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 Topics
    • Application Performance Management/Monitoring
    • Culture
    • Enterprise DevOps

Home » Blogs » DevOps Practice » What Can Automation Learn From DevOps?

What Can Automation Learn From DevOps

What Can Automation Learn From DevOps?

By: Bhanu Singh on April 22, 2019 3 Comments

A recent Capgemini survey revealed that while enterprise-scale automation is still in its infancy, IT automation projects are moving along. IT is starting to view automation less tactically and more strategically.

Recent Posts By Bhanu Singh
  • Legacy Systems: Should They Stay or Should They Go?
  • Engineering Productivity Lessons From COVID-19
  • Edge Computing and ITOps: Opportunities and Challenges
More from Bhanu Singh
Related Posts
  • What Can Automation Learn From DevOps?
  • What Donuts Teach Us About DevOps and Delivery Risk
  • IT Automation Tools Are No Longer Enough
    Related Categories
  • AI
  • Blogs
  • DevOps Practice
  • Enterprise DevOps
    Related Topics
  • Agile methodologies
  • artifical intelligence
  • automation
  • machine learning
Show more
Show less
IT leads automation implementation (respondents were asked to select all that apply: “In which of the following functions has your organization implemented automation initiatives?”). Capgemini Research Institute, Automation Use Case Survey; July 2018, N=705 organizations that are experimenting with or implementing automation initiatives.

The Capgemini survey also showed that IT automation can be responsible for several quick wins, including self-healing, event correlation, diagnostics, application releases, cybersecurity monitoring and storage and server management tasks. These projects not only lead to massive IT cost savings but, more importantly, to an increase in reliability and responsiveness to customer demands and business services. That would indicate that while automation is a great solution for manual work, it’s also a part of a high-level, strategic IT plan to innovate the business.

DevOps/Cloud-Native Live! Boston

As DevOps practices such as agile methodology, continuous deployment and optimization start to take hold within the modern enterprise, it stands to question: Can automation be agile as well? This is the promise of artificial intelligence (AI) for IT operations, or AIOps, but if that’s not a possibility for your IT organization today, it’s important to make sure that your automation practices are continuously optimized to fit the task. Setting and forgetting was a practice of the server era, and in a world of on-demand infrastructure, automation ought to be continuously optimized and evaluated for maximum benefit.

The New Expectations of Automation

IT automation projects can have serious ramifications if anything goes wrong because when the machines execute a policy, they do it in a big way. This is perhaps the chief argument as to why it’s critical that progressive steps are used to define and evaluate both the process being automated and the automation itself—they mitigate the seriousness of any issue that can arise. This is why it’s important to consider the following:

  1. Is this a good process, and is it worth automating?
  2. How often does this process happen?
  3. When it happens, how much time does it take?
  4. Is there a human element that can’t be replaced by automation?

Let’s break down these steps and see how it can provide the basis for an iterative approach to automation:

Is this a Good Process?

This may seem like a rudimentary question, but in fact, processes and policies are often set and forgotten—even as things change dramatically. Proper continuous optimization or agile automation development will force an IT team to revisit existing policies and identify if it’s still right for the business service goals.

Some processes are delicate and automation may threaten their integrity, whereas others are high-level and automation neglects the routine tasks that underlie the eventual results. A good automation engineer understands what tasks are best for automation and sets policies accordingly.

How Often Does this Process Happen?

Patching, updating, load balancing or orchestration can follow an on-demand or time-series schedule. As workloads become more ephemeral moving to serverless cloud-native infrastructure, this process’s schedules will change as well. An automation schedule ought to be continuously adapted to the workload need, customer demand and infrastructure form. As the business continues the march toward digital transformation, the nature and schedule of particular work may become more dynamic.

When It Happens, How Much Time It Takes?

This also depends on the underlying infrastructure. Some legacy systems require updates that may take hours and some orchestration of workloads will be continuous. Automation must be tested to be efficient and effective on the schedule and frequency of the manual task.

Is There a Human Element that’s Irreplaceable?

As much as you may want to, it’s difficult for automation to shift left (to more experienced tasks and teams) without the help of AI or machine learning. Many times, there is a human element involved in deriving insights, creating new workflows, program management or architecture that take place. When building an iterative automation practice, make sure you identify where human interaction must occur to evaluate and optimize. In our lifetime, technology has advanced at lightning speed, with robots now completing jobs that were once held by people. However, there are times when a machine just cannot deliver the same quality a human can.

Automation for All

Automation is perhaps one of the most defining signatures of the future of IT operations management. It relieves teams of routine work and helps improve overall efficiency, all while driving quick wins that turn an IT team into heroes. But don’t let automation be the end goal. Instead, consider it a tool that can drive action from data. And until AI is an everyday option, it’s inherent on the IT professional to continuously optimize the data that drive that action.

— Bhanu Singh

Filed Under: AI, Blogs, DevOps Practice, Enterprise DevOps Tagged With: Agile methodologies, artifical intelligence, automation, machine learning

Sponsored Content
Featured eBook
Hybrid Cloud Security 101

Hybrid Cloud Security 101

No matter where you are in your hybrid cloud journey, security is a big concern. Hybrid cloud security vulnerabilities typically take the form of loss of resource oversight and control, including unsanctioned public cloud use, lack of visibility into resources, inadequate change control, poor configuration management, and ineffective access controls ... Read More
« The Right DevOps Tool for the Job
The DevOps Institute Has Been Brandjacked »

TechStrong TV – Live

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

Upcoming Webinars

Building a Successful Open Source Program Office
Tuesday, May 24, 2022 - 11:00 am EDT
LIVE WORKSHOP - Fast, Reliable and Secure Access to Private Web Apps
Tuesday, May 24, 2022 - 3:00 pm EDT
LIVE WORKSHOP - Boost Your Serverless Application Availability With AIOps on AWS
Wednesday, May 25, 2022 - 8:00 am EDT

Latest from DevOps.com

GitLab Gets an Overhaul
May 23, 2022 | George V. Hulme
DevOps and Hybrid Cloud: Life in the Fast Lane?
May 23, 2022 | Benjamin Brial
DevSecOps Deluge: Choosing the Right Tools
May 20, 2022 | Gary Robinson
Managing Hardcoded Secrets to Shrink Your Attack Surface 
May 20, 2022 | John Morton
DevOps Institute Releases Upskilling IT 2022 Report 
May 18, 2022 | Natan Solomon

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 State of Open Source Vulnerabilities 2020
The State of Open Source Vulnerabilities 2020

Most Read on DevOps.com

DevOps Institute Releases Upskilling IT 2022 Report 
May 18, 2022 | Natan Solomon
Apple Allows 50% Fee Rise | @ElonMusk Fans: 70% Fake | Micro...
May 17, 2022 | Richi Jennings
Making DevOps Smoother
May 17, 2022 | Gaurav Belani
Creating Automated GitHub Bots in Go
May 18, 2022 | Sebastian Spaink
Is Your Future in SaaS? Yes, Except …
May 18, 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.