This article is contributed. See the original author and article here.
In today’s fast-paced business world, embracing technology and prioritizing employee engagement are key to staying ahead. Sage, a global leader in payroll, HR and finance software, understands this well. Their partnership with Microsoft Viva Glint and Viva Insights is a compelling example of how utilizing a comprehensive employee listening strategy can drive business performance within organizations.
Delivering exceptional customer service and prioritizing engineering time is critical for Sage to stay ahead in a competitive market. Sage addressed challenges to retention and productivity by understanding the voice of the employee and meeting patterns. With this knowledge in hand, leaders at Sage were able to address root causes and improve retention by 30% in their customer service department, improve engineering productivity by 10% by reducing unnecessary meetings and improve customer service performance by 10%.
Take a look at the full customer story here and video highlights below.
This article is contributed. See the original author and article here.
Six months ago, we introduced Microsoft Dynamics 365 Copilot, the world’s first AI Copilot natively built for customer relationship management (CRM) and enterprise resource planning (ERP) applications. Since then, more than 63,000 organizations have experienced Copilot features in Microsoft Dynamics 365 and Microsoft Power Platform first-hand, empowering marketing, sales, and customer service teams in new ways to improve experiences across the customer journey.
Copilot is designed to help people do their very best work—and we’re seeing real value to support this vision. Today, I’m excited to share the most widely used scenarios and performance metrics from employees at Microsoft and leading organizations using Copilot capabilities across the customer journey. These stories and insights showcase what’s possible when employees are assisted by AI in the flow of work—helping them to boost productivity, perform tasks more efficiently, and focus on what matters most.
Transforming customer experience in the age of AI
Sellers, service agents, and marketers share a common goal: developing exceptional customer experiences that ultimately impact the bottom line. In July, we introduced the next wave of Copilot and AI capabilities to deliver connected customer experiences—from within Microsoft Dynamics 365 Sales and Microsoft Dynamics 365 Customer Insights, all the way through to the customer interactions in Outlook and Microsoft Teams powered by Microsoft Sales Copilot. With Dynamics 365 Copilot and Microsoft Sales Copilot, marketers can use everyday language to create relevant and targeted campaigns and brainstorm creative copy; sellers can move from one customer call and email to the next with relevant context on the opportunity at their fingertips; and service agents can become super agents with the help of AI to serve up relevant information to close customer cases more quickly.
Assisted by Dynamics 365 Copilot, Microsoft Support team resolves more cases faster, with less effort
At Microsoft, we’re also leading our own AI-first transformation and, since April, have been using Copilot capabilities in Microsoft Dynamics 365 Customer Service within our Customer Service and Support (CSS) team—one of the largest customer service organizations in the world. Today, we can share how Copilot has impacted the way agents work to resolve support cases, and the impact on their efficiency and productivity.
Microsoft’s Office of the Chief Economist, in partnership with the Dynamics 365 product group, evaluated how Copilot in Dynamics 365 Customer Service has impacted agent productivity since April. The initial results shared here reflect those of 11.5K agents, with 6.5K agents who used Copilot and the control group of 5K agents who did not use Copilot.
The findings demonstrate how Copilot can support agents of all experience levels in their workflows to increase efficiency and quality of customer engagements. Key results included:
Expedited agent onboarding. High turnover rates are common for service teams across industries, placing a burden on organizations to onboard new agents to be productive quickly. Copilot has been particularly effective in helping newer agents who don’t have years of experience or institutional experience get up to speed and find relevant information more quickly, the study found. Specifically, for low-severity chat cases in one area of our commercial support business, we observed a 12 percent reduction in average handle time—the time actively spent on resolving a customer case.
More cases resolved faster—without peer assistance. In the most productive scenario, the study found that in one support business, 10 percent of cases that normally require collaboration with peers were resolved independently. This means fewer customers had to experience being put on hold.
Direct feedback from Microsoft Support agents reveals how Copilot improves interactions with customers:
“Just wanted to share my gratitude to Copilot as a person who always struggles to wrap up wording before sharing with the customer—amazing time and pain saver for me!”
“[A] customer switched language mid-chat from English to Spanish. Copilot enabled me to continue to solve the problem regardless of the language shift.”
“I used Copilot to help a customer and got CSAT [customer satisfaction score] 5 out of 5. Their feedback was, ‘Very informative and to the point.’”
While the study captures just the first few months of AI-assisted service within the Microsoft Support organization, the results should encourage other organizations looking to optimize service operations with AI. The findings offer a glimpse of efficiencies and productivity gains that other organizations might experience when using Copilot. Read more details about the Microsoft Support team’s experience with Copilot on Microsoft Source. For the full story and video testimonial about the team’s transformation journey, check out the case study.
