The document discusses how observability is becoming a core competency for organizations as digital environments grow more complex. It predicts that observability will be the new face of digital transformation, with a focus on digital experience. Additionally, it predicts that IT spending will need to deliver clear value in 2023's uncertain economic environment. Finally, it predicts that as observability becomes standard, automation will be the next differentiator for organizations, enabled by improvements in machine learning and the need to address talent shortages and cost pressures.
The document appears to be a presentation by Splunk Inc. discussing their data platform. Some key points:
1. Splunk's platform allows customers to investigate, monitor, analyze and act on data from any source in real-time.
2. It addresses challenges of collecting and making sense of massive amounts of data from various systems and devices across IT, security, and IoT use cases.
3. Splunk provides solutions and services to help customers accelerate their data journey from initial investigation to taking action.
How deeply can you understand what is happening inside your application? In modern, microservices-based applications, it’s critical to have end-to-end observability of each component and the communications between them in order to quickly identify and debug issues. In this session, we show how to have the necessary instrumentation and how to use the data you collect to have a better grasp of your production environment. On AWS, CloudWatch collects monitoring and operational data in the form of logs, metrics, and events, providing you with a unified view of AWS resources, applications, and services. With AWS X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. AWS App Mesh standardizes how your microservices communicate, giving you end-to-end visibility and helping to ensure high-availability for your applications.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
The document discusses observability for modern applications. It describes observability as a measure of how well internal states of a system can be inferred from external outputs. It outlines three pillars of observability: event logs, metrics, and tracing. It provides examples of how AWS services like CloudWatch, CloudWatch Logs, and AWS X-Ray can be used to gain observability. It also discusses key concepts like segments, subsegments, and service maps for tracing and provides code examples for instrumenting applications to generate metrics and traces.
Do You Really Need to Evolve From Monitoring to Observability?Splunk
The document discusses the concepts of monitoring and observability. It defines observability as focusing on what can't be seen or the unknowns in a system. Observability provides visibility into the state of applications, systems, and services through logs, metrics, and traces to understand problems and take actions. The document then summarizes SignalFx's approach to observability, which combines metrics, traces, and logs in a streaming architecture to provide insights in seconds and help troubleshoot issues.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
How to Move from Monitoring to Observability, On-Premises and in a Multi-Clou...Splunk
With the acceleration of customer and business demands, site reliability engineers and IT Ops analysts now require operational visibility into their entire architecture, something that traditional APM tools, dev logging tools, and SRE tools aren’t equipped to provide. Observability enables you to inspect and understand your IT stack on premises and in the cloud(s); It’s no longer about whether your system works (monitoring), but being able to task why it is not working? (Observability). This presentation will outline key steps to take to move from monitoring to observability.
The document appears to be a presentation by Splunk Inc. discussing their data platform. Some key points:
1. Splunk's platform allows customers to investigate, monitor, analyze and act on data from any source in real-time.
2. It addresses challenges of collecting and making sense of massive amounts of data from various systems and devices across IT, security, and IoT use cases.
3. Splunk provides solutions and services to help customers accelerate their data journey from initial investigation to taking action.
How deeply can you understand what is happening inside your application? In modern, microservices-based applications, it’s critical to have end-to-end observability of each component and the communications between them in order to quickly identify and debug issues. In this session, we show how to have the necessary instrumentation and how to use the data you collect to have a better grasp of your production environment. On AWS, CloudWatch collects monitoring and operational data in the form of logs, metrics, and events, providing you with a unified view of AWS resources, applications, and services. With AWS X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. AWS App Mesh standardizes how your microservices communicate, giving you end-to-end visibility and helping to ensure high-availability for your applications.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
The document discusses observability for modern applications. It describes observability as a measure of how well internal states of a system can be inferred from external outputs. It outlines three pillars of observability: event logs, metrics, and tracing. It provides examples of how AWS services like CloudWatch, CloudWatch Logs, and AWS X-Ray can be used to gain observability. It also discusses key concepts like segments, subsegments, and service maps for tracing and provides code examples for instrumenting applications to generate metrics and traces.
Do You Really Need to Evolve From Monitoring to Observability?Splunk
The document discusses the concepts of monitoring and observability. It defines observability as focusing on what can't be seen or the unknowns in a system. Observability provides visibility into the state of applications, systems, and services through logs, metrics, and traces to understand problems and take actions. The document then summarizes SignalFx's approach to observability, which combines metrics, traces, and logs in a streaming architecture to provide insights in seconds and help troubleshoot issues.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
How to Move from Monitoring to Observability, On-Premises and in a Multi-Clou...Splunk
With the acceleration of customer and business demands, site reliability engineers and IT Ops analysts now require operational visibility into their entire architecture, something that traditional APM tools, dev logging tools, and SRE tools aren’t equipped to provide. Observability enables you to inspect and understand your IT stack on premises and in the cloud(s); It’s no longer about whether your system works (monitoring), but being able to task why it is not working? (Observability). This presentation will outline key steps to take to move from monitoring to observability.
This session was presented at the AWS Community Day in Munich (September 2023). It's for builders that heard the buzz about Generative AI but can’t quite grok it yet. Useful if you are eager to connect the dots on the Generative AI terminology and get a fast start for you to explore further and navigate the space. This session is largely product agnostic and meant to give you the fundamentals to get started.
Artificial intelligence is reshaping business, and the time is ripe for companies to capitalise AI. The organisation can use AI to move their focus from discrete business problems to significant business challenges.
An organisation should use ML and Data Science to drive digital transformation for more back-office operational efficiency, better user/engagement, smoother onboarding, and better ROI by lowering cost and bring more data-driven taking mechanism for transparency.
AI will be a valuable, transformational change agent not only to the way business is done but to the way people live their daily lives if it isn't perceived as a plug-and-play technology with immediate returns but more like a long term solution to rewire the organisation.
A journey into the business world of artificial intelligence. Explore at a high-level ongoing business experiments in creating new value.
* Review AI as a priority for value generation
* Explore ongoing experimentation
* Touch on how businesses are monetising AI
* Understand the intent of adoption by industries
* Discuss on the state of customer trust in AI
Part 1 of a 9 Part Research Series named "What matters in AI" published on https://www.andremuscat.com
A recent study revealed that digital leaders (the top 10 percent of
companies leading technology innovation) achieve 2–3x revenue
growth as compared to their competitors—a widening divide that Accenture calls the “Digital Achievement Gap.” upload by Shamayun Miah Management Consultant Accenture
Observability has emerged as one of the hottest topics on the DevOps landscape. Organizations seek to improve visibility into their cloud infrastructure and applications and identify production issues that may negatively impact #customerexperience.
➡️ But what are some of the best practices for scaling observability for modernapplications?
➡️ What challenges are #cloudplatforms facing?
Explore how to overcome the challenges and unlock speed, observability, and automation across your DevOps lifecycle.
