DevOps.com

  • Latest
    • Articles
    • Features
    • Most Read
    • News
    • News Releases
  • Topics
    • AI
    • Continuous Delivery
    • Continuous Testing
    • Cloud
    • Culture
    • DevSecOps
    • Enterprise DevOps
    • Leadership Suite
    • DevOps Practice
    • ROELBOB
    • DevOps Toolbox
    • IT as Code
  • Videos/Podcasts
    • DevOps Chats
    • DevOps Unbound
  • Webinars
    • Upcoming
    • On-Demand Webinars
  • Library
  • Events
    • Upcoming Events
    • On-Demand Events
  • Sponsored Communities
    • AWS Community Hub
    • CloudBees
    • IT as Code
    • Rocket on DevOps.com
    • Traceable on DevOps.com
    • Quali on DevOps.com
  • Related Sites
    • Techstrong Group
    • Container Journal
    • Security Boulevard
    • Techstrong Research
    • DevOps Chat
    • DevOps Dozen
    • DevOps TV
    • Digital Anarchist
  • Media Kit
  • About
  • AI
  • Cloud
  • Continuous Delivery
  • Continuous Testing
  • DevSecOps
  • Leadership Suite
  • Practices
  • ROELBOB
  • Low-Code/No-Code
  • IT as Code
  • More
    • Application Performance Management/Monitoring
    • Culture
    • Enterprise DevOps

Home » Blogs » DevOps Practice » Predictions 2020: Ushering in 2020 Data Predictions

2020 Data Predictions

Predictions 2020: Ushering in 2020 Data Predictions

By: Haoyuan Li on December 5, 2019 Leave a Comment

2019 brought us more data organizations running more advanced analytics, AI and ML workloads than ever before. 2020 is the year where we’ll see a spike in both the number of technologies and data teams that support these types of workloads internally. We’ll see AI and analytics teams merge into one as the new foundation of the data organization, focused on areas such as moving to the cloud while maintaining on-prem Hadoop, “Kubernetifying” the analytics stack and Hadoop compute. These are the trends I believe we’ll see come about in 2020.

Recent Posts By Haoyuan Li
  • Building Hybrid and Multi-Cloud Architectures for Analytics and AI
More from Haoyuan Li
Related Posts
  • Predictions 2020: Ushering in 2020 Data Predictions
  • DevOps and Hybrid Cloud: Life in the Fast Lane?
  • Starburst Acquires Varada To Deliver The New Standard Of Data Lake Analytics
    Related Categories
  • Blogs
  • DevOps Culture
  • DevOps Practice
  • Doin' DevOps
    Related Topics
  • Hadoop Compute
  • HDFS
  • hybrid cloud
  • kubernetes
  • machine learning
  • Predict 2020
  • Predict 2020 Virtual Summit
Show more
Show less

Rise of the Hybrid Cloud

We’ve been hearing people talk about the hybrid cloud for the past three years now. For the most part, that’s all it’s been talk—but in 2020 it gets real. We are seeing large enterprises refusing to add capacity on-prem to their Hadoop deployments and instead invest in the public cloud. But they are still not willing to move their core enterprise data to the cloud. Data will stay on-prem and compute will be burst to the cloud, particularly for peak demands and unpredictable workloads. Technologies that provide optimal approaches to achieve this will drive the rise of the hybrid cloud. 

DevOps Connect:DevSecOps @ RSAC 2022

One Machine Learning Framework to Rule Them All

Machine learning with models has reached a turning point, with companies of all sizes and at all stages moving towards operationalizing their model training efforts. While there are several popular frameworks for model training, a leading technology hasn’t yet emerged. Just like Apache Spark is considered a leader for data transformation jobs and Presto is emerging as the leading tech for interactive querying, 2020 will be the year we’ll see a front-runner dominate the broader model training space with pyTorch or Tensorflow as leading contenders. 

Kubernetifying the Analytics Stack

While containers and Kubernetes works exceptionally well for stateless applications such as web servers and self-contained databases, we haven’t seen a ton of container usage when it comes to advanced analytics and AI. In 2020, we’ll see a shift to AI and analytic workloads becoming more mainstream in Kubernetes land. Kubernetifying the analytics stack will mean solving for data sharing and elasticity by moving data from remote data silos into K8s clusters for tighter data locality. 

Hadoop Storage (HDFS) is Dead but Hadoop Compute (Spark) Lives Strong

There is a lot of talk about Hadoop being dead, but the Hadoop ecosystem has rising stars. Compute frameworks such as Spark and Presto extract more value from data and have been adopted into the broader compute ecosystem. HDFS is dead because of its complexity and cost and because compute fundamentally cannot scale elastically if it stays tied to HDFS. For real-time insights, users need immediate and elastic compute capacity that’s available in the cloud. Data in HDFS will move to the most optimal and cost efficient system, be it cloud storage or on-prem object storage. HDFS will die but Hadoop compute will live on and live strong.