In addition to performance metrics, Microsoft employees provide feedback to the development team, helping to ensure every new capability provides the best possible benefit for users. This step is crucial as we roll out new features across Dynamics 365 Copilot—including a feature available today. Copilot summarization, now generally available, helps agents to quickly review the details of a case without sifting through notes, chat transcripts, and emails. This feature generates automatic conversation summaries, helping service agents to quickly understand highlights of a case—such as key customer problems and steps that agents took to resolve the case.
The Copilot summarization feature joins a host of upcoming Copilot capabilities for service teams, from the call center to field service professionals. View the release plans for Dynamics 365 Customer Service and Microsoft Dynamics 365 Field Service for details.
Service organizations expect Copilot to help deliver new levels of agent productivity and customer experiences
In addition to the early results from the Microsoft Support team, we’re hearing directly from leading organizations getting an early start with Copilot in Dynamics 365 Customer Service.
Prada Group, a global leader in luxury brands, is using Copilot to improve experiences for its discerning customers. “We’re excited to be one of the early adopters of the new Dynamics 365 Copilot AI tool,” shared Francesco De Giampaulis, Global Client Service & e-Commerce Payment Gateways and Anti-Fraud Manager, Prada Group. “By integrating it with our Knowledge Base and other internal sources, Copilot will assist our Client Service Advisors speeding up the onboarding process, offering a fast and smooth assistance to our customers, saving time searching for answers and focusing on providing a great experience, including suggestions for the right product or look.”
One of the leading investment management and advisory services, Vanguard Group, shared its initial experiences with Copilot. “Vanguard is utilizing Dynamics 365 Customer Service to support its agents in client service and knowledge management scenarios, as well as a custom bot to manage customer inquiries via its website,” explained Grant Pharez, Microsoft Dynamics 365 Specialist at Vanguard. “We are seeing promising results in testing the generative AI capabilities in these applications to help our customer care teams and self-service customer applications deliver exceptional service.”
Sellers reach new levels of productivity with Microsoft Sales Copilot
Concurrent to the Microsoft Support team’s experience, Microsoft deployed Microsoft Sales Copilot (previously Viva Sales) to 10,000 sellers within its sales organization. Early results show that 85 percent of surveyed sellers report completing one or more tasks faster, and 70 percent claim that Microsoft Sales Copilot helps them improve productivity.
Organizations like Securitas, a leading provider of custom security and guarding solutions, are noting the ability for sellers to focus time on what matters most. “Opportunity summary in Microsoft Sales Copilot is a huge and important leap in our direction to save more time for our sales personnel,” said Philip Eklund, Vice President, Client Engagement Services, Securitas. “With this capability in the hands of our sellers, they can spend more time equipping organizations with best-in-class security solutions to help make our world a safer place.”
Sellers using Microsoft Sales Copilot benefit from AI capabilities that help streamline the workday. Features slated for general availability in September and October include AI-generated preparation notes for customer conversations and opportunity and lead summaries. In addition, Microsoft Sales Copilot improves teamwork and knowledge sharing, providing sellers with collaboration spaces in Teams that integrate with CRM data and contact cards that surface CRM records directly in Microsoft 365 apps. View the release notes for Dynamics 365 Sales and Microsoft Sales Copilot for details. Get the e-book, “The AI Advantage: Driving Sales Performance with Next-Generation Tools”, which details how AI supports sales teams throughout the day.
Marketers surface deeper insights, optimize customer journeys with Copilot
Like sales and service professionals, marketing teams using Copilot in Dynamics 365 Customer Insights report tangible business benefits. TTEC Digital, a global customer experience (CX) technology and services company and Microsoft Gold Partner, shared how Copilot democratizes marketing tasks. According to Karl Phenix, VP at TTEC Digital, “Copilot in Customer Insights makes marketing employees more comfortable in doing complex tasks such as segmentation, which previously required specialists such as data scientists.” Karl added that “Copilot frees up time by generating emails in minutes, so marketing employees can do more to drive sales activities and accelerate the pipeline.”
Copilot features now generally available help marketers to deliver a consistent brand narrative and customer experience. Marketers can craft email content by prompting Copilot to curate content, change the tone and voice, or adjust the length of the copy. Available in preview, marketers can also create customer journeys simply by describing actions at each step, such as: “When a contact registers for an event, send a thank you email.” In fact, 59 percent of Dynamics 365 Customer Insights customers* have used Copilot when creating segments and 36 percent of customers used Copilot to ask questions to uncover customer and business insights. View the release notes for more details.
Start transforming customer experiences with Dynamics 365
Dynamics 365 is a complete suite of CRM and ERP applications that helps you manage your businesses across sales, marketing, service, finance, and supply chain.
Dynamics 365 Copilot is the world’s first AI copilot integrated into CRM and ERP applications in the cloud. Unlike other solutions, generative AI features are included in Dynamics 365 subscriptions for enterprise customers at no additional charge.
View the Dynamics 365 licensing guide to choose options that suit your business, and contact your Microsoft representative to learn more about the value and return on investments, as well as the latest offers—including a limited-time 26 percent savings on subscription pricing for Dynamics 365 Sales Premium.