More Than Monitoring: How Observability Takes You From Firefighting to Fire P...DevOps.com
For some, observability is just a hollow rebranding of monitoring, for others it’s monitoring on steroids. But what if we told you observability is the new way to find out why—not just if—your distributed system or application isn’t working as expected? Today, we see that traditional monitoring approaches can fall short if a system or application doesn’t adequately externalize its state.
This is truer as workloads move into the cloud and leverage ephemeral technologies, such as microservices and containers. To reach observability, IT and DevOps teams need to correlate different sources from logs, metrics, traces, events and more. This becomes even more challenging when defining the online revenue impact of a failed container—after all, this is what really matters to the business.
This webinar will cover:
The differences between observability and monitoring
Why it is a bigger challenge in a multicloud and containerized world
How observability results in less firefighting and more fire prevention
How new platforms can help gain observability (on premises and in the cloud) for containers, microservices and even SAP or mainframes
The numbers tell the story: 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives, yet 76% report they struggle with how to scale. With the stakes higher than ever, what can we learn from companies that are successfully scaling AI, achieving nearly 3X the return on investments and an average 32% premium on key financial valuation metrics?
To answer that question, Accenture conducted a landmark global study involving 1,500 C-suite executives from organizations across 16 industries. The aim: Help companies progress on their AI journey, from one-off AI experimentation to gaining a robust organization-wide capability that acts as a source of competitive agility and growth.
Read the full report:
http://www.accenture.com/AI-Built-to-Scale-Slideshare
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
How to Build Interactive Data Apps by ThoughtSpot Product LeadersProduct School
- An introduction to search for data
- How to add a consumer-friendly, self-search experience to your data app
- What the next generation of dashboards looks like
- Tools available for product builders
- A live deep-dive demo of how to build your first app embedding search
How Schneider Electric Assures Its Salesforce Lightning Migration with Thousa...ThousandEyes
ThousandEyes webinar from Tuesday September 17th 2019, presented by Archana Kesavan, Director of Product Marketing at ThousandEyes and Anil Sistal, Platform Architect at Schneider Electric on the topic of Schneider Electrics migration to ThousandEyes Synthetic Monitoring for Salesforce Lightning.
Platform Strategy to Deliver Digital Experiences on AzureWSO2
This slide deck introduces Choreo, a cloud native internal developer platform by Microsoft independent software vendor (ISV) Partner, WSO2. It enables your developers to create, deploy, and run new digital components like APIs, microservices, and integrations in serverless mode on any Kubernetes cluster with built-in DevSecOps.
Recording: https://wso2.com/choreo/resources/webinar/platform-strategy-to-deliver-digital-experiences-on-azure/
How Enterprise Architecture Management and Configuration Management DataBase ...LeanIX GmbH
This document discusses how CMDB (Configuration Management Database) data and EAM (Enterprise Architecture Management) tools like LeanIX can benefit each other. A CMDB provides a bottom-up inventory of technical components through automatic discovery, while an EAM tool provides a top-down view of the relationships between technology, applications, and business context. By combining data from both, organizations can ensure data quality, get a complete picture of their IT portfolio, and help execute their IT strategy. The document outlines challenges of solely using a CMDB and opportunities of integrating it with LeanIX, such as pre-filling data and regularly updating records.
This document summarizes a presentation about observability using Splunk. It includes an agenda introducing observability and why Splunk for observability. It discusses the need for modernization initiatives in companies and the thousands of changes required. It presents that Splunk provides end-to-end visibility across metrics, traces and logs to detect, troubleshoot and optimize systems. It shares a customer case study of Accenture using Splunk observability in their hybrid cloud environment. Finally, it concludes that observability with Splunk can drive results like reduced downtime and faster innovation.
Taking Splunk to the Next Level - ArchitectureSplunk
This session led by Michael Donnelly will teach you how to take your Splunk deployment to the next level. Learn about Splunk high availability architectures with Splunk Search Head Clustering and Index Replication. Additionally, learn how to manage your deployment with Splunk’s operational and management controls to manage Splunk capacity and end user experience
Observability – the good, the bad, and the uglyTimetrix
This document discusses observability and incident management. It notes that incidents are expensive and reduce credibility. Common causes of outages include changes, network failures, bugs, human errors, hardware failures, and unspecified issues. The timeline of an outage includes detection, investigation, escalation, and fixing. Many companies have a "zoo" of monitoring solutions that are difficult to manage. Common anti-patterns include an exponential growth of metrics that nobody understands. The document advocates focusing on key performance indicator metrics and using time-series databases, distributed tracing, and machine learning to more quickly detect anomalies and reduce incident timelines. It describes an open source project called Timetrix that combines metrics, events and traces for improved observability.
AIOps is becoming imperative to the management of today’s complex IT systems and their ability to support changing business conditions. This slide explains the role that AIOps can and will play in the enterprise of the future, how the scope of AIOps platforms will expand, and what new functionality may be deployed.
Watch the webinar here. https://www.moogsoft.com/resources/aiops/webinar/aiops-the-next-five-years
This document summarizes a presentation about Splunk's platform. It discusses Splunk's mission of helping customers create value faster with insights from their data. It provides statistics on Splunk's daily ingest and users. It highlights examples of how Splunk has helped customers in areas like internet messaging and convergent services. It also discusses upcoming challenges and new capabilities in Splunk like federated search, flexible indexing, ingest actions, improved data onboarding and management, and increased platform resilience and security.
This document discusses IBM's reference architecture for data and AI. It provides guidance on designing systems that use AI and analyze large amounts of data. The reference architecture covers strategies for collecting, storing, processing and analyzing data at large scales using technologies like Apache Spark, Hadoop and containers. It is intended to help organizations build systems that extract insights from data.
Data Governance and Metadata ManagementDATAVERSITY
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
Each CIO post description includes something resembling the 12 roles and requirements. This list outlines what CEOs are currently looking for in their CIOs. However, it's not necessarily what CEOs really need from their CIOs.
In the current data-driven economy, in which analytics and software have become the main factors in business, executives must reconsider the hierarchies and silos that fueled the business in the past. There is no longer a need for "technology people" who work independently of "data people" who work in isolation from "sales" people or from "finance." Instead, they need to manage organizations where every employee is embraced by technology and data as integral to their work.
They also require CIOs to guide them there. In this regard, redefining the business to accommodate the new data economy is the primary task executives have to today's top-of-the-line CIOs.
Here's how:
from Software and the Business to Software is the Business
When Cargill began to put IoT sensors in shrimp ponds, Chief Information Officer Justin Kershaw realised that the $130 billion agriculture business was evolving into a digital enterprise. To determine the point at which IT should stop and where IoT technology engineering needs to begin, Kershaw did not call CIOs from other food and agricultural companies to discuss their experiences. He contacted the CIOs of SAP and Microsoft as well as various other companies that use software. He was thinking about reimagining the world's biggest agricultural business as a software business.