AI and Analytics Teams Will Merge Into One as the New Foundation of the Data Organization

Yesterday’s Hadoop platform teams are today’s AI/analytics teams. Over time, a multitude of ways to get insights on data have emerged. AI is the next step to structured data analytics. What used to be statistical models has converged with computer science to become AI and ML. So data, analytics and AI teams need to collaborate to derive value from the same data they all use. This will be done by building the right data stack—storage silos and computes, deployed on-prem, in the cloud or in both, will be the norm. In 2020 we’ll see more organizations building dedicated teams around this data stack.

Talent Gap Will Inhibit Data Technology Adoption

Building the stacks that enable data technology into practice is hard, and this will only become more obvious in 2020. As companies discuss the importance of data in their organizations, they’ll need to hire the data, AI and cloud engineers to architect it. But there aren’t enough engineers who have expertise in these technologies to do that. This super-power skill is the ability to understand data, structured and unstructured, and pick the right approach to analyze it. Until the knowledge gap closes, we’ll continue to see a shortage of these types of engineers—many companies will come up short on their promises of “data-everywhere.”

China Is Moving to the Cloud on a Scale Much Larger than the US and Will Leap Frog From On-Prem to Massive Cloud Deployments for Advanced Workloads

Over the past five years, while enterprises in the U.S. have been moving in leaps and bounds to public clouds, enterprises in China have been investing mostly in on-prem infrastructure primarily for data-driven platform infrastructure. 2020 will be the inflection point where this changes. China will leapfrog into the cloud at a scale much larger than the U.S. by adopting the public cloud for new use cases, bursting in the cloud for peak loads and over time move existing workloads. Public cloud leaders in China will see dramatic growth that might outpace the growth of the current cloud giants.

2020 is the year where the rubber meets the road when it comes to advanced analytics and AI. Companies that back the types of technologies that enable and support this kind of data and workloads will emerge as leaders in the space. On the other side, companies that structure their data teams to meet the requirements of the new data stack will emerge as leaders as well. I’m excited to see how advanced analytics and AI opens up new and innovative applications and use cases.

Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

— Haoyuan Li

Filed Under: Blogs, DevOps Culture, DevOps Practice, Doin' DevOps Tagged With: Hadoop Compute, HDFS, hybrid cloud, kubernetes, machine learning, Predict 2020, Predict 2020 Virtual Summit

Sponsored Content
Featured eBook
The State of Open Source Vulnerabilities 2020

The State of Open Source Vulnerabilities 2020

Open source components have become an integral part of today’s software applications — it’s impossible to keep up with the hectic pace of release cycles without them. As open source usage continues to grow, so does the number of eyes focused on open source security research, resulting in a record-breaking ... Read More
« SMBs Struggle with Digital Transformation
The Role of DevOps in Custom Software Development »

TechStrong TV – Live

Click full-screen to enable volume control
Watch latest episodes and shows

Upcoming Webinars

Deploying Microservices With Pulumi & AWS Lambda
Tuesday, June 28, 2022 - 3:00 pm EDT
Boost Your Java/JavaScript Skills With a Multi-Experience Platform
Wednesday, June 29, 2022 - 3:30 pm EDT
Closing the Gap: Reducing Enterprise AppSec Risks Without Disrupting Deadlines
Thursday, June 30, 2022 - 11:00 am EDT

Latest from DevOps.com

DevOps Connect: DevSecOps — Building a Modern Cybersecurity Practice
June 27, 2022 | Veronica Haggar
What Is User Acceptance Testing and Why Is it so Important?
June 27, 2022 | Ron Stefanski
Developer’s Guide to Web Application Security
June 24, 2022 | Anas Baig
Cloudflare Outage Outrage | Yet More FAA 5G Stupidity
June 23, 2022 | Richi Jennings
The Age of Software Supply Chain Disruption
June 23, 2022 | Bill Doerrfeld

Get The Top Stories of the Week

  • View DevOps.com Privacy Policy
  • This field is for validation purposes and should be left unchanged.

Download Free eBook

The 101 of Continuous Software Delivery
New call-to-action

Most Read on DevOps.com

Four Steps to Avoiding a Cloud Cost Incident
June 22, 2022 | Asim Razzaq
How FinOps Can Optimize Cloud Costs and Drive Innovation
June 21, 2022 | Larry Cusick
The Age of Software Supply Chain Disruption
June 23, 2022 | Bill Doerrfeld
Survey Uncovers Depth of Open Source Software Insecurity
June 21, 2022 | Mike Vizard
At Some Point, We’ve Shifted Too Far Left
June 22, 2022 | Don Macvittie

On-Demand Webinars

DevOps.com Webinar ReplaysDevOps.com Webinar Replays
  • Home
  • About DevOps.com
  • Meet our Authors
  • Write for DevOps.com
  • Media Kit
  • Sponsor Info
  • Copyright
  • TOS
  • Privacy Policy

Powered by Techstrong Group, Inc.

© 2022 ·Techstrong Group, Inc.All rights reserved.