If you are a Dynamics 365 customer, use Copilot capabilities today. Visit the Dynamics 365 release planner to view features coming soon and available to try now.
Copilot in Dynamics 365 and Power Platform
Copilot features are empowering marketing, sales, and customer service teams in new ways.
This article is contributed. See the original author and article here.
Global retailers, manufacturers, and distributors continue to face the new normal of doing business today: economic volatility, unpredictable customer spending, and operational complexities. As we gear up for the holiday season, businesses that are agile and responsive will be poised to capture market demand and deliver an exceptional end-to-end customer experience. Adopting modern technology solutions can introduce agility to key processes overnight, and leaders should look across their supply chain functions to identify levers for maximum impact.
Supply chain technology leaders recognize that competitiveness—and in some cases, an organization’s survival—demands digital parity, if not leadership, so they now openly embrace exploratory IT investments.1
One of those levers is warehouse management, a market that IDC reports grew at a compound annual rate of 14 percent in 2023.2 By embracing modern, robotic, and AI-enhanced warehouse management solutions (WMS), organizations can drive meaningful results across the business in a relatively quick time-to-value.
In this post, we’ll explore why warehouse management solutions are needed and how Microsoft and Dynamics 365 enable customers to navigate ongoing disruptions, optimize inventory levels, and deliver on time with ease.
Navigate supply chain uncertainties with technology
While the early days of the COVID-19 pandemic are behind us, retailers and operators are still navigating the new normal, which includes:
Growing labor constraints.
Demand volatility.
Multichannel distribution.
Storage capacity challenges.
Permeation of AI into core processes.
In the face of these challenges, there is an opportunity for businesses to embrace uncertainties with technology and maximize levers like distribution capacity, improved employee and warehouse productivity, and consistent operations during volatile times. Legacy enterprise resource planning (ERP) systems are often disjointed and lead to a delay in real-time insights and optimization.
What is a modern WMS?
A modern warehouse management system helps businesses manage and optimize key warehouse operations like inventory tracking and shipping coordination through an open and composable framework. It can integrate with multiple systems and platforms and helps support end-to-end business processes, from ERP to customer relationship management. For businesses that want to stay competitive in an ever-expanding fulfillment economy, a modern WMS meets those challenges with an agile, digitally connected solution that reduces costs through maximizing resources like employees, machinery and storage.2
Modern warehouse management solutions can help improve real-time visibility into inventory levels, provide the ability to automate and streamline operations, and drive greater efficiency across the organization.
Adopting a modern WMS can contribute to these outputs:
Reduced costs through improved inventory turns and optimized storage space.
Improved customer satisfaction via on-time and in-full delivery and improved fill rates.
Business growth and agility to meet unexpected customer demand and product development.
Automation and enhanced productivity to free up your employees’ time to focus on what’s next.
The benefits of a modern WMS
1. Reduced costs
Golden State Foods (GSF) is an industry leader that produces liquid products like sauces, dressings, and condiments for customers like McDonald’s and Chick-fil-A. With a 25 year-old legacy ERP system, GSF chose Dynamics 365 ERP solution’s Supply Chain Management and Finance to help create a modern, common platform with centralized reporting and more standardized processes to facilitate opening a new plant.
“We chose Dynamics 365 because we need modern technology that will evolve with us.”
–Carol Fawcett: Corporate Vice President and Chief Information Officer, GSF
With Dynamics 365 Supply Chain Management, GSF’s warehouse management processes were completely modernized. Dynamics 365 is being used to receive, put away, and consume inventory for production; report inventory as finished; store it in finished goods warehouses; and select it for shipment for customer orders. It prints standard barcode labels that are used at customers’ distribution centers for fast and accurate traceability—a considerable improvement from previous processes. This end-to-end visibility helps GSF operations managers improve inventory turns and make better decisions about production restraints and forecasting. With improved forecasting, GSF can reduce waste, optimize inventory, and increase its efficiency across its plants.
2. Improved customer satisfaction
Bedrosians Tile & Stone is one of the largest porcelain tile and stone importers and distributors in the United States, with 40 retail locations worldwide. It’s 30 year-old legacy ERP system impacted demand planning and forecasting, which was critical for Bedrosians’ massive 10,000-item inventory. Without accurate demand planning and forecasting, Bedrosians was reactive and vulnerable to market whims.
Like many retailers, Bedrosians saw customer demand skyrocket during the COVID-19 pandemic. Annual spending on home improvements grew, but without accurate demand forecasting, Bedrosians struggled to find that “just right” inventory on hand formula, often finding itself understocked or overstocked. With lead times as long as six months or more, the need to have accurate inventory levels—and visibility into them—couldn’t be more important.