Modern Delivery
Moving software from a supporting role to leading position is the why is the issue, then modern delivery is the way to do it. Modern delivery involves an approach to product (rather as project) management rapid development and small teams of cross-functional experts which co-create, as well as continuous integration and delivery, all with a brand new financial model that supports "value" not "projects."
However, don't try to build an modern SDLC. Instead, build a software development cycle (SDLC) on an industrial infrastructure. The architecture that is intended for this data-driven economy relies on platforms and cloud-connected, makes use of APIs that connect with an ecosystem outside and splits monolithic applications into microservices.
"A platforms model encompasses more than just an architecture. It's a mental model that allows us to consider how vertically we can provide the vet, farmer, or pet's owners, then expand to think horizontally about ways to make solutions adaptable, scalable and secure" claims Wafaa Mamilli Chief Information Officer and Digital Officer of global animal health firm Zoetis. "Platforms can be flexible, intelligent and run algorithms that let us rapidly change. If we did not adopt the platform model and approach, we'd be funding these massive programs."
The Democratisation of IT
If you gift someone an uncooked fish, they can take a bite for a few hours.
Exciting it trends in 2015 why you should consider shifting and upgrading yo...lithanhall
This document discusses exciting IT trends for 2015 and high demand IT career paths. It summarizes Gartner's top 10 strategic technology trends for 2015, including computing everywhere, the internet of things, 3D printing, advanced analytics, context-rich systems, smart machines, cloud/client computing, software-defined applications and infrastructure, web-scale IT, and risk-based security. It also outlines 5 in-demand IT career tracks: enterprise resource planning, systems management, business intelligence/big data analytics, technology sales and marketing, and technopreneurship. Finally, it introduces Lithan Hall Academy which provides skills training programs to help workers transition into these high-demand IT roles.
This session was presented at the AWS Community Day in Munich (September 2023). It's for builders that heard the buzz about Generative AI but can’t quite grok it yet. Useful if you are eager to connect the dots on the Generative AI terminology and get a fast start for you to explore further and navigate the space. This session is largely product agnostic and meant to give you the fundamentals to get started.
Artificial intelligence is reshaping business, and the time is ripe for companies to capitalise AI. The organisation can use AI to move their focus from discrete business problems to significant business challenges.
An organisation should use ML and Data Science to drive digital transformation for more back-office operational efficiency, better user/engagement, smoother onboarding, and better ROI by lowering cost and bring more data-driven taking mechanism for transparency.
AI will be a valuable, transformational change agent not only to the way business is done but to the way people live their daily lives if it isn't perceived as a plug-and-play technology with immediate returns but more like a long term solution to rewire the organisation.
A journey into the business world of artificial intelligence. Explore at a high-level ongoing business experiments in creating new value.
* Review AI as a priority for value generation
* Explore ongoing experimentation
* Touch on how businesses are monetising AI
* Understand the intent of adoption by industries
* Discuss on the state of customer trust in AI
Part 1 of a 9 Part Research Series named "What matters in AI" published on https://www.andremuscat.com
A recent study revealed that digital leaders (the top 10 percent of
companies leading technology innovation) achieve 2–3x revenue
growth as compared to their competitors—a widening divide that Accenture calls the “Digital Achievement Gap.” upload by Shamayun Miah Management Consultant Accenture
Observability has emerged as one of the hottest topics on the DevOps landscape. Organizations seek to improve visibility into their cloud infrastructure and applications and identify production issues that may negatively impact #customerexperience.
➡️ But what are some of the best practices for scaling observability for modernapplications?
➡️ What challenges are #cloudplatforms facing?
Explore how to overcome the challenges and unlock speed, observability, and automation across your DevOps lifecycle.
More Than Monitoring: How Observability Takes You From Firefighting to Fire P...DevOps.com
For some, observability is just a hollow rebranding of monitoring, for others it’s monitoring on steroids. But what if we told you observability is the new way to find out why—not just if—your distributed system or application isn’t working as expected? Today, we see that traditional monitoring approaches can fall short if a system or application doesn’t adequately externalize its state.
This is truer as workloads move into the cloud and leverage ephemeral technologies, such as microservices and containers. To reach observability, IT and DevOps teams need to correlate different sources from logs, metrics, traces, events and more. This becomes even more challenging when defining the online revenue impact of a failed container—after all, this is what really matters to the business.
This webinar will cover:
The differences between observability and monitoring
Why it is a bigger challenge in a multicloud and containerized world
How observability results in less firefighting and more fire prevention
How new platforms can help gain observability (on premises and in the cloud) for containers, microservices and even SAP or mainframes
The numbers tell the story: 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives, yet 76% report they struggle with how to scale. With the stakes higher than ever, what can we learn from companies that are successfully scaling AI, achieving nearly 3X the return on investments and an average 32% premium on key financial valuation metrics?
To answer that question, Accenture conducted a landmark global study involving 1,500 C-suite executives from organizations across 16 industries. The aim: Help companies progress on their AI journey, from one-off AI experimentation to gaining a robust organization-wide capability that acts as a source of competitive agility and growth.
Read the full report:
http://www.accenture.com/AI-Built-to-Scale-Slideshare
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
How to Build Interactive Data Apps by ThoughtSpot Product LeadersProduct School
- An introduction to search for data
- How to add a consumer-friendly, self-search experience to your data app
- What the next generation of dashboards looks like
- Tools available for product builders
- A live deep-dive demo of how to build your first app embedding search
How Schneider Electric Assures Its Salesforce Lightning Migration with Thousa...ThousandEyes
ThousandEyes webinar from Tuesday September 17th 2019, presented by Archana Kesavan, Director of Product Marketing at ThousandEyes and Anil Sistal, Platform Architect at Schneider Electric on the topic of Schneider Electrics migration to ThousandEyes Synthetic Monitoring for Salesforce Lightning.
Platform Strategy to Deliver Digital Experiences on AzureWSO2
This slide deck introduces Choreo, a cloud native internal developer platform by Microsoft independent software vendor (ISV) Partner, WSO2. It enables your developers to create, deploy, and run new digital components like APIs, microservices, and integrations in serverless mode on any Kubernetes cluster with built-in DevSecOps.
Recording: https://wso2.com/choreo/resources/webinar/platform-strategy-to-deliver-digital-experiences-on-azure/
How Enterprise Architecture Management and Configuration Management DataBase ...LeanIX GmbH
This document discusses how CMDB (Configuration Management Database) data and EAM (Enterprise Architecture Management) tools like LeanIX can benefit each other. A CMDB provides a bottom-up inventory of technical components through automatic discovery, while an EAM tool provides a top-down view of the relationships between technology, applications, and business context. By combining data from both, organizations can ensure data quality, get a complete picture of their IT portfolio, and help execute their IT strategy. The document outlines challenges of solely using a CMDB and opportunities of integrating it with LeanIX, such as pre-filling data and regularly updating records.
