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Why AIOps Matters for Customer Experience

By Viki Paige, Director of AIOps Solution Marketing

There’s been a proliferation of AIOps articles, reports and product news in the past few months, with no shortage of points of view, schools of thought and rules of thumb. After sifting through all the different opinions, approaches and claims, it’s easy to lose sight of what’s most important. No wonder the monthly Google search volume for AIOps is nearly triple what it was a year ago. In this post, we’ll attempt to sort through the noise and take a look at why AIOps really matters for today’s organizations.

One Dominant Business Driver for AIOps

When it comes to AIOps deployments, there can be a tremendous amount of variation from one organization to the next. Implementation approaches, use cases and technological environments can all vary widely. AIOps promises to improve event correlation, speed root cause analysis, establish automation, and much more.

In spite of all this diversity and variation, there’s almost unanimous agreement among our customers on one thing: the most important objective for doing AIOps in the first place. It’s all about delivering a better customer experience. In fact, 93% of our customers say that’s the number one reason they’re adopting AI and machine learning according to a recent survey we conducted. With all the possibilities and variations around AIOps, it can be easy for teams to lose sight of this most critical business outcome. 

Optimizing the Digital Experience: The Mandate and Challenges

For today’s organizations, delivering digital services that delight customers is a competitive mandate. While this objective grows increasingly critical for the business, it is becoming a daunting challenge for IT operations, particularly given the complex, dynamic and ephemeral nature of today’s IT ecosystems.

Within many organizations, the increasing reliance on cloud services, containers, microservices, and other modern technologies has led to a dramatic proliferation of operational data. Some reports indicate teams now are contending with a ten-times increase in monitoring metrics given the emergence of these technologies.

These metrics are important. However, given the interrelated, complex nature of today’s environments, the metrics traditionally tracked don’t necessarily provide a very clear picture of what really matters: how system performance is affecting the customer experience.

More metrics equates to more alarms. While following up on these alarms is vital, it is getting increasingly difficult to weed out redundant or low-level alarms and ensure the highest priority items are always spotted and immediately acted upon. Fundamentally, the explosion in the volume, variety, and velocity of data has brought teams to a point in which humans simply can’t keep pace.

The Bottom-line Benefits of Optimized Experiences

Given the customer experience imperatives, and the challenges associated with addressing them, AIOps is emerging as one of the most strategic initiatives for organizations. For IT to deliver value to the business, teams need the right service-driven metrics at the right time—and we believe that AIOps from Broadcom uniquely delivers these capabilities.

With its advanced analytics and intelligent automation, our AIOps solution provides comprehensive insights and enables proactive remediation. Your teams can now detect and address complex IT problems, including performance, capacity, and configuration issues—before they have an impact on customers or the business.

With the help of our AIOps solution, you can start delivering the optimized digital experiences that businesses and customers need, and so realize a number of significant dividends. By employing our solution, customers have realized these business benefits:

  • 69% increase in customer retention
  •  68% growth in new customers
  •  49% more profits

You can learn more about how IT and business leaders are measuring happy customers in this recent survey we conducted with Dimensional Research on Improving User Experience and the Bottom Line

Delivering optimized digital experiences is now critical for today’s businesses, and meeting this objective will only grow more vital in the weeks and months ahead. Find out how your organization can start delivering flawless, secure customer experiences that propel your business. To learn more, visit our digitalexperience.ai page.

Fueling Digital Disruption with AIOps

By: Kieran Taylor, Head of AIOps Product Marketing

What’s your organization’s vision for digital transformation? Simply moving an existing service online, or upending your markets? The reality is that today’s AIOps solutions are fueling breakthroughs in terms of what’s possible. In this blog post, I’ll take a look at some of the innovations taking place in the market, and examine the massive impact advanced AIOps solutions can have on your digital transformation initiatives. 

Where Will Digital Transformation Take You?

What does digital transformation mean to your business’ leadership? That’s looming as an increasingly important question. Within many organizations, digital transformation initiatives  start with a focus on a specific project. For example, leadership will focus on moving an existing service to a new digital channel.

