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Each December here on eWEEK, we ask IT professionals to look ahead and offer some educated “Predictions, Sure Things and Wild Guesses” as to what we can expect from the coming year. There are always a lot of interesting answers, whether or not they turn out to be on- or off-target.
So here it is in mid-July 2020, and we’re deep into a very strange and unusual year, with the convergence of a 100-year global pandemic, an explosion of issues in race relations and law enforcement and clear disagreements about leadership at the top levels of government. No one could have foreseen what challenges 2020 was going to hand us, just as no one knows what 2021 will bring us, either.
Still, as in all of analytics, there are bread crumbs on the path to the future, dropped by data and history from the past. If read and followed well, they could portend key trends that are laying in wait for us right now.
Along these lines, eWEEK invites its readers to look ahead, use the data and industry information you have at your disposal, and let our community know about important things you expect to see in the future in your corner of IT. And you don’t have to wait until December to do it! You have the ideas? Send ‘em to us whenever you’re ready to do so.
Starting us off in this midyear time frame is Nate Stewart, Chief Product Officer at database maker Cockroach Labs, who is seeing the following trends in both consumer and developer demand.
Data Point Trend No. 1: The migration to the cloud has only just begun
A recent COVID-19 era IDC Forecast for 2020 estimates that $69.2 billion will be spent in cloud IT infrastructure in 2020, which represents a predicted 3.6 percent annual increase over 2019 spend. While it’s widely accepted that the adoption of a cloud-centric approach is a smart approach for modern organizations, many IT decision-makers are still hesitant to transition all their data to a cloud environment, preferring to stick to what they know: on-premise legacy systems or private cloud.
However, the remote working model that has been fueled by the pandemic is forcing companies to deeply consider the elasticity and nimble nature of the public clouds. While a complete migration to the cloud represents a path to mitigate risk and cut costs, it is not a full reality yet–nor is it a silver bullet. Many organizations still require a healthy dose of hybrid compatibility with legacy, on-prem systems.
The emergence of Kubernetes has helped many take advantage of effortless scale for stateless workloads, but they are still faced with the challenge of managing mission-critical workloads that rely on a database to deliver a system of record. To date, there’s been an impedance mismatch between the platform and business objectives that have held many of these critical workloads from migration consideration. The legacy database simply does not allow them to take advantage of the cloud as well as advertised. To be successful, IT decision-makers need to be selective in how they manage mission-critical system of record workloads at scale to account for the distributed nature of the cloud.
Data Point Trend No. 2: The continued rise of Kubernetes
Prior to COVID-19, the Cloud Native Computing Foundation (CNCF) cited increased Kubernetes adoption rates as organizations moved to flexible and efficient DevOps environments. COVID-19 will likely further fuel Kubernetes’ popularity among IT decision-makers who want to adapt to the new normal. We are seeing a strain on infrastructure, and organizations are being forced to modify and change their business models, which means they need to iterate and introduce new applications quickly to meet this uber-dynamic (and chaotic) business environment.
Kubernetes provides a platform for this sort of rapid change. But what does all this change mean for the data? Legacy databases can’t keep up with the massive increase in globally dispersed transactional volumes. COVID-19 is forcing IT architects to transition to modern, dynamic systems at an even more rapid pace or else face extinction.
Data Point Trend No. 3: Focus on the developer experience
Developers are consumers, just like everyone else. They use consumer technology every day, experience the benefits and ease of use first hand and want similar experiences from the enterprise applications they use and build at work. The new norm in which we now live and work demands technology that addresses workflow needs and has forced enterprises to rethink their decision-making processes to balance economic value with experiential value. When creating new applications, developers need to ensure that enterprise-focused offerings, even ones that support backend operations, provide a user experience similar to a consumer’s technology experience.
Data Point Trend No. 4: Rethinking disaster resilience
In 2019, Wells Fargo experienced an outage that prevented consumers from completing transactions for hours, even days. Robin Hood had a rather public recurring outage over the course of a month just last winter. Not only did these outages impact its financial standing, but it did significant damage to the brand and bottom line. Companies no longer face the probability of an outage, but the eventuality. This means disaster preparedness, along with disaster recovery, plans are a necessity.
Before an organization creates a disaster recovery plan, it must determine the probability of a disaster and identify two key pain points. The Recovery Time Objective (RTO) determines how long their business can be down without causing significant damage to the brand or bottom line. Recovery Point Objective (RPO) determines the amount of data that can be lost before hurting the business objectives. Once these points are determined, organizations need to ensure their IT infrastructure supports disaster scenarios and meets both of the RTO and RPO business objectives—providing protection against disasters and potential data losses.
With digital as the preferred delivery model, resilience has been elevated to a place of prominence as it can impact both the top and bottom line of the business. It is imperative for IT leaders to stop applying resilience to systems, but instead look for systems that have it baked in as part of the DNA of its end-to-end infrastructure.
Data Point Trend No. 5: Business continuity at scale
The evolution of the database is divided into three waves or generations. The first generation of database tools (dating back to the 1980s) gave us structure and accessibility but ran exclusively on single machines and was very difficult to manage. The second generation gave us NoSQL, which unlocked the earliest data-intensive applications and served the developer well, but consistency, reliability, and support for users outside of the core developer audience suffered.
Now, in the third wave, those two generations of technology come together with a distributed computing approach to relational data structure and standard SQL. These new-age distributed architectures can be deployed on any type of infrastructure and fully utilize the elasticity and global nature of cloud infrastructure. That means that it guarantees data consistency: instances, or even entire data centers, can be lost, without any loss of data or disruptions of service. Cloud-native applications provide a level of resiliency and business continuity at scale that is virtually unprecedented in the data space.
Data Point Trend No. 6: Shift to serverless
According to research by Forrester, nearly 50 percent of companies are either using or plan to switch to serverless architecture within the next year. Serverless is the ultimate end-state cloud architecture that will enable companies to shift complete operational responsibilities to the cloud, effectively increasing agility and innovation. Due to the impacts of COVID-19, the serverless model is now more attractive to organizations because it’s simpler to use, to deploy and to maintain applications. Building serverless applications means that developers can focus on their core product instead of worrying about managing and operating servers or runtimes in the cloud or on-premises. Developers reclaim time and energy that can be spent on more quickly creating applications that have a direct impact on the bottom line.
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