This document summarizes a presentation about observability using Splunk. It includes an agenda introducing observability and why Splunk for observability. It discusses the need for modernization initiatives in companies and the thousands of changes required. It presents that Splunk provides end-to-end visibility across metrics, traces and logs to detect, troubleshoot and optimize systems. It shares a customer case study of Accenture using Splunk observability in their hybrid cloud environment. Finally, it concludes that observability with Splunk can drive results like reduced downtime and faster innovation.
Taking Splunk to the Next Level - ArchitectureSplunk
This session led by Michael Donnelly will teach you how to take your Splunk deployment to the next level. Learn about Splunk high availability architectures with Splunk Search Head Clustering and Index Replication. Additionally, learn how to manage your deployment with Splunk’s operational and management controls to manage Splunk capacity and end user experience
Observability – the good, the bad, and the uglyTimetrix
This document discusses observability and incident management. It notes that incidents are expensive and reduce credibility. Common causes of outages include changes, network failures, bugs, human errors, hardware failures, and unspecified issues. The timeline of an outage includes detection, investigation, escalation, and fixing. Many companies have a "zoo" of monitoring solutions that are difficult to manage. Common anti-patterns include an exponential growth of metrics that nobody understands. The document advocates focusing on key performance indicator metrics and using time-series databases, distributed tracing, and machine learning to more quickly detect anomalies and reduce incident timelines. It describes an open source project called Timetrix that combines metrics, events and traces for improved observability.
AIOps is becoming imperative to the management of today’s complex IT systems and their ability to support changing business conditions. This slide explains the role that AIOps can and will play in the enterprise of the future, how the scope of AIOps platforms will expand, and what new functionality may be deployed.
Watch the webinar here. https://www.moogsoft.com/resources/aiops/webinar/aiops-the-next-five-years
This document summarizes a presentation about Splunk's platform. It discusses Splunk's mission of helping customers create value faster with insights from their data. It provides statistics on Splunk's daily ingest and users. It highlights examples of how Splunk has helped customers in areas like internet messaging and convergent services. It also discusses upcoming challenges and new capabilities in Splunk like federated search, flexible indexing, ingest actions, improved data onboarding and management, and increased platform resilience and security.
This document discusses IBM's reference architecture for data and AI. It provides guidance on designing systems that use AI and analyze large amounts of data. The reference architecture covers strategies for collecting, storing, processing and analyzing data at large scales using technologies like Apache Spark, Hadoop and containers. It is intended to help organizations build systems that extract insights from data.
Data Governance and Metadata ManagementDATAVERSITY
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
Each CIO post description includes something resembling the 12 roles and requirements. This list outlines what CEOs are currently looking for in their CIOs. However, it's not necessarily what CEOs really need from their CIOs.
In the current data-driven economy, in which analytics and software have become the main factors in business, executives must reconsider the hierarchies and silos that fueled the business in the past. There is no longer a need for "technology people" who work independently of "data people" who work in isolation from "sales" people or from "finance." Instead, they need to manage organizations where every employee is embraced by technology and data as integral to their work.
They also require CIOs to guide them there. In this regard, redefining the business to accommodate the new data economy is the primary task executives have to today's top-of-the-line CIOs.
Here's how:
from Software and the Business to Software is the Business
When Cargill began to put IoT sensors in shrimp ponds, Chief Information Officer Justin Kershaw realised that the $130 billion agriculture business was evolving into a digital enterprise. To determine the point at which IT should stop and where IoT technology engineering needs to begin, Kershaw did not call CIOs from other food and agricultural companies to discuss their experiences. He contacted the CIOs of SAP and Microsoft as well as various other companies that use software. He was thinking about reimagining the world's biggest agricultural business as a software business.
Modern Delivery
Moving software from a supporting role to leading position is the why is the issue, then modern delivery is the way to do it. Modern delivery involves an approach to product (rather as project) management rapid development and small teams of cross-functional experts which co-create, as well as continuous integration and delivery, all with a brand new financial model that supports "value" not "projects."
However, don't try to build an modern SDLC. Instead, build a software development cycle (SDLC) on an industrial infrastructure. The architecture that is intended for this data-driven economy relies on platforms and cloud-connected, makes use of APIs that connect with an ecosystem outside and splits monolithic applications into microservices.
"A platforms model encompasses more than just an architecture. It's a mental model that allows us to consider how vertically we can provide the vet, farmer, or pet's owners, then expand to think horizontally about ways to make solutions adaptable, scalable and secure" claims Wafaa Mamilli Chief Information Officer and Digital Officer of global animal health firm Zoetis. "Platforms can be flexible, intelligent and run algorithms that let us rapidly change. If we did not adopt the platform model and approach, we'd be funding these massive programs."
The Democratisation of IT
If you gift someone an uncooked fish, they can take a bite for a few hours.
Exciting it trends in 2015 why you should consider shifting and upgrading yo...lithanhall
This document discusses exciting IT trends for 2015 and high demand IT career paths. It summarizes Gartner's top 10 strategic technology trends for 2015, including computing everywhere, the internet of things, 3D printing, advanced analytics, context-rich systems, smart machines, cloud/client computing, software-defined applications and infrastructure, web-scale IT, and risk-based security. It also outlines 5 in-demand IT career tracks: enterprise resource planning, systems management, business intelligence/big data analytics, technology sales and marketing, and technopreneurship. Finally, it introduces Lithan Hall Academy which provides skills training programs to help workers transition into these high-demand IT roles.
2017 was a test of business resilience. While cyberattacks and natural disasters devastated some businesses, many others kept their operations running without disruption. Advances in artificial intelligence, machine learning and blockchain technology, among others, began helping more businesses eliminate inefficiencies, human error and downtime.
What will 2018 hold? We tapped our industry experts for their predictions on what IT trends they’re watching this year.
We asked how cyber security will evolve, what emerging technologies will take hold (and which ones are over-hyped), what mistakes companies may be making, and what all this means for the coming year. Here’s what the experts said.
The document discusses how cloud technology lends strength to data analytics. It notes that while cloud adoption faces challenges around security, privacy, and integration, cloud analytics are becoming mainstream. The cloud provides scale, elasticity and accessibility of data that supports analytics applications. Issues include complexity of data integration from diverse sources and managing risks of traditional long-term analytics projects. However, packaged cloud-based analytics applications accessed via SaaS can help businesses gain insights more quickly. While security remains a concern, cloud providers and in-house practices can help address issues.
1) Cloud computing adoption is growing in India due to rising adoption by large enterprises and SMEs seeking cost benefits over traditional data storage. However, migration challenges like legacy system compatibility and data security issues remain.