While there’s nothing wrong with starting pragmatically, the reality is that digital transformation isn’t a project; it’s a journey. That’s why it’s important to understand the longer-term direction and ultimate destination. Ultimately, digital transformation can have an impact not only on digital interactions, but on operations, business models, and entire markets.

There’s numerous examples of digital pioneers, companies that have converted digital savvy into the innovative offerings and models that disrupt competitors and even create entirely new markets. While these disruptors are often digital-native upstarts, what I find most exciting are examples of well-established enterprises that have transformed their businesses.

Take for example a leading telecommunications firm that has transformed its complex operations infrastructure and gained insights for optimizing all aspects of the software delivery lifecycle. Through these AIOps-driven initiatives, they’ve been able to enhance customer experience and streamline new service delivery. Now, instead of needing several months to deliver a new service, it takes less than two weeks. As a result, the organization is outpacing its competitors, delivering differentiated services that are disrupting its markets.

Innovations Open up New Possibilities

Digital disruption is being propelled by innovations in three key areas: big data, artificial intelligence and machine learning, and automation—and the pace of innovation continues to accelerate. Advancements in each of these areas are being brought to bear in AIOps, which is fueling increasingly significant potential in terms of the operational and business benefits. The reality is that teams can now leverage significantly more powerful capabilities today than they could even just a year ago, and the payoff can be huge. According to a survey we conducted with Frost & Sullivan, enterprises that adopt an advanced digital experience infrastructure see their profits increase two-times faster.

Our Vision for Transcending AIOps

To date, AIOps has largely been associated with IT operations, which is not a surprise given the phrase stands for artificial intelligence in IT operations. However, we at Broadcom have a vision for the category that transcends IT operations.

At its core, AIOps is about customer experiences, and IT operations teams aren’t the only groups that have an interest in, and contribute to, customers’ digital experiences. Line-of-business leaders, development organizations, security staff, testing teams, and more all play a critical role. However, for the most part, these teams have been operating in silos, employing unique tools and workflows. The result is that these different groups are ill-equipped to effectively share data and collaborate. When done right, AIOps will analyze and correlate data across all these teams.

At Broadcom, we are executing on a vision to use AIOps to connect business goals, customer experience, and application delivery systems in a virtuous cycle of continuous improvement. automation.ai represents the realization of our vision of connecting data, not tools.

automation.ai combines comprehensive ecosystem observability, advanced analytics, and intelligent automation to provide comprehensive insights across your digital delivery chain, from user experiences with mobile applications to backend mainframes, and all points in between.

Our platform correlates and analyzes comprehensive data sets, leveraging data on topology, network flow, user journeys, transactions, time-series, and more. It then applies AI and machine learning to these data sets, using algorithms developed and trained based on extensive digital business data from the world’s largest enterprises. We then apply proven machine-learning techniques in a continuous fashion to ensure the right automated actions are taken to proactively solve today’s most complex IT problems. automation.ai fosters continuous improvement, enabling teams to realize these objectives:

  •  Optimize service delivery. By providing unified intelligence and advanced management and monitoring capabilities, your DevOps teams can view the software delivery lifecycle holistically and optimize every phase to consistently deliver flawless, secure customer experiences.
  •  Increase operational efficiency. automation.ai represents a single platform that fuels insights and efficiency. The solution enables organizations to employ a single platform for the entire digital delivery chain. With automation.ai, disparate teams can share data, collaborate, and optimize, with unprecedented ease and efficiency.
  •  Accelerate innovation and transformation. By enabling collaboration and optimization throughout software delivery lifecycle, our platform helps your teams realize breakthroughs in their digital transformation initiatives from transforming experiences, to reinvent businesses, and ultimately disrupt markets.