Bedrosians’ legacy ERP impacted its ability to optimize inventory placement and as such, the company was at risk of promising products they couldn’t deliver or losing sales opportunities while inventory was in transit. Bedrosians chose Dynamics 365 ERP solutions to help optimize financial, inventory, purchasing, and planning capabilities to better streamline the movement of their globally sourced inventory. What used to be a manual guessing game has turned into an automated, scientific forecast based on historical data and industry trends. This ensures Bedrosians can capitalize on sales opportunities, despite months-long lead times, and deliver an on-time and in-full customer experience.
“Implementing Dynamics 365 has been a game-changer for our business. It has improved our operation and financial management. Real-time visibility, optimized procurement, and streamlined order processing has resulted in increased sales, improved margins, and a more efficient supply chain and positioned us for sustained growth in a competitive market.”
–Nirbhay Gupta: CIO, Bedrosians Tile & Stone
3. Business growth and agility
Barnas Hus is Norway’s leading children and baby products retailer, with both e-commerce and 28 physical stores. Working with a Microsoft partner, KPMG, Barnas Hus set out to face its supply chain challenges that were hindering its business growth, such as lack of visibility and inconsistent accuracy in its legacy ERP system. Barnas Hus embraced a modern, cloud-powered platform enabled by Dynamics 365. This technology-focused improvement helped the company transform its warehouse management, inventory control, production planning, and more—setting Barnas Hus up to meet growing customer demand.
Once they had made the shift, Barnas Hus opened a new state-of-the-art warehouse that utilizes autonomous robotics to accurately pick, sustainably pack, and trace every product. The modern warehouse management system improved inventory visibility and freed up employees to spend time with customers. The best part? The ease of implementation led to a quick time to demonstrate value and Barnas Hus saw its biggest month ever in revenue.
Michael Hill is a leading jeweler based in Australia with operations in New Zealand, Canada, and the United States. When the pandemic hit, its 300 stores were facing temporary closures and the company confronted logistic complications that forced expensive, indirect, and inefficient shipments to its customers worldwide. Michael Hill’s legacy ERP system was inflexible and lacked visibility and accuracy.
The international jeweler moved quickly to avoid harm to its business and its brand. It rapidly deployed Dynamics 365 and almost immediately began providing increased visibility into inventory availability across its supply chain. This gave Michael Hill the ability to treat each of its stores as a warehouse location, which seamlessly allowed customers to order items online with the option to pick up at the site of their choice or ship direct from that location. It also vastly reduced the manual labor previously required from Michael Hill employees to ensure fulfillment.
“We use the ship-from-store capability in Dynamics 365 to fulfill demand from many locations, rather than requiring human intervention whenever stock is transferred. That helps us reduce how many hops it takes to put a piece into the hands of the customers, and that’s our end game—a better experience.”
–Matt Keays: Chief Information Officer, Michael Hill
By implementing Dynamics 365 as its warehouse management system, Michael Hill was able to deliver agile flow solutions that freed up its employees to focus on more strategic initiatives such as loyalty programs and trialing new fulfillment models.
Learn more about Dynamics 365 solutions
To compete and thrive in market conditions today, organizations should look to adopt modern warehouse management solutions to better prepare for uncertainty, increased demand, and disruptive conditions. While legacy ERP systems are complex, Microsoft partners and Dynamics 365 solutions provide quick time-to-value and provide the agility and automation required for growth.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and HYPE CYCLE is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
This article is contributed. See the original author and article here.
Today, we are excited to announce the general availability of Conditional Access overview dashboard and templates. Conditional Access protects thousands of organizations across the globe daily and customers often ask us about best practices and how to improve security coverage. Conditional Access overview dashboard and templates empower Microsoft Entra ID customers to gain insights into their security posture, assess the impact of individual policies, and simplify deployment of Microsoft’s recommendations.
I’ve invited Krishna Venkit and Lisa Huang-North, product managers on the Identity Security team to share more details about these two features.
Best Regards,
Nitika Gupta
Group Product Manager, Identity Security
Microsoft Identity Division
————————————————————
Hi everyone!
The Conditional Access overview is a built-in dashboard that offers a comprehensive view of your Conditional Access posture. As an administrator, it provides a concise summary of your policies,identifies any gaps in your policy coverage, and provides valuable insights based on sign-in activity within your tenant. This feature enables you to swiftly pinpoint areas where you can enhance the enforcement of Zero Trust principles, ultimately bolstering your defense mechanisms.
Figure 1 Conditional Access overview
The dashboard is now the default landing page of Conditional Access. As the first entry point into Conditional Access, the overview page lets you quickly create new policies using one of the Conditional Access templates which capture commonly used policies and best practices.
The dashboard also offers the following insights and reporting capabilities:
The “See all unprotected sign-ins” link under the Users tile helps you rapidly identify users that are signing in without the protections of a Conditional Access policy.
Figure 2 Sign-ins without CA coverage during the last 7 days
The ‘See all non-compliant devices’ and ‘See all unmanaged devices’ links under the Devices tile help you identify device compliance gaps.