2) The market for cloud computing in India is expected to grow significantly in the coming years due to the exploding digital universe and increasing cloud adoption across both private and government sectors. However, data security, vendor lock-in, and lack of IT infrastructure in some areas may hamper growth.
3) Cloud computing provides significant benefits to organizations of all sizes by optimizing costs and increasing productivity, profitability, and business efficiency through accessible and scalable resources. However, concerns around data privacy, security
The document summarizes Gartner's top 10 strategic technology trends for 2014 presented at their annual conference. The trends include:
1) Increased mobile device diversity and management challenges for IT as employees use 3-5 devices by 2016.
2) Growing demand for cross-platform mobile apps as apps shrink and become more targeted.
3) Emergence of the "Internet of Everything" connecting 25 billion devices by 2020 and creating opportunities for data analytics.
4) Evolution to hybrid cloud architectures that combine internal and external services in various compositions.
5) Movement to cloud-based, client-agnostic applications accessible from any device.
6) Transition to personal clouds centered on user-defined services rather
The document discusses predictions for cloud computing trends in 2016. Key predictions include large companies increasingly adopting cloud infrastructure to cut costs and risks; the rise of cloud analytics to help IT monitor cloud deployment costs; hybrid cloud strategies becoming more common and supported by cloud vendors; and security becoming a priority as more sensitive data and applications move to the cloud. It also summarizes Amazon Web Services' (AWS) Well-Architected Framework for designing cloud architectures, which focuses on security, reliability, performance efficiency, and cost optimization.
IoT's rapid evolution marks the next stage in the innovation economy - White ...Technicolor
Like many new technology trends – such as Big Data or Cloud
Computing – that have captured the imagination of consumers
and business executives alike, the Internet of Things, or IoT,
has become a bit like a “Rorschach Test.” People see what they
want to see with the term is invoked.
To be fair, IoT lends itself to this tendency, because the concept
is so incredibly big, and its implications so deep. At its root IoT
is about devices talking to each other without human intervention
using the internet protocol. But this alone would cleanly fall into
the category of machine-to-machine (M2M) communications.
“When you look at what’s happening with IoT devices, explains
Danny Lousberg, Director of Product Management for Qeo
at Technicolor, “you will see a huge effort to create a vertical
ecosystem in which a specific device is communicating with a
specific back-end server that lives somewhere in the cloud to
tackle a specific use case for the user. And that means these
devices all are battling for a piece of mindshare and eyeballs.”
“The Internet of Things is inherently different from M2M
communication because M2M is really meant to solve large-scale
problems for a big group of devices that are all trying to work
together in a larger environment that is not necessarily controlled
by the end user.”
What makes IoT truly powerful is when M2M is linked to Mobility,
Big Data, Cloud Computing and other critical elements in today’s
modern technology infrastructure to empower and provide
options to end-users.
“From my perspectives, it will be virtually impossible to view these
technological paradigms independent of each other and from IoT,”
says Kurt Jonckheer, General Manager, Virdata, and VP, Strategic
Projects, Technicolor.
“The promise of IoT is that devices and appliances of all sorts
will, without human interference, interact with each other to
create a better experience for users by engaging in things like
self-diagnosis, harnessing event-driven actions that enhance
the human experience, or simply reduce costs in an intelligent
and automated manner.”
This combination of technologies is already generating billions
of dollars in revenue. Trillions more will be triggered as
businesses come to grips with the true potential of IoT.
The document summarizes key findings from the BT CIO report 2016 regarding the changing role of the CIO. Some of the main points from the summary are:
- The three most disruptive technology trends driving change are cloud computing, mobility/collaboration, and data. A fifth of organizations describe themselves as completely cloud-centric.
- CIOs are playing a more central strategic role in the boardroom and are expected to drive innovation. Their skills must embrace faster-paced digital change.
- While security concerns still present challenges, the cloud is seen as an opportunity to improve security for many organizations. CIOs are measuring success against new digital-focused KPIs.
- S
Marcos Taccolini | Top Ten Technology Trends of 2015Marcos Taccolini
3D printing will reach a tipping point over the next three years as the market for low-cost 3D printing devices grows rapidly and industrial use expands significantly. Computing will increasingly adapt to the requirements of mobile users as devices proliferate and IT loses control of endpoints. The Internet of Things will create new usage models like pay-per-use that can be applied across industries by leveraging data streams from digitized assets, services, people, places and systems.
This document outlines Oracle's top 10 predictions for the enterprise cloud by 2025. The predictions are:
1) Second-generation cloud providers will offer 100% data center replacement capabilities.
2) 80% of all enterprise workloads, including mission-critical workloads, will move to the cloud.
3) All applications will incorporate AI to further distance themselves from legacy applications.
4) AI and emerging technologies will double productivity.
5) 85% of customer interactions will be automated.
6) The developer community will expand 10 times and productivity will increase 400%.
7) More than 50% of data will be managed autonomously.
8) 90% of enterprises will use a single
Cxo cockpit customer newsletter - october 2013Richard Wolters
This newsletter provides an overview of updates to the CXO-Cockpit reporting solution. It includes articles on mobile strategy considerations, a customer case study of how Atria Senior Living uses CXO-Cockpit for data-driven operations, details of the new CXO-Cockpit version 5.0 including linked objects and report builders, and fast facts on CXO apps, new customers, and the company's new office location.
Top software development trends of 2021*instinctools
The technologies that businesses use today are bound to the new world paradigm and capable of adapting to it. Here are some trending technologies that can easily help companies adjust to a digital business world 2.0 in just a short time.
Here are the top 7 digital transformation trends in 2022. 1. Working Environments and Hybrid Experiences 2. AI, ML, and hyperautomation 3. Collaboration
Digital Transformation and Next Gen Technology Study 2023Tam Luong
The document is a summary of a study on digital transformation in the financial services industry. Some key findings include:
- Digital transformation is now mainstream, with over half of participants agreeing it is their most important strategic initiative. However, legacy systems still hold many back.
- Firms are increasing spending on technologies like AI, cloud computing, and blockchain, seeing tangible returns. Leaders are expanding AI use enterprise-wide and centralizing data.
- Challenges remain around balancing innovation with daily operations, budget and skills shortages. Replacing legacy systems is a top priority for non-Leaders.
- Emerging technologies like blockchain, quantum computing, and edge computing could further disrupt the industry, but investment is more cautious
https://iot-eurasia.com/
"IOT will completely transform the way we do business, in a staggered manner such that most of the business transactions will become near real time or real time, enabled by IOT. IOT also helps us to get additional data points which is not possible in non-IOT setup. These additional data points generate additional value or enhances the existing value. Few examples to quote include real time patient data (vital signs, quality of life, etc.), real-time manifacturing, drug supply and also predict the demand and supply drug. The next level of competitive advantage can be derived when we add advanced analytics capabilities to unlock the insights from IOT and other traditional data points. Predictive analytics take decision making to the next level, where almost all decisions can be made better."
