DevOps.com

  • Latest
    • Articles
    • Features
    • Most Read
    • News
    • News Releases
  • Topics
    • AI
    • Continuous Delivery
    • Continuous Testing
    • Cloud
    • Culture
    • DataOps
    • DevSecOps
    • Enterprise DevOps
    • Leadership Suite
    • DevOps Practice
    • ROELBOB
    • DevOps Toolbox
    • IT as Code
  • Videos/Podcasts
    • Techstrong.tv Podcast
    • Techstrong.tv - Twitch
    • DevOps Unbound
  • Webinars
    • Upcoming
    • Calendar View
    • On-Demand Webinars
  • Library
  • Events
    • Upcoming Events
    • Calendar View
    • On-Demand Events
  • Sponsored Content
  • Related Sites
    • Techstrong Group
    • Cloud Native Now
    • Security Boulevard
    • Techstrong Research
    • DevOps Chat
    • DevOps Dozen
    • DevOps TV
    • Techstrong TV
    • Techstrong.tv Podcast
    • Techstrong.tv - Twitch
  • Media Kit
  • About
  • Sponsor
  • AI
  • Cloud
  • CI/CD
  • Continuous Testing
  • DataOps
  • DevSecOps
  • DevOps Onramp
  • Platform Engineering
  • Sustainability
  • Low-Code/No-Code
  • IT as Code
  • More
    • Application Performance Management/Monitoring
    • Culture
    • Enterprise DevOps
    • ROELBOB
Hot Topics
  • Atlassian Advances DevSecOps via Jira Integrations
  • PagerDuty Signals Commitment to Adding Generative AI Capabilities
  • Mastering DevOps Automation for Modern Software Delivery
  • DigiCert Allies With ReversingLabs to Secure Software Supply Chains
  • The Future of Continuous Testing in CI/CD

Home » Blogs » Continuous Delivery » XebiaLabs Injects Predictive Analytics Into DevOps Platform

XebiaLabs Injects Predictive Analytics Into DevOps Platform

Avatar photoBy: Mike Vizard on April 17, 2019 1 Comment

XebiaLabs is moving to take the guesswork out of DevOps following the launch of a set of tools that leverage machine learning algorithms to predict when and how the release of an application is most likely to go awry.

Recent Posts By Mike Vizard
  • Atlassian Advances DevSecOps via Jira Integrations
  • PagerDuty Signals Commitment to Adding Generative AI Capabilities
  • DigiCert Allies With ReversingLabs to Secure Software Supply Chains
Avatar photo More from Mike Vizard
Related Posts
  • XebiaLabs Injects Predictive Analytics Into DevOps Platform
  • XebiaLabs Drives Triple-Digit Growth and Closes $100M+ Strategic Capital Investment from Susquehanna Growth Equity and Accel
  • XebiaLabs Shows Off ARA, More at Jenkins World
    Related Categories
  • AI
  • Continuous Delivery
  • DevOps Toolbox
  • Doin' DevOps
    Related Topics
  • application release
  • application release lifecycle management
  • devops
  • machine learning
  • Predictive Analytics
Show more
Show less

The Risk Prediction Module being added to the XebiaLabs DevOps platform comes on the heels of XebiaLabs’ move to make its XL JetPack software for automating application deployments available on the Amazon Web Services (AWS) Marketplace. XL JetPack is an automation framework based on YAML files and a declarative programming framework that enable DevOps teams to push applications into production on a cloud platform in as little as 15 minutes.

Cloud Native NowSponsorships Available

XebiaLabs CEO Derek Langone said that while DevOps advancements have been made in terms of achieving continuous integration, the goal of achieving continuous delivery has proven to be more elusive. As automation frameworks such as XL JetPack become more accessible, however, IT operations teams will be better able to keep pace with the rate at which organizations want to be to deploy and update applications, he said.

It’s becoming increasingly apparent that a combination of automation frameworks and machine learning algorithms will enable DevOps teams to make a significant leap forward in terms of application release lifecycle management. Because of all the nuances of the different platforms that IT organizations are trying to leverage, it’s become a major challenge to roll out an application manually. As the number of applications that need to be released at roughly the same time increases, managing the release cycle process is moving beyond the capabilities of an IT team made up of mere mortals.