Figure 3 Non-compliant devices
You can discover the top 10 most accessed apps without Conditional Access coverage using the coverage tab and go one step further and identify the users without coverage for that app by clicking on the numbers in the ‘Users without coverage’ column.
Figure 4: Top accessed applications without CA coverage
You can discover security alerts generated based on sign-in activity in your tenant and take quick action on the alerts by deploying recommended zero trust conditional access policies using the Conditional Access templates. Speaking of which, let’s take a brief walkthrough of Conditional Access templates.
Conditional Access templates are a pre-defined set of conditions and controls that provide a convenient method to deploy new policies aligned with Microsoft recommendations. Customers are assured that their policies reflect modern best practices for securing corporate assets, promoting secure, optimal access for their hybrid workforce.
Conditional Access templates are organized across five scenarios:
Secure foundation
Zero Trust
Remote work
Protect administrators
Emerging threats
Organizations can choose from 16 predefined Conditional Access templates based on their specific needs. Here is an example!
With the “Require phishing-resistant multifactor authentication for admins” Conditional Access template, customers can reduce the risk of compromise and phishing attacks on privileged users. This powerful template usesConditional Access authentication strengths to help you choose the right authentication method requirements for specific scenarios, making it easier than ever for organizations to move their most critical users towards more secure, modern, and strong authentication.
This article is contributed. See the original author and article here.
This post is authored by Gerry Murray, Marketing and Sales Technology Research Director, IDC; and coauthored by Carlena Neely, Product Marketing Manager, Business Applications, Microsoft.
Dynamics 365 AI
Learn about the latest AI breakthroughs with Microsoft Sales Copilot.
Delving into the realm of customer-centric strategies, IDC analyst Gerry Murray casts a visionary light on the transformative influence of generative AI (Gen AI) on sales and service. Murray’s perspective resonates powerfully with the groundbreaking nature of Gen AI, which is reshaping customer interactions into a new era of efficiency and effectiveness.
Gen AI isn’t just another technology; it’s a strategic leap that orchestrates seamless data and workflows across marketing, sales, and service touchpoints. Gerry Murray emphasizes its potential to eliminate mundane tasks, such as drafting emails and preparing for meetings, while providing real-time support during crucial interactions. It is also extremely exciting to have covered the addition of Microsoft Sales Copilot, providing a more streamlined and AI-powered selling experience.
The true potential of Gen AI infused in tools such as Microsoft Sales Copilot unfolds when it seamlessly integrates with other applications such as CRM systems, Microsoft 365, and Microsoft Teams, presenting a harmony that minimizes risks while maximizing benefits. This strategic synergy aligns with industry best practices and fosters an environment of innovation.
Gen AI transcends the realm of ordinary tools; it’s an enabler propelling business toward an era of seamless experiences and unparalleled efficiency.
AI-powered customer and seller experiences
Customers have extremely high expectations for a vendor’s ability to personalize everything about their experiences pre- and post-sale. Consumers expect each touchpoint in their journey to be informed and enhanced by all the previous touchpoints. Business buyers have the same expectations, but they take much more work on the part of sellers to fulfill as everything about the B2B sales process is far more complex than B2C. In both cases, the days of relying on customers to continually explain the context of their situation to the next point of contact are over.
To achieve today’s new level of continuity, the data from every touchpoint needs to be available to every other system within brand and regulatory policy. Giving all customer-facing functions equal insights into behaviors such as social sentiment, sales engagement, purchase histories, late payments, product returns, and support consumption can greatly improve business performance across the board. That improvement requires the underlying infrastructure supporting front-office applications to enable the customer’s data to be available to service them wherever they go next, which is a daunting challenge for large enterprises with fragmented data silos.
Generative AI (Gen AI) for front office applications can manage the data and workflow triggers between customer interactions across marketing, sales, and service enabling these employees to be more helpful faster, which in turn raises customer satisfaction, advocacy, and lifetime value.
Generative AI for sales
AI-powered role-based assistants can help sales reps increase productivity and personalize every customer interaction so they can close more deals. Gen AI can be present in the tools sellers use daily such as Outlook, Microsoft Teams, or Microsoft Dynamics 365 Sales, and connects to other CRM systems. AI alleviates the tedium and time sinks of endless click loops through menus, drop downs, pick lists, and check boxes. The impact on employee experience will be significant as AI will enable sellers to:
Get auto-generated opportunity summaries including status, progress, and highlights of key changes.
Create contextual emails that utilize customer CRM data to pull in product, customer, and opportunity information.
Prepare for customer meetings with a summary view including account information, recent notes, highlights of any issues or concerns, customer news, and more.
Get real-time tips and suggested answers during video meetings prompted by competitor or brand mentions by the customers to stay ready to handle objections.
Augmenting the front office with insight
But AI in and of itself is not enough, as it requires a great deal of data. To help organizations increase the speed of acting on customer insights and orchestrating personalized customer journeys, data infrastructure must offer both customer data platform and customer journey orchestration capabilities as a single solution and continue investments into real-time marketing.