"In order to move business beyond main areas, industries will have to secure partnerships with good IoT platforms. For instance, transforming Telco into an ICT (Information and communication technologies) organization by offering Digital services such as IoT Application Enablement Platform (AEP) and M2M Connectivity Platforms. A telecommunication firm has a unique opportunity to drive mobile payments – by building on direct carrier billing through multiple payment options, data management and seamless fulfilment – to the next level. Also, faster adoption of cloud, big data and cyber technologies would ensure delivering impeccable network, platform and solution functionalities."
Enterprise mobility, cloud computing, and retail automation are expected to be major trends in the Indian software market in 2012. Cost reduction will be a primary focus for companies. The mobile BI market is growing rapidly, with over 33% of BI functionality expected to be consumed on mobile devices by 2013. The cloud computing market in India is projected to reach $1 billion within the next 5 years, growing at a fast rate, driven by increasing digital data and adoption of cloud-based solutions. Hybrid cloud models are gaining popularity as they allow companies to balance security, control, and scalability needs.
The future is in the cloud, or at least it's migrating there. Offering scalability, flexibility and agility, the cloud is the obvious solution for businesses seeking to make sense of the deluge of data. Cloud services can also help companies meet sustainability goals and even cut costs. But cloud strategies need to be carefully crafted to avoid the risks of remote storage and realise the potential of cloud-enabled efficiencies.
IOT is going to be very big and the fitness, health club and gym industry are no exception. To lead the adoption of IOT requires thoughtful strategy and a clear road map for implementation.
Similar to it-observability-predictions-2023.pdf (20)
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
2. Splunk IT+Observability Predictions 2023 | 02
The Fast Track to
Foundational
The world of IT Operations has
been in tremendous flux for more
than a decade. The worlds of IT
Ops, we should say: traditional
ops, the many variations of
DevOps, and the organizations
that have pockets of both. All
of these approaches grapple
with the increasing complexity of infrastructure and
applications. Hybrid, multicloud … microservices,
Kubernetes, serverless.
3. Splunk IT+Observability Predictions 2023 | 03
One of the big topics in recent years has been observability, a modern approach
to monitoring that provides complete visibility and context across the full stack of
infrastructure, applications and the customer experience. Observability helps ensure
digital health, reliability and performance.
And it’s essential in today’s hypercomplex environments.
“Every organization has a digital presence, with more and more moving parts,” says
Mala Pillutla, Splunk’s group vice president for observability. “Especially for larger
organizations, the complexity is increasingly volatile. They need Kubernetes monitoring,
serverless monitoring and more. The success of your entire digital ecosystem,
and therefore your business, depends on observability to keep it all running.
So observability is no longer a differentiator — it’s a core competency.”
She says she sees two basic types of sponsor for observability. “One is your traditional
ops team, a centralized, shared service that supports the entire org. The other is a
loose grouping of AppDev, DevOps and SREs, and we tend to see them in cloud-native
organizations where the teams are not centralized. The first group is focused on the
transition from legacy, monolith architecture to cloud-native tools, and the second is
not playing that longer game. They’re already there; they want new tools with out-of-
the-box value.”
4. Splunk IT+Observability Predictions 2023 | 04
Simon Davies, Splunk’s SVP and general manager in the Asia-Pacific region, agrees.
He says he sees a wide range of legacy and cutting-edge organizations tackling the
challenge differently.
“A lot of organizations in Asia don’t have the same legacy technology debt, allowing them
to leapfrog into new technologies,” he says. “A lot of orgs are thinking about observability
for the first time, with no legacy practice.”
And others, says Dhiraj Goklani, Splunk’s VP of observability, struggle to catch up. “Some
folks are still asking, ‘What is observability?’ And they’re still finding it hard to digest,
while at the other end, it’s definitely understood, and a must-have for cloud-native
organizations.”
Our State of Observability 2022 report found similar variance in Europe, both among
types of organization and among countries. Organizations in France and the United
Kingdom trailed the average in observability adoption, on average, while Germany
outperformed the global baseline.
5. Splunk IT+Observability Predictions 2023 | 05
Garth Fort, Splunk’s chief product officer, notes that all this complexity is going to
keep complexifying.
“Our Predictions report last year talked about the growth of serverless, and that’s
continuing,” he says. “We’re still very early in the adoption of true service architectures.
More of our customers are building apps using microservices and containerized
architectures, and the way you monitor performance when a container may exist for
mere milliseconds is so different from earlier, less dynamic architectures.”
Observability, then, will continue to support hybrid, multicloud infrastructures as they
sprawl toward the edge and incorporate machine learning, microservices, containers
and all the rest, and as the very practice of IT operations continues to evolve.
“And observability tools will be easier to use, despite
that complexity,” says Ammar Maraqa, Splunk’s chief
strategy officer. “These solutions need to support
the journey of any individual organization across
the various phases of cloud, and that’s the only way
these solutions will succeed.”
6. Predictions and Survival
Strategies for 2023
07
Observability
Meet the new face of DX.
08
IT
Where’s the value?
09
Automation
The next differentiator
11
Security and Observability
The convergence is
happening, and it’ll make
organizations more resilient.
13
CTO and CISOs
How two keys roles
will expand
15
Talent
Broader recruitment,
better training and
more automation
17
AI and ML
The value is materializing.
And ML Ops will help.
19
AI and ML
AI ethics is making strides.
22
The Importance
of Resilience
25
Contributors
7. Splunk IT+Observability Predictions 2023 | 07
Prediction
Observability will be
the new face of digital
transformation — and
digital experience.
At the start of the digital age, “digital transformation” was a useful term for a broad set of
modernization efforts that were expected to deliver a variety of significant payoffs: Reducing
costs; streamlining software development, product innovation and service delivery; improving
forecasting and other strategic functions; automatically keeping the break room stocked
with coffee and trail mix. These days, digital transformation is both faster and more focused.
Especially since the arrival of Covid-19, DX efforts have focused on digital experience.
“Digital transformation, for most organizations today, is about
providing a highly available, seamless digital experience for the
customer,” says Katie Bianchi, Splunk’s chief customer officer.
Chief Product Officer Garth Fort points to Splunk customer
Papa John’s, whose pandemic-era transformation was
discussed at our annual .conf event. “Pre-pandemic, 40%
of their business was digital. Post-pandemic, 90% of their
orders come in through some sort of a digital interface,” Fort
says. “When any business sees that kind of e-commerce shift,
their mobile app and their payment infrastructure and all that
becomes absolutely mission critical. A lot of our customers in
different industries had that sort of sudden pivot during the
pandemic, whether it was in dealing with more digital customer
interaction or in enabling widespread remote collaboration.”
And don’t expect a post-pandemic world where any of that
changes back. “Accelerated digital transformation is here
to stay,” says Splunk Chief Strategy Officer Ammar Maraqa.
