Central Role of Messaging Middleware in Cloud and Digital Transformation Initiatives

Highly decentralized computing is the new normal for most organizations, and digital transformation (DX) initiatives are changing application architectures to event driven to support real-time and near-real-time response cycles. In this environment, enterprises are increasingly turning to messaging middleware to meet the combined requirements of complexity, speed, reliability, and security to connect the digital world of applications and data.

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Lyft’s Move to Microservices: A Case Study

Lyft’s consumer mobile app has real­time transactions totaling more than one million rides per day, so performance is critically important. The smallest lapses – even a few milliseconds – contribute to negative customer experiences and lost revenue. As Lyft’s Vice President of Engineering, Pete Morelli, explained, “The bigger you get, the better you have to be. Half an hour of downtime may have cost you five rides early on, now it costs millions of dollars in rides. The level of reliability expected of Lyft is not trivial. People are riding to work or to doctors’ appointments.

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InVision Improves Performance by 75% with LightStep

InVision is the leading product design collaboration platform that powers the world’s best user experiences. With intuitive tools for ideation, design, prototyping, and design management, the InVision platform gives users everything they need for digital product design, all in one place. More than 4 million people – at tens of thousands of companies, including eighty percent of the Fortune 100, and brands like Airbnb, Amazon, HBO, Netflix, Slack, Starbucks, and Uber rely on the InVision platform to make products users love.

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Enterprise-class Security for Robotic Process Automation

Why, after 20+ years of investment in business process automation technologies, less than 20% of the tasks have been automated? The primary reason is the lack of well defined APIs in 85% of the enterprise systems. The result is an ever growing IT backlog of integration requests from line of business.

This paper provides an overview of the industry’s highest standard for enterprise-grade security as demonstrated by the market’s leading Digital Workforce platform, Automation Anywhere Enterprise.

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RPA + AI = Competitive Edge

Where does RPA intersect with AI? In the hotbed of emerging AI technologies— where you’ll find speech and facial recognition, neural networks, and deep learning to mention a few—RPA meets AI in cognitive computing.

This eBook explains what makes these smart bots—called cognitive bots—so valuable. You’ll discover unprecedented ways cognitive bots can help your business.

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Global Microservices Trends Report

The old elements of logging, metrics, and tracing are insufficient for today’s complex software systems. If you’re adopting microservices, you know that faster root cause analysis and the ability to confidently measure and explain performance is key to improve efficiency and save developer time.

Read this report to understand:

  • Countless disconnected time­series statistics aren’t enough to explain the behavior of modern applications.
  • Tools must identify, triage, and explain latency issues, as organizations adopt microservices
  • It’s critical to evolve our thinking about latency measurements and how they play a part in diagnostic workflows.

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Performance is a Shape – Not a Number

Report Describes How to Confidently Measure and Explain Performance

The old elements of logging, metrics, and tracing are insufficient for today’s complex software systems.

If you’re considering or in the midst of adopting microservices, you know that faster root cause analysis and the ability to confidently measure and explain performance is key to improve efficiency and save developer time. Read this report to understand why:

  • Countless disconnected time-series statistics aren’t enough to explain the behavior of modern applications.
  • Tools must identify, triage, and explain latency issues, as organizations adopt microservices.
  • It’s critical to evolve our thinking about latency measurements and how they play a part in diagnostic workflows.

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Lyft’s Move to Microservices: A Case Study

Lyft’s consumer mobile app has real­time transactions totaling more than one million rides per day, so performance is critically important. The smallest lapses – even a few milliseconds – contribute to negative customer experiences and lost revenue. As Lyft’s Vice President of Engineering, Pete Morelli, explained, “The bigger you get, the better you have to be. Half an hour of downtime may have cost you five rides early on, now it costs millions of dollars in rides. The level of reliability expected of Lyft is not trivial. People are riding to work or to doctors’ appointments.

Learn More

Get Whitepaper

Global Microservices Trends Report

The old elements of logging, metrics, and tracing are insufficient for today’s complex software systems. If you’re adopting microservices, you know that faster root cause analysis and the ability to confidently measure and explain performance is key to improve efficiency and save developer time.