The most effective way to optimize the benefits of AI and minimize the risks at the same time is to put AI in the context of other applications. This approach makes AI effective at completing repetitive tasks for customer-facing employees in marketing, sales, commerce, merchandising, point of sale, customer service and support, call center, loyalty, and so forth, all functions in which decision quality and cycle time are essential to customer satisfaction. Microsoft Dynamics 365 Copilot can eliminate repetitive tasks such as:
Drafting messages and project plans.
Scheduling and summarizing sales calls.
Creating, testing, and fine-tuning audience segments.
Matching brand guidelines for emails, forms, and event registration pages using natural language to deliver a consistent brand narrative and customer experience.
Orchestrating customer journeys across marketing, sales, and service, so customer actions can be responded to appropriately and quickly, generating sales leads or increasing customer satisfaction.
AI significantly impacts customer-facing employees, improving their experience and enabling them to focus on higher-value tasks. It accelerates decision-making, improves productivity, and enhances the coordination of interactions with customers across various touchpoints.
Enhancing business efficiency
Gen AI is new and evolving at warp speed. IDC expects there to be a great deal of innovation in terms of future capabilities and a wide range of use cases across multiple front-office functions. Examples of how Gen AI can enhance work processes for sales and marketing include:
Additional sales use cases for Gen AI could include request for proposal (RFP) creation and response, upselling recommendations, price optimization, contract generation and review, account planning, territory optimization, and more.
In marketing, Gen AI can describe their customer segment in their own words to create a target segment with the query assist feature. Marketers can also use Gen AI to get inspiration for email campaign content based on a simple request. Gen AI can make suggestions based on key topics entered by the marketer and the organization’s existing marketing emails, as well as from a range of internet sources to increase the relevance of generated ideas. Additional use cases could include fine-tuned segmentation, send time optimization, content generation, testing and optimization, attribution, media mix modeling, and more.
IDC conclusion
Gen AI is one of the most significant technological advances of the last decade, it is as much of a quantum leap as the graphical user interface, the Internet, and smartphones. Gen AI is a major advancement for line-of-business people who can now explain what they want to do to an AI assistant instead of having to learn how to do it in a graphical user interface (GUI) that might involve hundreds of mouse clicks on menu calls, dialog boxes, drop downs, radio buttons, application switching, and so forth.
Learn more about the latest AI breakthroughs with Microsoft Sales Copilot on the Dynamics 365 AI webpage.
This article is contributed. See the original author and article here.
Utilizando Log Analytics para monitorar logs de auditoria do Azure RedHat OpenShift
Introdução
Por padrão, os clusters Azure Red Hat OpenShift possuem uma forma de monitorar os logs de auditoria através do OpenShift Logging, que envolve a instalação do OpenShift Elasticsearch Operator e OpenShift Cluster Logging. Embora essa solução seja eficiente, ela não permite a integração com o Azure Monitor, a solução de monitoramento da Microsoft, nem a centralização dos logs de auditoria de diversos clusters em um único local.
Para demonstrarmos uma solução personalizada, é necessário possuir um cluster Azure Red Hat OpenShift. Caso você não possua um cluster, é possível seguir o tutorial Criando um cluster Azure Red Hat OpenShift e lembre-se de utilizar a opção do pull secret para baixar as imagens da RedHat Pull Secret
Fluent Bit é um sistema de coleta e encaminhamento de registros e logs (logs de eventos e mensagens) desenvolvido como parte do ecossistema Fluentd. É uma solução leve e eficiente projetada para coletar, filtrar e encaminhar logs em ambientes distribuídos.
Azure Red Hat OpenShift
Após a criação do cluster, vamos analisar as pastas que estão os logs de auditoria do cluster.
Faça o login no cluster, você pode pegar o endereço do cluster no portal do Azure, na aba Overview do cluster criado e clicando no botão Connect
Clique na URL e utilize o username kubeadmin como user e o password como senha.
Instalando o Fluent Bit no cluster
Para fazer a instalação no Azure Red Hat OpenShift, precisamos setar o security context constraints (SCC), para isso você precisa estar logado via cli e ter um usuário com permissão de cluster-admin.