And he says that in a more complex IT environment, fast and
8. Splunk IT+Observability Predictions 2023 | 08
fulfilling experiences are harder to deliver. “The complexity of
greater, faster digital transformation is a challenge for most
organizations. The tools to manage that complexity become
even more important.”
That’s what makes observability the essential DX driver, Fort
says. “It’s not good enough to be responsive when customers
are having a problem on your network,” he says. “If we’re
all doing our jobs right, the IT Ops team can remediate DX
problems before the customer even sees them.”
A strong observability practice, he says, is the only way to
get the alerts and insights that let you respond to a change in
system behavior before the end user suffers. And not having
those kinds of early-warning insights isn’t an option.
Prediction
IT spending
really has
to deliver
measurable value.
It’s not a prediction, but an observation, to say that
2023 dawns amid considerable macroeconomic
uncertainty. That tends to make companies more
prudent about investments. While we’re not
predicting that IT budgets will contract, they’ll
certainly be more closely scrutinized.
“Right now, all the economic factors except employment point
toward recession,” says Petra Jenner, SVP and general manager
for Splunk in the EMEA region. “Companies are very concerned
about investments in the face of a downturn. They’re purchasing
only what’s needed right now, not making any forward-looking
investments.”
“Companies are thinking clearly about which tech investments
they want to make,” Splunk CEO Gary Steele agrees. “Real value
has to be delivered, pretty quickly.”
We expect that value focus to center on digital experience,
because nothing moves the needle more than direct
improvements to how you serve your customers. And nothing
moves it faster in the wrong direction than delivering a frustrating
or broken interaction when better options are a click away.
9. Splunk IT+Observability Predictions 2023 | 09
Prediction
When observability is table stakes,
automation will be the next
differentiator.
Customer experience will shape digital
transformation efforts in the years ahead.
Focusing within the world of IT Operations,
the big differentiator will be automation.
“Between the increasing complexity of systems and the huge
shortage of tech talent, organizations will need a much greater
reliance on automation just to keep up,” says Spiros Xanthos,
Splunk’s SVP and general manager of observability, and a
founder of observability startup Omnition.
Xanthos notes that the greater need to automate IT operations
coincides with improvements in machine learning. “We’ve been
collecting telemetry data for a long time, but that data was
not structured enough for good automation,” he says. “The
poor signal-to-noise ratio allowed us to do some automation
through AIOps, but it was very limited. Now organizations are
increasingly able to collect data at full fidelity. That’s going to
change things dramatically, because the much higher quality
data lets us build the models that we need essentially to
automate processes right.”
“The combination of AI/ML and automation is going to be really
big,” says Ammar Maraqa, Splunk’s chief strategy officer. “The
need is really there, because of the shortage of skilled IT and
security talent and the increasing pressure on costs.”
Katie Bianchi, Splunk’s chief customer officer, also calls out
talent issues. “Given ongoing talent shortages,” she says,
“automation enables you to scale domain expertise.”
10. Splunk IT+Observability Predictions 2023 | 10
She says machine learning will both simplify and improve
all business outcomes, from application performance to
improved security detection. “In all those cases, ML provides
better and more accurate insight so that we can see what’s
coming next and orchestrate the best response,” she says.
“Making automation smarter is the next big leap,” says Mark
Woods, our chief technical advisor in EMEA. “It’s one thing to
automate playbooks so that something a human would do
happens at greater speed and scale. But the next step will be
the application of more generalized learning to automation.
Not just learning for a specific task, but something that’s
trained up in one area that has applications across many areas.”
That will include a large range of things, from alerts
and responses to system outages and cyberattacks, to
streamlining peripheral processes and accelerating release
velocity. Subho Majumdar, a senior applied scientist at Splunk,
brings up process automation to more effectively onboard
new talent.
“We have a lot of documentation that a new engineer might
need to read when they join the company,” he says. “Imagine
automating the onboarding process by using ML. Large
language models could analyze all the internal documents
and wikis to come up with role-specific recommendations for
new hires.”
From new hire orientation to chatbots your customers can
actually chat with, to greater resilience against threats and
performance issues, expect automation to be the next
big thing.
And then a few years after that, just like observability, expect it
to become foundational.
11. Splunk IT+Observability Predictions 2023 | 11
Prediction
Observability and
security data/tools
will converge
to create more
resilient orgs.
“There are cases, especially in highly regulated environments,
for segregating some security data. But generally, there’s a
lot of overlap between what was traditionally Operations and
Security,” says Robert Pizzari, Splunk’s VP of security in the
Asia-Pacific region. “Progressive organizations are finding
ways to optimize their data and tooling to accelerate time to
resolution for any kind of incident.”
“Where there’s a strong push toward SRE-based engineering
teams, a reliance on cloud-native tech, there’s really no choice
but to converge data and processes,” says Dhiraj Goklani,
Splunk’s VP of observability in APAC. “You have to go down
the DevSecOps path and bring it all together, baked into
engineering best practices. Otherwise it’s a disaster waiting
to happen.”
Spiros Xanthos, Splunk SVP and general manager of
observability, sees the trend across the tech marketplace.
“The industry is in consolidation mode,” he says. “Consolidation
of data and consolidation of tooling.” Essential data, whether
it’s on-premises or in the cloud, can’t be siloed. “The complex
interconnectedness of applications running on the cloud
makes availability and security tougher problems.”
There’s a lot of talk about business resilience. It’s the hot new buzzword. But it’s also much
more than that. We’ve identified two trends, covered in these next two predictions, that make
meaningful contributions to the strength and durability of digital systems. The first is the
convergence of data and tools from two formerly siloed aspects of resilience.
12. Splunk IT+Observability Predictions 2023 | 12
As the data comes together, and teams collaborate more
across the DevSecOps spectrum, there’s a tooling shift
as well. Point solutions that see and serve only a fraction
of the situation aren’t helping resilience, and maintaining
expertise across so many tools is a burden on fast-changing
organizations. Splunk’s 2022 State of Observability and
State of Security reports both found that while the most
mature organizations in both disciplines actually reported
using as many or more tools than neophytes, the leaders had
also dramatically reduced the number of vendors providing
those tools.
“We’re seeing that ourselves,” Xanthos says. “Our own suite of
cloud products has a number of tools, and we tend to see the
more advanced customers adopt more of those tools.”
“There’s so much to be gained from this sort of convergence,”
says Chief Product Officer Garth Fort. “At .conf, we talked to
the new CISO of REI, who was familiar with Splunk as a security
tool, and he found that REI was already using Splunk for
observability, so he was able to easily bring it over for security,
using the same tools and the same data. And that applies to
any technology — anytime teams can use a common tool with
a common set of data, there’s going to be big benefits.”
