with 79% of those respondents looking to increase their reliance on external AWS help.
Among the challenges:
- 39% cited building cloud-native applications.
- 38% reported struggling with migrations from legacy infrastructure to AWS.
- AI/ML initiatives on AWS, implementing data lakes and other cloud modernisation goals were also major challenges.
With all of these challenges stacking up, you have one of two choices: Deal with the costs, labour and efforts in in finding and teaching the right talent. OR, find external help.
For Now, Use These Tips On Optimising Your Cloud Costs
Senior Cloud Architect and allround hyperscaler expert, Brendon De Meyer, has the following to say about optimising your cloud costs:
“Don’t Treat The Cloud As A Hardware Refresh”
The cloud sits on a very intricate and expansive infrastructure and design.
“This means that it uses:
- Far better hardware than most businesses are able to afford;
- A highly superior network and infrastructure;
- Orchestration/engineering expertise that are superior to most organisational capabilities.
For this reason, going from on-premise to cloud is not a like-for-like scenario. You really do not need to make everything the same and replicate your existing setup. So it’s important to know your baselines, monitor your workloads and adjust.”
“Modernise Your Solutions In The Cloud”
“Every hyperscaler has cloud-native solutions for everything you might need. These are full consumption-based services which are often fully managed by the hyperscaler themselves. This means that internal teams manage only your code and the customer/user integration.
By all means, use the cloud to spare yourself a capex-intensive hardware refresh and reduce your risk with ageing hardware, but the very next step should be modernising your applications and technology stack.”
“Use Hyperscaler-Native Solutions”
There will be a huge push for you to use virtual applications in the cloud.
“The drawback is that, often, these solutions are built on the compute mechanisms offered by a Hyperscaler. So they are VMs, which are often the most expensive way to consume services in the cloud.
Furthermore, the way the bigger hyperscalers are architected means that you don’t have all the access to the hypervisor you might need. This means that you often have to modify the way your VPC works to accommodate these appliances.
I acknowledge that there are very real features offered by hardware vendors that might not exist in the cloud. And in those scenarios, by all means, use them, but if you are looking for a load balancer or a firewall, compare your chosen Hyperscaler solution to your preferred OEM and see if, feature for feature, the Hyperscaler solution meets the brief.
If it does, you will save a bucket on licensing and engineering complexity.”
Looking For External Help?
Then look no further!
We not only have the cloud expertise to modernise (and optimise) your hyperscale environment, we also have exactly what you need to have your AI and ML initiatives take rapid flight.
(We’re talking months, not years).
And if you’re thinking about implementing data lakes, or taking on any other cloud modernisation goals – Our teams have you covered!
Get in touch or check out our blog on more cloud, ML, and data related advice.