Por padrão a instalação do Fluent Bit os DaemonSets são instalados somente nos workers nodes, mas para ter acesso aos logs de auditoria, precisamos fazer a instalação somente no master node, para isso, vamos criar um arquivo chamado values.yaml com o seguinte conteúdo:
# kind — DaemonSet or Deployment
kind: DaemonSet
# replicaCount — Only applicable if kind=Deployment
replicaCount: 1
image:
repository: cr.fluentbit.io/fluent/fluent-bit
# Overrides the image tag whose default is {{ .Chart.AppVersion }}
tag: “latest-debug”
pullPolicy: Always
# Configure podsecuritypolicy
# Ref: https://kubernetes.io/docs/concepts/policy/pod-security-policy/
# from Kubernetes 1.25, PSP is deprecated
# See: https://kubernetes.io/blog/2022/08/23/kubernetes-v1-25-release/#pod-security-changes
# We automatically disable PSP if Kubernetes version is 1.25 or higher
podSecurityPolicy:
create: false
annotations: {}
openShift:
# Sets Openshift support
enabled: true
# Creates SCC for Fluent-bit when Openshift support is enabled
securityContextConstraints:
create: true
annotations: {}
resources: {}
# limits:
# cpu: 100m
# memory: 128Mi
# requests:
# cpu: 100m
# memory: 128Mi
## only available if kind is Deployment
ingress:
enabled: false
className: “”
annotations: {}
# kubernetes.io/ingress.class: nginx
# kubernetes.io/tls-acme: “true”
hosts: []
# – host: fluent-bit.example.tld
extraHosts: []
# – host: fluent-bit-extra.example.tld
## specify extraPort number
# port: 5170
tls: []
# – secretName: fluent-bit-example-tld
# hosts:
# – fluent-bit.example.tld
## only available if kind is Deployment
autoscaling:
vpa:
enabled: false
annotations: {}
# List of resources that the vertical pod autoscaler can control. Defaults to cpu and memory
controlledResources: []
# Define the max allowed resources for the pod
maxAllowed: {}
# cpu: 200m
# memory: 100Mi
# Define the min allowed resources for the pod
minAllowed: {}
# cpu: 200m
# memory: 100Mi
updatePolicy:
# Specifies whether recommended updates are applied when a Pod is started and whether recommended updates
# are applied during the life of a Pod. Possible values are “Off”, “Initial”, “Recreate”, and “Auto”.
updateMode: Auto
## How long (in seconds) a pods needs to be stable before progressing the deployment
##
minReadySeconds:
## How long (in seconds) a pod may take to exit (useful with lifecycle hooks to ensure lb deregistration is done)
##
terminationGracePeriodSeconds:
priorityClassName: “”
env: []
# – name: FOO
# value: “bar”
# The envWithTpl array below has the same usage as “env”, but is using the tpl function to support templatable string.
# This can be useful when you want to pass dynamic values to the Chart using the helm argument “–set =”
# https://helm.sh/docs/howto/charts_tips_and_tricks/#using-the-tpl-function
envWithTpl: []
# – name: FOO_2
# value: “{{ .Values.foo2 }}”
#
# foo2: bar2
## https://docs.fluentbit.io/manual/administration/configuring-fluent-bit/classic-mode/configuration-file
config:
service: |
[SERVICE]
Daemon Off
Flush {{ .Values.flush }}
Log_Level {{ .Values.logLevel }}
Parsers_File parsers.conf
Parsers_File custom_parsers.conf
HTTP_Server On
HTTP_Listen 0.0.0.0
HTTP_Port {{ .Values.metricsPort }}
Health_Check On
## https://docs.fluentbit.io/manual/pipeline/inputs
inputs: |
[INPUT]
Name tail
Path /var/log/kube-apiserver/*.log
multiline.parser docker, cri
Tag audit.kube-apiserver.*
DB /tmp/kube_apiserver.db
Mem_Buf_Limit 50MB
Refresh_Interval 10
Skip_Empty_Lines On
Buffer_Chunk_Size 5M
Buffer_Max_Size 50M
Skip_Long_Lines Off
[INPUT]
Name tail
Path /var/log/openshift-apiserver/*.log
multiline.parser docker, cri
Tag audit.openshift-apiserver.*
DB /tmp/openshift-apiserver.db
Mem_Buf_Limit 50MB
Refresh_Interval 10
Skip_Empty_Lines On
Buffer_Chunk_Size 5M
Buffer_Max_Size 50M
Skip_Long_Lines Off
[INPUT]
Name tail
Path /var/log/oauth-apiserver/*.log
multiline.parser docker, cri
Tag audit.oauth-apiserver.*
DB /tmp/oauth-apiserver.db
Mem_Buf_Limit 50MB
Refresh_Interval 10
Skip_Empty_Lines On
Buffer_Chunk_Size 5M
Buffer_Max_Size 50M
Skip_Long_Lines Off
## https://docs.fluentbit.io/manual/pipeline/filters
filters: |
[FILTER]
Name kubernetes
Match kube.*
Merge_Log On
Keep_Log Off
K8S-Logging.Parser On
K8S-Logging.Exclude On
## https://docs.fluentbit.io/manual/pipeline/outputs
outputs: |
[OUTPUT]
Name stdout
Match *
## https://docs.fluentbit.io/manual/administration/configuring-fluent-bit/classic-mode/upstream-servers
## This configuration is deprecated, please use `extraFiles` instead.
upstream: {}
## https://docs.fluentbit.io/manual/pipeline/parsers
customParsers: |
[PARSER]