We believe that automation.ai will transcend AIOps by extending benefits to all the teams that contribute to a customer’s digital experience. By combining comprehensive ecosystem observability, advanced analytics, and intelligent automation, our platform helps your teams optimize service delivery, increase IT efficiency, and accelerate innovation. Watch this video, where I share more about how we’re helping customers become digital disruptors and see how you can get started on your digital transformation journey.


Maximizing AIOps Dividends: 5 Key Solution Requirements—and How Broadcom Delivers

By Sudip Datta, Head of AIOps Products

To keep pace with escalating demands and data volumes, artificial intelligence for IT operations (AIOps) solutions are emerging as an increasingly foundational solution for today’s DevSecOps teams. In my latest blog post, I’ll share the five most critical requirements for an effective AIOps solution and how AIOps from Broadcom® uniquely meets these key imperatives.

Today, customer experience is the number one measurement for the quality of digital services your business delivers. It’s therefore not an overstatement to say that virtually every core business success metric is in some way contingent upon the performance of the IT infrastructures and operations that power the business’ digital services. While optimizing service levels is critical, it seems to be getting more challenging to do every day. This is true for two key reasons:

  • Complexity. Most digital services now rely not only on traditional systems, including on-premises mainframes and distributed platforms, but on a plethora of new, dynamic technologies, such as containers, software defined networks, cloud delivery models, virtual and software-defined components, and more.
  •  Scale. The volume, variety, and velocity of data that needs to be managed, correlated, and analyzed continues to grow dramatically. In the wake of initiatives like multi-cloud deployments, microservices development, and Internet of Things (IoT) implementations, teams continue to see explosive growth in the operational data being generated, often totalling petabytes. Ultimately, internal team members simply can’t keep pace.

To contend with the explosive growth in data, increasing complexity, and heightened user demands, IT teams need to adopt an AIOps solution. By delivering AI, machine learning, and automation, AIOps solutions enable teams to manage and optimize service levels in modern IT environments. With the right AIOps solution, you can improve IT efficiency, reduce cost and transform the customer experience.

Sudip Datta, Head of AIOps Products for the Enterprise Software Division at Broadcom shares the five things you should look for in an AIOps solution.

Further Insights on Key AIOps Requirements and How Broadcom Can Help

To maximize the potential benefits of AIOps, decision makers should ensure the solution they employ addresses these five requirements:

#1: Service-driven business insight

At the end of the day, IT has to serve the business. IT teams need business service-based views in order to identify which issue is affecting the business’ most important key performance indicators (KPIs).

Through smart service modeling, AIOps from Broadcom delivers business-driven service views that connect your underlying application, infrastructure, and network components, so you can quickly identify which issue is having the biggest impact on your business’ KPIs. Our AIOps solution integrates with End User Monitoring (EUM) tools to track business KPIs against the services. This enables more intelligent prioritization, so teams can minimize any impact on the customer experience and ensure the most critical business services continue to perform optimally.

#2: Full ecosystem observability

For managing your organization’s entire digital experience, it’s imperative to collect and observe data from each component of the digital chain — mobile to mainframe, cloud to on-prem, and from the end user layer to the infrastructure, including the network in between. 

However, with the increasing prevalence of approaches like continuous integration/continuous delivery, DevOps, containers, and microservices, environments continue to grow more dynamic, ephemeral, interrelated, and complex. In this type of environment, it’s difficult to apply traditional monitoring, virtually impossible to keep it consistently current, and challenging to get the outputs needed to truly understand performance.

To address these limitations, IT teams need to move from monitoring to observability. Quite simply, to be successful, it’s not enough to monitor a monolithic computing stack or a discrete infrastructure element. Teams need to make complex, modern ecosystems observable.

With AIOps from Broadcom, your teams can establish observability of their modern implementations. They can aggregate and correlate data from multiple sources, and combine intelligence in a unified data lake. Our solution’s coverage spans from mobile platforms to mainframes, and from the user experience to the application to the network. It can also ingest intelligence from a wide range of third-party tools, including open-source monitoring products.

