AWS launched a colossal 3,300 new features and services across the cloud hyperscaler in 2022 -- an average of nine every single day; just the latest indication of how hard it can be to keep up with the pace of new tools from just one software and services provider, in what is already a rapidly evolving broader technology environment.
AWS customers meanwhile are highly focussed on trimming cloud costs amid a tough economic climate.
That's according to Amazon CEO Andy Jassy who told shareholders in his annual letter that “AWS sales and support teams are spending much of their time helping customers optimize their AWS spend” in the wake of “one of the harder macroeconomic years in recent memory” – one that also saw Amazon lay off 27,000 corporate staff.
The retail and cloud computing juggernaut had a brutal 2022, slumping to an annual net loss of $2.7 billion from profits of $33.4 billion in 2021 and seeing operating income more than halve to $12.2 billion from $24.9 billion.
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As well as sweeping layoffs, that has seen the company make some substantial operational changes, closing certain businesses and demanding the return to offices for staff three-days-per-week from May 2023. (“We’ve become convinced that collaborating and inventing is easier and more effective when we’re working together and learning from one another in person… [many breakthrough moments came from] people staying behind after a meeting and working through ideas on a whiteboard, or continuing the conversation on the walk back from a meeting, or just popping by a teammate’s office later that day with another thought," Jassy said.)
Jassy said that despite the “short-term headwinds [that] soften our growth rate, we like a lot of the fundamentals that we’re seeing in AWS… customers tell us that they’re not cost-cutting as much as cost-optimizing so they can take their resources and apply them to emerging and inventive new customer experiences they’re planning.”
Inferring the future of AWS...
Turning to Amazon’s own outlook for AWS an example of innovation that Jassy dwelled on most was telling: chip development. Flagging AWS’s Arm-based Graviton chip performance he added that “machine learning adoption has continued to accelerate, customers have yearned for lower-cost GPUs (the chips most commonly used for machine learning). AWS started investing years ago in these specialized chips for machine learning training and inference [answers delivered by ML models]. We delivered our first training chip in 2022 (“Trainium”); and for the most common machine learning models, Trainium-based instances are up to 140% faster than GPU-based instances at up to 70% lower cost. Most companies are still in the training stage, but as they develop models that graduate to large-scale production, they’ll find that most of the cost is in inference because models are trained periodically whereas inferences are happening all the time as their associated application is being exercised...2
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Jassy added: “We launched our first inference chips (“Inferentia”) in 2019, and they have saved companies like Amazon over a hundred million dollars in capital expense already. Our Inferentia2 chip, which just launched, offers up to four times higher throughput and ten times lower latency than our first Inferentia processor.
"With the enormous upcoming growth in machine learning, customers will be able to get a lot more done with AWS’s training and inference chips at a significantly lower cost. We’re not close to being done innovating here, and this long-term investment should prove fruitful for both customers and AWS.
"AWS is still in the early stages of its evolution, and has a chance for unusual growth in the next decade…
Change is always around the corner. Sometimes, you proactively invite it in, and sometimes it just comes a-knocking. But, when you see it’s coming, you have to embrace it... I’m optimistic about our future prospects because I like the way our team is responding to the changes we see in front of us.