Name docker_no_time
Format json
Time_Keep Off
Time_Key time
Time_Format %Y-%m-%dT%H:%M:%S.%L
# This allows adding more files with arbitary filenames to /fluent-bit/etc by providing key/value pairs.
# The key becomes the filename, the value becomes the file content.
extraFiles: {}
# upstream.conf: |
# [UPSTREAM]
# upstream1
#
# [NODE]
# name node-1
# host 127.0.0.1
# port 43000
# example.conf: |
# [OUTPUT]
# Name example
# Match foo.*
# Host bar
# The config volume is mounted by default, either to the existingConfigMap value, or the default of “fluent-bit.fullname”
volumeMounts:
– name: config
mountPath: /fluent-bit/etc/fluent-bit.conf
subPath: fluent-bit.conf
– name: config
mountPath: /fluent-bit/etc/custom_parsers.conf
subPath: custom_parsers.conf
Se desejar comparar o arquivo que está sendo criado com o arquivo oficial do Fluent Bit, você pode acessar o repositório do Fluent Bit, o arquivo yaml acima também tem a configuração para as pastas abaixo de logs do Azure Red Hat OpenShift que usam a tag [INPUT].
/var/log/kube-apiserver
/var/log/openshift-apiserver
/var/log/oauth-apiserver
Nessa configuração acima estão também estamos usando a imagem com a tag “latest-debug”, com essa tag é possível ver os logs do Fluent Bit no console do pod após a instalação do Fluent Bit no cluster, para isso basta executar o comando abaixo:
ls /var/log/kube-apiserver
ls /var/log/openshift-apiserver
ls /var/log/oauth-apiserver
Para realizar a instalação, esteja na mesma pasta em que o arquivo values.yaml foi criado e execute o comando abaixo.
Logo após instalado, vá ao dashboard do seu cluster, selecione workloads e pods na aba lateral e selecione o project como logging, você deve ter a mesma quantidade de pods que o cluster tem de worker nodes, no meu caso são três workers nodes.
Com a configuração atual estamos somente lendo os arquivos de logs e mostrando no terminal.
Criando um Log Analytics workspace
Para enviarmos os logs para o Azure Monitor precisamos criar um Log Analytics workspace, para isso acesse siga os passos
Após a criação do Log Analytics workspace e acesse o mesmo e na menu lateral nos settings clique no Agents.
Salve o Workspace ID e o Primary Key, pois vamos usar os mesmo para a nova configuração.
Agora precisamos adicionar mais um output na configuração do ConfigMap do Fluent Bit.
Vá no ConfigMap(fluent-bit) e adicione o output abaixo no final do arquivo e clique no salvar.
Após criar a secret você pode verificar a mesma rodando o comando abaixo.
kubectl get secret fluentbit-secret -n logging
Agora precisamos adicionar secret no DaemonSet, para isso vá no menu lateral e selecione DaemonSets e clique no fluent-bit e selecione Enviroments
Clique no Add from ConfigMap or Secret
Adicione as environments SharedKey e WorkspaceId e no Select a resource , selecione o Secret que foi criado anteriormente fluent-bit-secret, deixe igual a imagem abaixo e clique no save.
Para que a nova configuração seja aplicada, é necessário excluir os Pods atuais; execute o comando abaixo.
Após deletar os pods, você pode verificar que os novos pods já estão sendo criados com a nova configuração, para isso execute o comando abaixo.
kubectl get pods -l app.kubernetes.io/instance=fluent-bit -n logging
# Utilize o nome do primeiro de pod que aparecer e execute o comando abaixo para ver os logs do pod.
kubectl logs fluent-bit-xxxx -n logging | grep “customer_id=”
Vai mostrar os logs como abaixo, mostrando que o output para o Log Analytics workspace a foi enviado com sucesso.
Vizualizando os logs de auditoria no Log Analytics workspace
Entre no portal da azure, busque na barra de pesquisa do Log Analytics workspace e na lista selecione o Log Analytics workspace que foi criado nos passos anteriores.
No menu lateral selecione logs como na imagem abaixo.
Vai abrir uma tela de queries e feche a mesma.
Em tables, abra custom logs e deve ter uma tabela com no nome AuditOpenshift_CL
Vá no campo e coloque o comando abaixo e clique no Run
AuditOpenshift_CL |
take 100
Após rodar o comando, irá mostrar todos os logs de auditoria que estão sendo enviados para o Log Analytics workspace
Conclusão
Em resumo, o Fluent Bit é uma ferramenta poderosa para coletar e enviar logs para o Log Analytics Workspace da Azure. Com a configuração correta, você pode coletar logs de vários serviços e aplicativos em execução em seu cluster Kubernetes(OpenShift) e enviá-los para o Log Analytics Workspace para análise e monitoramento. Além disso, o Fluent Bit é altamente configurável e pode ser personalizado para atender às suas necessidades específicas. Esperamos que este guia tenha sido útil para você começar a usar o Fluent Bit em seu ambiente Kubernetes(OpenShift).
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