How Configuration Management Systems Deliver Change and Compliance

The fundamental capability which configuration management provides is backup and archiving of critical configuration data from network and server equipment. This along with collecting detailed inventory data provide the basis for managing change and compliance.

The ability to detect, report and alert on change in near real time improves overall service availability and reduces the time required to identify the cause of incidents and outages.

This paper is to help Network Engineers, IT Managers and Executive Leadership understand the benefits of configuration management and how it contributes to change and compliance management at the business.

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Optimizing and Automating Event Management to Support Incident Management

Opie has just arrived in the office and sat down to check his email. “Holy moly!” He yells out. He is looking at a massive influx of email messages in his Inbox from the Event Management tool, which was just configured to send out the alert notifications via email. “There’s no way the operations team will be able to respond to all those notifications in an efficient and timely manner. There has to be a better way to handle and address network events.”

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Navigating the 7 Pitfalls of Incident Management

Technology organizations are constantly under pressure to do more with less. With the explosion in both complexity and quantity of applications and digital infrastructure teams need to support, it’s becoming even more critical for IT teams to invest in automation. Explore seven painful anti-patterns that can get in the way of automating incident response for faster resolution and fewer escalations. Learn how you can:

  • Prevent Incidents and Reduce Incident Duration
  • Reduce the Cost of Response
  • Share Knowledge and Continuously Improve

Learn how to tackle these issues to help your team achieve faster resolution and fewer incidents.

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Self-Service Operations

The speed, flexibility, and security controls dictated by today's business demands can't be met with the old practices that Operations has historically relied on. Self-Service operations is a key design pattern that allows organizations to move faster, be more flexible and lock things down. Read this ebook to learn how self-service operations allows you to:

  • Distribute and align operations activity to unlock the full potential of your people and move as fast as your business demands.
  • Experience fewer interruptions and less waiting, resulting in getting more done.

Learn why Self-Service operations is a straightforward, yet powerful operating model that should be in every IT leader’s playbook.

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What is Runbook Automation?

Operations teams feel beat down from working in a high pressure environment with tons of requests and rework. What will Runbook Automation do for your operations?

  • Less waiting and quicker turnaround times — Replace "open a ticket and wait" with "here's the button to do it yourself."
  • Fewer interruptions and escalations— Cut down on the repetitive requests that disrupt your already overworked subject matter experts and delay other work.
  • Shorter incidents — Enable those closest to the problem to take action quickly and effectively.

Learn how Runbook automation can easily translate expert operations knowledge into automated procedures that anyone in your organization can execute on-demand.

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DevOps In An Unplanned World

When done right, DevOps Practices can rapidly increase the speed of release cycles. What happens when critical events occur which cause business disruptions resulting in delays in release schedules? Every minute of outage can mean tens or hundreds of thousands of dollars, sometimes even millions, lost when mission-critical applications are involved.

Download this whitepaper to learn:

  • The 3 key factors for managing a successful service delivery value chain
  • Different curveballs which can add additional friction to the service-delivery process
  • How Everbridge can help organizations deliver services faster and achieve a higher rate of customer satisfaction

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10 Reasons Why You’re Missing Your SLAs

Disruptions caused due to digital issues result in you not meeting the terms of your SLAs (Service Level Agreements) which then result in downtime and service disruptions. On average, the cost of downtime is $9,000 per minute as per the latest MIM report. This can have a negative impact on your brand reputation as well.

Thus, meeting SLAs is a top Enterprise priority. We have compiled a list of factors that lead to you missing your SLAs, download this whitepaper to learn:

  • The solutions to the different factors causing you to miss your SLAs
  • How to establish a streamlined workflow
  • The value of automated escalations

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Why Standardize Orchestration and Automation of the Incident Response Process

There is a real cost to lost opportunities resulting from unplanned technology disruptions, outages, or breaches. In order to minimize downtime and protect people, facilities and business operations, Chief Information Officers (CIOs) need timely information on the nature of every critical event and context to understand how it is affecting the business overall.

In this Executive Brief we cover best practices which help a CIO better orchestrate and automate incident response process and discuss:

  • The three standard ‘Pillars of Response’
  • The five focus areas to achieve digital resiliency
  • A CIO’s role in critical event management

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AI Transformation Playbook

AI (Artificial Intelligence) technology is now poised to transform every industry, just as electricity did 100 years ago. Between now and 2030, it will create an estimated $13 trillion of GDP growth. While it has already created tremendous value in leading technology companies such as Google, Baidu, Microsoft and Facebook, much of the additional waves of value creation will go beyond the software sector.

This AI Transformation Playbook draws on insights gleaned from leading the Google Brain team and the Baidu AI Group, which played leading roles in transforming both Google and Baidu into great AI companies. It is possible for any enterprise to follow this Playbook and become a strong AI company, though these recommendations are tailored primarily for larger enterprises with a market cap/valuation from $500M to $500B.