AIOps from Broadcom cross correlates intelligence from every component being tracked. By applying machine learning to these unified data sets, our solution enables teams to understand interrelations among different elements. Now, your teams can see how everything in your environment is connected via an intuitive topology view. With these capabilities, teams can begin to track the indicators that really matter, and gain the intelligence needed to understand and optimize performance.

#3: Comprehensive data sets

For true AI-driven insights, comprehensive data sets are essential. AIOps from Broadcom provides extensive depth and breadth of coverage, ingesting structured and unstructured data, including metrics, alarms, logs, topology, text, and API data. Historically, Manager of Managers have been positioned as AIOps tools and they ended up being alarm aggregation engines, as opposed to enablers of predictive and root cause analytics.

Only our AIOps solution ingests and correlates all these data types and offers metric-driven—rather than event-driven—anomaly detection to help you discover potential issues before they affect your users. We believe that the structured and unstructured data presented contextually and in combination can provide the appropriate level of insight and depth that serve the right personas from the SRE to NOC operators to the level-2 administrators,

#4: Algorithmic root cause analytics

Once unified, comprehensive data sets have been established, teams need machine learning-based algorithms that can automatically find the root cause of problems. Today organizations are dealing with thousands of alarms that are being filtered manually and then further dissected in war room situations resulting in an MTTR of 4-5 hours.

With AIOps from Broadcom, your teams can move from reactive firefighting to proactive management. Our AIOps solution delivers machine-learning-based algorithms that can automatically identify the cause of issues. 

Only our extensive library of algorithms leverages the “four Ts”—topology, time, text, and training—to correlate information from multiple data sources and determine the root cause. The topology and time define the boundaries of space and time thereby eliminating unrelated noises. The usage of Natural Language Processing (NLP) helps in deduplicating messages. Further details on the algorithms can be found in this technical white paper.

#5: Intelligent automation

Now more than ever, it’s critical that your teams can reduce outages and fix problems before they have an impact on your business. AIOps from Broadcom features leading predictive analytics that can trigger autonomous remediation and preempt issues. Rather than having IT admins hardcoding automation actions against conditions, we employ machine learning on past heuristics to assign recommendation scores to possible automation actions. Our solution can automatically trigger proactive execution of remediation scripts, and the automated updating of service desk tickets to reflect the steps taken—all before users ever notice there’s an issue.

With the right AIOps solution, today’s DevSecOps teams can realize improved service levels, cost efficiencies, and agility. By delivering all the must-have capabilities required, AIOps from Broadcom puts your teams in an optimal position to wring maximum benefits from their AIOps investments

To learn more about our solution, read the white paper: AIOps Essentials – A Unified Data Model as the Foundation for AIOps

How To Harness The Power Of Observability, AIOps And Automation

By: Ali Siddiqui, Head of AIOps Segment, Enterprise Software Division, Broadcom

Does one plus two ever equal 30? It can when you’re talking about combining the concept of observability with the power of automation and artificial intelligence for IT operations (AIOps). In this post, I’ll introduce the concept of observability and show how AIOps and automation can be powerful complements. You can use these approaches to deliver the capabilities IT teams need to track and optimize their dynamic modern environments.

Introduction To Observability: What It Means And Why It Matters

Today, many IT teams are struggling with an overload of metrics. In many organizations, massive amounts of metrics are being generated, the vast majority of which they may never look at. This leads to a case of severe metric fatigue. This reality, coupled with the increasing complexity and dynamism of today’s environments, is part of what’s driving a widespread move to observability.

At a high level, observability refers to the degree to which the internal state of a system can be inferred based on externally available outputs. Therefore, the more observable a system is, the more it will enable teams to understand, manage, and enhance its performance. Teams can use observability to gain new levels of visibility focusing on business services that drive digital transformation.

Observability is emerging as a critical consideration for today’s DevSecOps teams, who are tasked with adapting to the radical transformation of IT environments. In the past, monitoring systems were focused on capturing, storing, and presenting data generated by underlying IT systems. This meant that human operators were responsible for analyzing the resulting data sets and making necessary decisions.