Read this report to understand:

  • Countless disconnected time­series statistics aren’t enough to explain the behavior of modern applications.
  • Tools must identify, triage, and explain latency issues, as organizations adopt microservices
  • It’s critical to evolve our thinking about latency measurements and how they play a part in diagnostic workflows.

View Now

Performance is a Shape – Not a Number

Report Describes How to Confidently Measure and Explain Performance

The old elements of logging, metrics, and tracing are insufficient for today’s complex software systems.

If you’re considering or in the midst of adopting microservices, you know that faster root cause analysis and the ability to confidently measure and explain performance is key to improve efficiency and save developer time. Read this report to understand why:

  • Countless disconnected time-series statistics aren’t enough to explain the behavior of modern applications.
  • Tools must identify, triage, and explain latency issues, as organizations adopt microservices.
  • It’s critical to evolve our thinking about latency measurements and how they play a part in diagnostic workflows.

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Taking Procure-to-Pay to the Next Level with Robotic Process Automation

Organizations have a lot riding on the efficiency and effectiveness of their procure-to-pay processes. Disruptions to an organization’s ability to purchase or pay for materials, goods and services can negatively impact its supply chain, customers and financial standing. Yet, most organizations rely on manual or semi-automated procure-to-pay processes that cost too much, take too long, create too many errors, provide inadequate visibility and frustrate internal stakeholders and suppliers. A big part of the blame can be pinned on the top-down approach that most organizations have traditionally taken to automating business processes. Another contributor is the exploding volume of “dark data” – untapped structured and unstructured data from documents such as invoices, purchase orders and shipping documents. Robotic process automation (RPA) with cognitive automation makes it easier and more cost effective for procure-to-pay organizations to automate. The technology empowers business users with software robots (bots) that automate business processes, such as procure-to-pay, to achieve operational and strategic benefits.

This paper details the challenges with traditional approaches to business process automation, provides an overview of RPA and cognitive automation, and lays out the technology’s benefits in procure-to-pay.

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Enhancing Your RPA Implementation with Intelligent Information

Amidst all of explosive growth in the RPA space, what is keeping organizations from taking their RPA capabilities to the next level? AIIM believes that one answer lies in the unique challenges associated with integrating unstructured information into an RPA environment.

In this eBook, we explore the following questions:

  • What is the current state of process automation, what is keeping organizations from moving forward, and how does RPA address a key pain point for many organizations?
  • How and where is RPA being used to leverage existing enterprise IT investments?
  • What unique challenges does unstructured information create for process automation and RPA engines?
  • What does an intention to spend more on RPA tell us about other key organizational priorities and pain points?

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Ovum Decision Matrix: Selecting a Robotic Process Automation (RPA) Platform, 2018–19

RPA platforms represent a hyper growth market, with enterprises investing in new RPA platforms for process and task automation to achieve greater operating efficiency and agility, while allowing the human workforce to focus on more strategic and higher priority projects and tasks. Intelligent process automation (IPA) is in an early phase of its evolution and represents the next frontier for RPA vendors. This Ovum Decision Matrix (ODM) is a comprehensive evaluation to help enterprise IT and business leaders, including chief information officers (CIOs), enterprise and process architects, IT directors, line-of-business (LOB) leaders and process owners, and digital transformation leaders select an RPA platform that is well suited to their specific requirements.

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7 Predictions For The 2019 RPA Market

With RPA, companies can automate a wide range of processes they wouldn’t have imagined possible before. These range from very rote tasks, such as cutting and pasting customer data from a CRM system into a back-office ERP system, all the way up to unattended software bots capable of intelligent decision-making based on pre-set logic.

What is clear is that RPA is at a tipping point. But will this growth continue? If so, on what path? What innovations lie ahead?

This e-book will provide Automation Anywhere’s insights about the future, with seven RPA predictions for 2019. These predictions relate to market growth, technology disruptions, platform enhancements and new use cases for RPA.

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Cognitive automation: 6 Steps to Success

What cognitive automation is, why you need it, and how to do it right

Adding cognitive capabilities to robotic process automation (RPA) is the biggest trend in business process automation since, well, RPA.

In this eBook, you’ll learn how to succeed with cognitive automation by following six basic steps.

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