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7 days of upcoming tech trends!

8 ways the tech world will change in 2019: DevOps, Kubernetes, open source fragmentation, and more

Ravi Mayuram
DevOps
© Shutterstock / My Life Graphic

2018 has certainly been a year. As the days grow shorter, we can’t help but look forward to a brand new 2019 and all the amazing tech trends in store for us. Today, Ravi Mayuram goes over eight of his predictions for the tech world in the new year, including the future of DevOps, Kubernetes, open source, and more.

No one know what the future might hold, but we’re taking our best stab at it with some pretty educated guesses. The new year is just around the corner and we’ve asked a number of experts what they think is in store for developers in 2019.

Obviously, nothing is set in stone. However, we talked to Ravi Mayuram, a Senior VP of Products and Engineering and CTO at Couchbase, about where the tech world will go in 2019. His thoughts: open source fragmentation, the rise of Kubernetes and serverless, and DevOps’ continued relevance.

Without further ado, let’s see what our expert had to say!

DevOps, serverless, open source

1. Open Source fragmentation will lead to developer headaches.

We’re beginning to see an inflection point with Open Source. For example, Oracle is taking a more commercial approach to Java, which will cause fragmentation for Java developers. Additionally, some database companies have changed their licensing terms and Open Source models, which will cause issues for cloud players who were previously benefiting from the software. In 2019, developers will be challenged to determine which Open Source platform to move to that matches all their needs and works cohesively with their current technology – without threat of changing.

2. Kubernetes keeps climbing as the contender to power Cloud 2.0.

In 2018, Kubernetes emerged as the defacto cloud orchestration layer after having organized the container chaos across the industry. But we’re still very much in the early days of Kubernetes – and as the software ecosystem around containers grows (i.e. performance, tracing, cloud monitoring) in 2019, Kubernetes will become more than just the orchestration layer. It will become the operating system as we move to Cloud 2.0, the next phase of cloud technology that is intelligent and business-driven — and that uses true multi-cloud strategies.

3. Serverless becomes less mysterious.

Today, every CIO and CTO are evaluating serverless technologies, but a big constraint preventing adoption is the potential for vendor lock-in and unknown variables. In 2019, the mystery around serverless will slowly lift – and in the process, bring it to broader adoption. Today, serverless can lead to lock-in with certain cloud implementations, but we’re likely to see an emerging ecosystem of supporting technologies develop as microservices lay the foundation for a new type of cloud operating system.

SEE ALSO: Which technologies will dominate in 2019? Containers and serverless go head to head

Cloud and AI/ML

4. Multi-cloud implementations suffer new issues from lack of interoperability across clouds.

As providers continue to innovate before standardizing processes and interoperability, problems will arise in multi-cloud environments because providers have created interfaces with slightly different ways of working. For example, Google and Amazon each have their own messaging systems, as does Kafka, and applications developed do not simply move to another without undergoing changes. In 2019, these issues will come to light – and users will experience many headaches before true interoperability is achieved across multi-cloud deployments.

5. The groundwork has been laid for AI/ML technologies, and now the real questions will surface.

Over the past year, companies have been figuring out where and how to implement AI/ML technologies, and many are still refining the “how.” While that’s true, the groundwork has been laid and the mentalities have been shifted, and 2019 will be a big year for questions in AI/ML – literally, in the sense of how organizations determine what questions to use to train their AI/ML algorithms. There are also broader conversations that have been sparked around ethics and biases, and 2019 will see the conversation continue, with academia and business working together to develop a trusted approach to developing AI/ML for the future.

6. Data gets a makeover to support AI/ML algorithms.

Today, data remains a difficult part of AI and is a barrier to effective training methods and truly trusted outcomes. Data quality and availability can vary wildly within an organization, and it can take time to determine what data is clean, up-to-date and trustworthy. 2019 will see data systems come under greater scrutiny within the enterprise as data grows in value, and we’ll see efforts to address data quality across the board to better leverage AI/ML technologies.

7. IoT data and edge analytics will prove more valuable than predictive analytics in 2019.

Many organizations are currently focused on predictive analytics — and for good reason, as it promises to solve issues before they actually become issues. But in the next year, analytics at the edge will deliver more business value than predictive analytics in the cloud. Edge analytics makes sense of the terabytes of always flowing IoT data to empower field workers, line of business decisions, and overall helps organizations to better serve customers in different ways. While it will ultimately complement maturing predictive analytics, IoT data and analytics at the edge will see a higher ROI in the coming year for its many applications.

SEE ALSO: The JAX DevOps 2019 program is live!

Future of the database / NoSQL

8. The database sprawl will continue as different types of databases proliferate.

App developers are creating a lot of data in a lot of different ways, but it’s all bumping into each other without a serviced solution that offers flexibility to house and manage this data. As it stands, developers are using multiple databases for each individual application, creating a database sprawl as users cobble together multiple databases to plug different holes in the system. While the short-term gain of being able to use emerging technologies and have many choices seems great upfront, companies need to consider their long-term goals, rather than select a cobbled together, quick solution.

Author

Ravi Mayuram

Ravi Mayuram is a Senior VP of Products and Engineering and CTO at Couchbase. Follow him on Twitter @RaviMayuram.


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