This fundamental model doesn’t align with current realities, however. With the increasing prevalence of approaches like continuous integration/continuous delivery, DevOps, containers and microservices, environments continue to grow more dynamic, ephemeral, interrelated and complex. With basic monitoring techniques, teams may lack the visibility they need, and their manual processes can’t always scale to support the explosive growth in data volumes that arise in these modern environments.

Traditional monitoring approaches worked fine when an operator was tasked with tracking a simple, static system within an isolated computing stack. These systems typically had easily observable outputs that made it easy to understand and predict behavior. Today’s environments present a completely different picture. For example, a team may be responsible for a cloud-based microservices implementation that’s highly ephemeral, with elements in a virtually constant state of flux. In this type of environment, it’s difficult to apply traditional monitoring, virtually impossible to keep it consistently current, and it’s challenging to get the outputs you need to truly understand performance.

To address these limitations, teams can reorient their goals and approaches and move from monitoring to observability. It’s no longer about monitoring a monolithic computing stack or a discrete infrastructure element; it’s about making complex, modern ecosystems observable. By doing so, teams can fully capitalize on the agility of modern approaches while optimizing service levels at the same time.

Another critical consideration in this regard is the fact that monitoring can’t be an afterthought after development is done. Rather, observability should be a part of the software development life cycle, and it should be part of the culture, just like DevOps.

How To Capitalize On AIOps And Intelligent Automation

Through AIOps and intelligent automation, teams can establish a strong complement to their observability initiatives. IT teams should seek to address these core steps in AIOps initiatives:

• Acquire: They should harness various data sources from across the organization’s ecosystem.

• Aggregate: They should aggregate data from disparate sources and apply correlation to fully capitalize on the intelligence they capture.

• Analyze: Teams should focus on artificial intelligence and machine learning that filters through noise, gains more targeted insights, and identifies patterns that enable more accurate predictions.

• Act: They should find ways to automate root cause analysis and remediation, as well as the opening and closing of tickets.

Tips for Leveraging AIOps And Automation To Promote Observability

Teams can leverage AIOps and automation to expand and enhance observability efforts in a couple of key ways:

• Enhance ecosystem observability. Teams should aggregate data from multiple sources and combine intelligence in a unified data lake. By applying machine learning to these unified data sets, teams can begin to understand interrelations among different elements. This can help teams can move beyond vague potential predictors of issues to a true understanding of causality, even across disparate yet interrelated systems. These insights can ultimately help teams establish observability of the complex, distributed and interrelated ecosystems that power today’s business services.

• Expand visibility. Instead of just tracking production environments, teams can pragmatically expand their automated monitoring into development and testing scenarios. In this way, teams can gain insights into the instrumentation enhancements that will further improve observability throughout the software development life cycle.

Conclusion

For IT teams contending with the dynamic, large-scale nature of modern IT environments, it is growing increasingly critical to employ observability techniques. Through observability, teams can achieve new breakthroughs in visibility and service levels. By combining observability with AIOps strategies, teams can promote not only enhanced service delivery but also accelerated digital innovation to help IT more effectively support business objectives.

Employing AIOps to Establish Self-healing Networks: The Mandate for Hyper-connected Businesses in a 5G World

By: Ashok Reddy, General Manager for the Enterprise Software Division

Business success is increasingly contingent upon optimally performing, highly reliable network communications. However, for the teams responsible for tracking and managing network performance, the job only seems to get tougher. In this post, I outline why current trends are making the move to AI-enabled networks an urgent requirement.

In addition, I discuss why Broadcom is uniquely positioned to help organizations navigate this transition successfully. Today, 99.9% of internet traffic goes through Broadcom technology and 100% of public clouds use our products. This market presence puts us in an unrivaled position to help businesses make the move to the AI-enabled networks of the future.

Challenges of Modern Network Environments

Today, it is through digital channels that businesses serve customers, manage operations, track supply chains, and more. Now, it is through these channels that businesses compete. Today’s businesses are now hyper-connected, constantly reliant upon complex, multi-cloud environments connected through a mesh of networks.