The Risk Prediction Model from XebiaLabs promises to increase the odds of success by applying predictive analytics infused with machine learning and other proprietary XebiaLabs algorithms to identify DevOps bottlenecks before they are encountered. Capabilities provided by that module include alerts that warn the team when a release is likely to be delayed or to fail before the release pipeline starts running; a Risk Forecast view that summarizes predicted delays and failures for every task in the release process; an overview of statistics for similar releases to provide historical context; and forensics tools that uncover flaky automated tests, problematic build setups, long-running deployments and time-consuming manual tasks. That Risk Prediction Module is meant to complement the risk scoring capability that XebiaLabs already includes in its platform.

Arguably, the biggest barrier to DevOps adoption today continues to be the level of expertise required to succeed. But as the combination of predictive analytics infused with machine learning algorithms and algorithms that can discern instantly how changes to the IT environment will impact applications become more common, the level of expertise required to master DevOps processes should decline. As that transition occurs, the number of organizations embracing DevOps more broadly should increase.

In the meantime, DevOps teams would be well-advised to consider to what degree they might next want to rely on predictive analytics to prescriptively automate processes with eye toward eliminating the need for as much human intervention as possible.

— Mike Vizard

Filed Under: AI, Continuous Delivery, DevOps Toolbox, Doin' DevOps Tagged With: application release, application release lifecycle management, devops, machine learning, Predictive Analytics

« Building Amazing Apps, Part 3: Optimizing the Network
HybridOps: Driving Better Collaboration and Productivity in IT »

Techstrong TV – Live

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

Upcoming Webinars

Maximize IT Operations Observability with IBM i Within Splunk
Wednesday, June 7, 2023 - 1:00 pm EDT
Secure Your Container Workloads in Build-Time with Snyk and AWS
Wednesday, June 7, 2023 - 3:00 pm EDT
ActiveState Workshop: Building Secure and Reproducible Open Source Runtimes
Thursday, June 8, 2023 - 1:00 pm EDT

GET THE TOP STORIES OF THE WEEK

Sponsored Content

PlatformCon 2023: This Year’s Hottest Platform Engineering Event

May 30, 2023 | Karolina Junčytė

The Google Cloud DevOps Awards: Apply Now!

January 10, 2023 | Brenna Washington

Codenotary Extends Dynamic SBOM Reach to Serverless Computing Platforms

December 9, 2022 | Mike Vizard

Why a Low-Code Platform Should Have Pro-Code Capabilities

March 24, 2021 | Andrew Manby

AWS Well-Architected Framework Elevates Agility

December 17, 2020 | JT Giri

Latest from DevOps.com

Atlassian Advances DevSecOps via Jira Integrations
June 6, 2023 | Mike Vizard
PagerDuty Signals Commitment to Adding Generative AI Capabilities
June 6, 2023 | Mike Vizard
Mastering DevOps Automation for Modern Software Delivery
June 6, 2023 | Krishna R.
DigiCert Allies With ReversingLabs to Secure Software Supply Chains
June 6, 2023 | Mike Vizard
The Future of Continuous Testing in CI/CD
June 6, 2023 | Alexander Tarasov

TSTV Podcast

On-Demand Webinars

DevOps.com Webinar ReplaysDevOps.com Webinar Replays

Most Read on DevOps.com

No, Dev Jobs Aren’t Dead: AI Means ‘Everyone’s a Programmer’? ¦ Interesting Intel VPUs
June 1, 2023 | Richi Jennings
Forget Change, Embrace Stability
May 31, 2023 | Don Macvittie
Revolutionizing the Nine Pillars of DevOps With AI-Engineered Tools
June 2, 2023 | Marc Hornbeek
Friend or Foe? ChatGPT’s Impact on Open Source Software
June 2, 2023 | Javier Perez
Checkmarx Brings Generative AI to SAST and IaC Security Tools
May 31, 2023 | Mike Vizard
  • Home
  • About DevOps.com
  • Meet our Authors
  • Write for DevOps.com
  • Media Kit
  • Sponsor Info
  • Copyright
  • TOS
  • Privacy Policy

Powered by Techstrong Group, Inc.

© 2023 ·Techstrong Group, Inc.All rights reserved.