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Redefining Quality Control with AI-powered Visual Inspection for Manufacturing

Emerging technology — from the introduction of assembly lines to the Internet of Things — has always defined manufacturing.

With the creation of computers and early automation came traditional machine vision, in which machines analyze photos of parts and components for defects based on a set of human-defined rules. While it reduces human error, traditional machine vision lacks the capacity to solve for pain points like complex defects and changing environments.

Today, more sophisticated artificial intelligence (AI), including machine learning (ML) and deep learning (DL), allows manufacturers to use AI-powered visual inspection to enhance quality and reduce costs. But even now, only 5% of manufacturing companies have a clearly defined strategy for implementing AI.

Companies need strategies to overcome challenges in visual inspection, which still relies heavily on human inspectors or inflexible rules-based machine vision. The cost of sending defective pieces to customers — both in reputation and in recalls — isn’t sustainable in a competitive global environment.

The right AI platforms offer tools that can enhance quality control and cut costs — after users tackle key obstacles.

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Accelerate AI Adoption

Landing AI’s industrial AI platform consists of a suite of interconnected tools that enables you to build, deploy, manage and scale AI solutions for visual inspection in an end-to-end workflow.

Designed from the bottom up to enable manufacturers to take projects from concepts to scalable solutions with speed, LandingLens minimizes customization and scaling challenges. While AI models are unique, leveraging universal tools can expedite complex projects. Built for evolving data, LandingLens is comprised of a suite of tools to automate machine learning for industrial vision.

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2020 Global AI-Powered Vision Inspection Enabling Technology Leadership Award

As the AI tide takes over all industries, Landing AI’s most innovative, effective, and easy-to-use AI-powered vision inspection platform enables manufacturers to achieve high-quality output. Landing AI offers immense value to its customers through its robust and adaptive AI algorithms, which is constantly improved by some of the best technical minds in the industry and seamlessly updated at the customer site through the cloud. The visionary leadership of Dr. Andrew Ng, the highly driven techno-commercial team, strong vision inspection domain knowledge, and resilience toward ensuring customer success well position Landing AI to remain a market leader in this space.

With its strong overall performance, Landing AI has earned Frost & Sullivan’s 2020 Enabling Technology Leadership Award in the global AI-powered vision inspection industry.

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2020 State of AI-Based Machine Vision

Of the many use cases in manufacturing, visual inspection—a task that involves using human eye or machine vision to verify if a product is free of defects or if parts are correctly assembled—is well-suited for AI. According to a study by McKinsey & Company, AI-powered quality inspection can increase productivity by up to 50% and defect detection rates by up to 90% compared to manual inspection.

Given these benefits, have businesses started using AI in visual inspections? If so, what is the level of adoption, and what are the challenges? These questions and more drove Landing AI, an industrial AI company, and the Association for Advancing Automation to launch this survey on the state of AI-based machine vision.

The survey polled 110 companies from the manufacturing and machine vision industry with both multiple and single choice questions. Respondents who took the survey perform a variety of roles and include C-suite executives, automation engineers and plant managers. One main takeaway is that businesses have high confidence in the effectiveness of AI, and a growing number of companies are already using deep learning-based machine vision for automated visual inspection.

In this report, we will highlight four key findings, detail those discoveries, and provide analysis.

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AI Transformation Playbook

AI (Artificial Intelligence) technology is now poised to transform every industry, just as electricity did 100 years ago. Between now and 2030, it will create an estimated $13 trillion of GDP growth. While it has already created tremendous value in leading technology companies such as Google, Baidu, Microsoft and Facebook, much of the additional waves of value creation will go beyond the software sector.

This AI Transformation Playbook draws on insights gleaned from leading the Google Brain team and the Baidu AI Group, which played leading roles in transforming both Google and Baidu into great AI companies. It is possible for any enterprise to follow this Playbook and become a strong AI company, though these recommendations are tailored primarily for larger enterprises with a market cap/valuation from $500M to $500B.

View Now

Redefining Quality Control with AI-powered Visual Inspection for Manufacturing

Emerging technology — from the introduction of assembly lines to the Internet of Things — has always defined manufacturing.

With the creation of computers and early automation came traditional machine vision, in which machines analyze photos of parts and components for defects based on a set of human-defined rules. While it reduces human error, traditional machine vision lacks the capacity to solve for pain points like complex defects and changing environments.

Today, more sophisticated artificial intelligence (AI), including machine learning (ML) and deep learning (DL), allows manufacturers to use AI-powered visual inspection to enhance quality and reduce costs. But even now, only 5% of manufacturing companies have a clearly defined strategy for implementing AI.

Companies need strategies to overcome challenges in visual inspection, which still relies heavily on human inspectors or inflexible rules-based machine vision. The cost of sending defective pieces to customers — both in reputation and in recalls — isn’t sustainable in a competitive global environment.

The right AI platforms offer tools that can enhance quality control and cut costs — after users tackle key obstacles.

View Now