Ultimately, business fortunes are resting on these networks. While ensuring network availability and performance has never been more critical, it has also never been more difficult. Network operations continue to grow in size and complexity, with traditional networks running alongside emerging mobile and fixed networks, including software-defined infrastructures, 5G, and more. Further, the volume of traffic, devices, and device types continues to expand, with innovations in IoT and virtual reality poised to introduce ever more explosive growth.

These growing, modern networks create complexity and overwhelming scale. Teams have to contend with massive volumes of operational data, leaving operators bracing for a Tsunami of metrics that have to be tracked, aggregated, analyzed, and acted upon. Ultimately, these volumes surpass any human’s ability to keep pace. Therefore, while network performance grows ever more critical, networks continue to get more susceptible to outages and performance issues than ever before.

Requirement: A New Approach to Network Operations

As they look to contend with these emerging requirements and challenges, network operations teams need to adopt a new approach. Toward that end, it will be critical to establish tight integration between network infrastructure and network monitoring software in order to gain the right context and intelligence. Teams will also need to establish unified visibility of the entire ecosystem, including new and traditional network implementations.

Perhaps most importantly, to keep up with growing volumes and more intelligently track, manage, and optimize networks, teams are realizing that they need to move away from a reliance solely on manual efforts, and start harnessing AI and machine learning.

In short, as Wall Street Journal reporter Sara Castellanosa recently wrote, companies are “finding that AI can identify and fix problems more quickly than humans.” Castellanosa’s article cites the example of Adobe. The software vendor instituted an AI-based program that automated around 30 tasks, including correcting data batching failures. The program has reduced the average time it takes to correct a failure from 30 minutes to three minutes.

With these kinds of results becoming possible, it’s no surprise that the move to AI-enabled networks is gaining momentum. The article quoted an IDC analyst as saying that AI-enabled networks will be mainstream at big companies in the next three to five years. The most critical objective? An IDC survey of 301 IT professionals found that 50% of respondents said the most important thing an AI-enabled network would do is improve application availability and performance.

How Broadcom Can Help

As network operations teams seek to establish AI-enabled networks, working with the right vendors and technologies will be crucial. This is one key reason why so many leading enterprises are turning to Broadcom. Broadcom is the top vendor of networking, storage, and computing connectivity technologies. As mentioned earlier, 100% of public clouds use Broadcom chipsets today, and 99.9% of internet traffic goes through our technology. Further, all the leading smartphone vendors, including Apple, Google, and Samsung, rely on Broadcom technology.

Broadcom delivers the market’s leading AIOps solution, which offers open and scalable data analytics. AIOps from Broadcom provides the key capabilities teams need to optimize modern environments:

  • Automation and predictive analytics, enabling the triggering of autonomous remediation so issues can be addressed before they have an impact on users or the business.
  • Full-stack observability, providing monitoring coverage of applications, infrastructure, and networks.
  • Service modeling, offering views that connect business services with all their underlying components.
  • Alarm noise reduction, eliminating the noise from the signal and helping IT speed mean time to resolution.
  • Application-centric network topology, mapping issues to associated business services, enabling more intelligent prioritization.

Combined, our chipsets and AIOps solution can deliver breakthrough capabilities. With these combined offerings, teams can do granular, packet-level network monitoring, leveraging in-band network telemetry to do real-time flow monitoring. AIOps from Broadcom can ingest rich packet-level network data from Trident chipsets. Now, Broadcom’s new Trident 4 switch series combined with our AIOps solution delivers AI-driven network triage and remediation. With these offerings, Broadcom is uniquely qualified to help organizations harness real-time analysis and correlation of network data, so over time teams can institute reliable, self-healing networks.

Conclusion

For today’s hyper-connected businesses, the establishment of AI-enabled, self-healing networks represents an increasingly vital mandate. For further insights, watch the below video.