Ev Kontsevoy is sendan identity-based infrastructure access management provider.
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Over the past five years, we have experienced a period of tremendous growth and optimism in the technology industry. Record funding rounds, sky-high valuations and strong private sector and government spending have created a period in which founders can easily gain traction and startups have ample cash to invest in each other’s services . Starting a business is never easy, but this economic environment does simplify the early stages for many entrepreneurs.
We are now in a different reality. Facing rising inflation, jittery investors and struggling supply chains, businesses can no longer easily obtain the capital they need to start and scale. The economic downturn has caused people to become fearful and conservative, which is reflected in lower stock prices, fewer funding rounds and less frequent IPOs.
Opportunities for growth and success now appear to be few and far between, but history shows otherwise.Just watch Hollywood blockbusters big short–Many investors who made bold, shrewd bets during the Great Recession reaped huge profits when the economy collapsed. The same goes for startups. Those companies with great products and bold visions can be hugely successful, even when most other companies struggle to gain traction.
For companies with transformative products, tough economic times may even be the perfect time to expand market share or create new markets entirely. Most customers are now purely value-focused, choosing to invest only in those solutions that provide them with a tangible financial benefit. A solution that launched (Slack) and thrived (AWS) during the Great Recession immediately provided new benefits and capabilities to a large customer base.
There will be winners and losers in the current economic downturn, and being able to predict the winners will be extremely valuable. To understand which technologies will lead us out of the downturn, we should look at the choices being made now by hyperscalers — large companies operating at unprecedented scale with seemingly limitless resources.
Hyperscale History
People often compare the tech industry to the fashion industry. Engineers are human too, and we’re susceptible to influence—even fashion. New JavaScript frameworks and configuration management systems replace their unpopular predecessors every year.
However, there are some long-term trends that are solid and stable, and these trends are often defined by a few large companies that effectively make choices for everyone else. Hyperscalers—companies like Google, Amazon, Microsoft, Facebook, and Apple—employ so many engineers, operate such massive server farms, and process so much data that they operate at a scale no other company can understand. Hyperscalers can’t buy off-the-shelf solutions to their problems because no one builds off-the-shelf solutions for their scale. Instead, these industry giants create new solutions to their challenges that inevitably become the next must-have technology for everyone else. As we say in Silicon Valley: “The future is already here, it’s just not evenly distributed.”
In the early 2000s, Google realized that its search engine would never have a viable business model if it was running on traditional high-end servers. While these machines were fast and reliable, they were also expensive — with exotic processors and running proprietary UNIX or Windows operating systems. Google decided to switch to slower, unnamed x86 machines managed by a free, open-source operating system called Linux. This decision by hyperscalers showed that the reliability of expensive machines doesn’t matter at scale, and the resulting invention was cloud computing.
Winning cloud infrastructure products follow a model of taking the sophisticated, battle-tested technologies of hyperscalers and making them available to everyone else. AWS is the productized version of Google’s architecture. Docker democratized containers, and Kubernetes is just a simplified version of Google’s Borg. Hadoop came from Yahoo, Cassandra came from Facebook, and Apache Kafka came from LinkedIn.
The next big thing in tech isn’t just on the horizon; they’re already here. After the explosion of innovation in cloud computing over the past decade, it is only logical that the next technology for hyperscale verification would be security.
safe turning point
Businesses have taken full advantage of the utility and scale offered by cloud computing, but security has not kept pace. With enterprises now overseeing more sensitive data than ever before, many organizations still rely on a security posture designed for the data center and the world of defined perimeters, not the Wild West of the public cloud. Traditional access protocols like usernames and passwords—essentially just secrets that can be lost, shared, or stolen—fundamentally do not scale to the levels required for very large-scale applications.
The scale is bigger and the stakes higher than ever. Companies such as Google, Facebook, and Apple oversee vast amounts of sensitive information. When this information is leaked or stolen, it can cause huge financial and reputational damage — not to mention opening the door to potential lawsuits or government oversight. Many hyperscale enterprises have come to rely on secret identity-based access using certificates. They have recognized that the concept of boundaries is outdated and they are moving to a zero trust architecture. These companies are already making big decisions that will affect the entire next decade of security and technology. Companies that can quickly adapt to these technological changes will be the big winners in the current downturn.
As with any major industry shift, implementing a new operating system can be mind-boggling. Organizations looking to implement a new confidential solution should start with recent projects and focus on one access at a time; trying to transform an entire organization at once to boil the sea is a recipe for failure. While this will be an ongoing, long-term process for many organizations, I believe today is the best place to start.
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