13. Splunk IT+Observability Predictions 2023 | 13
Start with the chief technology officer: “The role of CTO is
becoming more prominent, and taking more responsibility
for technologies like observability that span DevOps and
traditional IT operations,” says Mala Pillutla, Splunk’s group vice
president for observability. “Splunk’s early customers were
mostly the NOC and the SOC, but with the rise of observability
we’re seeing platform teams and centers of excellence under
the CTO become a more significant constituent.”
Chief Customer Officer Katie Bianchi spends most of her time
talking to our customers and understanding how their IT and
Security organizations contribute to overall business success,
and she too has seen more leadership from CTOs.
“Today’s CTO has taken on more responsibility. As more and
more organizations shift to the cloud and their observability
needs subsequently grow, CTOs now have much more
responsibility across a broad range of applications and
infrastructure.”
It makes sense to Spiros Xanthos, Splunk SVP and general
manager of observability, and a three-time founder/CEO.
“Usually the CTO manages the development organization, or
maybe the SRE organization as well, so they have a much
bigger responsibility usually in the operations of the cloud
infrastructure and applications running on it,” Xanthos says.
“At the same time, we’re increasingly seeing that the CISO is
not responsible strictly for security anymore, because the
tools and data that provide cyber resilience can be used for
availability resilience.”
Which brings us to the chief information security officer. Years
of effort to tear down data silos, and to provide tools that let
Prediction
The CTO is rising, and the CISO
is expanding.
The convergence of data and tools around the separate functions of IT
resilience and cyber resilience are also affecting leadership, generally in one
of two significant senior roles. First, many organizations are empowering
the CTO, in part driven by the adoption of DevOps practices. And at other
organizations, CISOs are taking greater responsibility for resilience in general,
including not only combatting security attacks, but ensuring performance.
14. Splunk IT+Observability Predictions 2023 | 14
security teams see across the entire organization, have put
CISOs in a great position to tackle any threat to IT systems.
“Not only do CISOs have these tools,” Xanthos says, “but
obviously, one of the first questions that must be addressed
when you detect an availability problem is, ‘Is this a security
incident?’”
“We’re starting to see the organizational dynamics and
definition of mission reflect the convergence at the data
layer,” says Patrick Coughlin, Splunk’s vice president of GTM
strategy and specialization. “Job titles and job descriptions are
changing to match, and the influence of the CISO is expanding
across the enterprise to cover this broader definition of
incident, meaning that the CISO is now weighing in on new
decisions throughout the organization.”
The CISO’s move toward overall resilience and the CTO’s more
holistic responsibility for technology can happen at the same
time within an org. Or not.
“It’s not a uniform shift,” Bianchi says. “Every organization
achieves the balance it needs. But we’re definitely seeing the
scope of those two roles, CTO and CISO, expand.”
With both options, we see organizations trying to achieve in
their leadership what they’ve spent decades trying to build
in their digital environments: centralized, unsiloed oversight,
to deliver greater efficiency, stronger resilience and better
strategic insights.
15. Splunk IT+Observability Predictions 2023 | 15
Prediction
How we’ll mitigate the talent crisis:
Broader recruitment, training in principles
not tool skills, and automation.
“No matter what economic environment emerges, that very
tight labor market won’t change for security or IT,” notes
Splunk CEO Gary Steele. As a result, companies are trying
harder to throw a wide net for talent, rather than a narrow net
for skills. Hiring curious problem solvers rather than people
with the four specific certifications in the job rec.
Dhiraj Goklani, VP of observability in APAC, agrees with
that strategy, but notes that the problem isn’t just a lack of
STEM graduates. “In many markets across APAC, we see
organizations building next-gen architectures and tooling such
as observability to attract and retain a talented workforce.”
That’s where tools like GitHub Copilot will eventually allow
smaller teams of developers to work faster, and allow less
technical people to extend their abilities. (See our Exec
Predictions report for the changes to IT that these large
language models will bring.)
The pandemic accelerated several notable trends in the human resources realm. Our Executive
report dives deeper into the tension between recessionary forces and employee demands, but
here we wanted to highlight efforts to mitigate the talent shortage that forever plagues IT and
security teams alike.
16. Splunk IT+Observability Predictions 2023 | 16
In addition to automation and hiring for talent, not narrow
experience, software makers and the IT Operations and
Security teams they serve will have to add a broader education
component to their focused tool training.
“Organizations need to rely on their suppliers to build the
ecosystem of talent that will deliver business outcomes most
effectively,” says Chief Customer Officer Katie Bianchi.
“Companies like Salesforce have been innovative because they
recognized the need to build an ecosystem of talent that can
use their platform to power major business outcomes. The goal
is not to train teams just on using the solution, but also on using
the solution to achieve business outcomes.”
She says another onus on the supplier is to make the product
as easy to use as possible.
“We’re trying to move in that direction ourselves,” says Lily Lee,
senior manager of security solutions strategy. “In the case of
security, my team is looking at how we can make our product
education more broadly applicable, so we are not just teaching
you Splunk, but also how to be a better threat hunter, how to
be a better tier one or tier two analyst.”
This approach will build a better talent ecosystem, and make
the companies that invest in such career-level training more
attractive to the very talent they’re trying so hard to retain in
the first place.
17. Splunk IT+Observability Predictions 2023 | 17
Prediction
AI/ML value is materializing all around
us. MLOps will bring structure and
transparency to extend that progress.
Years of artificial intelligence hype is finally paying off.
“In the classic adoption curve, we’re past the hype and into the
building phase,” says Mangesh Pimpalkhare, vice president
of product management for the Splunk platform. “We’re just
getting to the point of real value being realized.”
The average user of software, whether it’s a consumer’s video
streaming platform or a business user’s customer resource
management application, doesn’t realize that their digital
experience is enhanced by machine learning. Sure, it’s all over
the marketing copy, but the user experience is simply smarter,
faster … better.
“The stage has shifted a lot in the last ten, even the last five
years,” says John Reed, principal product manager at Splunk
specializing in AI. “In the early days, there was a lot of focus on
the actual technology and manual, hands-on training. That’s
no longer the goal or end point. AI is becoming the lubricant
to make things easier. The focus is not on the nuts
and bolts underneath; it’s about value.”
“The software makers have figured out
the underlying complexity, those nuts
and bolts,” Pimpalkhare says. “That lets
customers focus on results.”
But someone has to focus on the
operational aspects of machine learning.
Thus, a new discipline has emerged: MLOps.
“MLOps is DevOps for machine learning,” says Joe
Ross, a senior principal applied scientist at Splunk. “Machine
learning has additional complexities. It’s a combination of
18. software and data with a more complex lineage, so being able
to characterize and describe how you got to certain outputs
or outcomes so you can debug it or explain it to a regulator is
more complex. Through MLOps, we’re seeing the application of
standard software lifecycle management practices to AI/ML. A
lot of that is taking the shape of better tooling.”
In fact, MLOps has spawned a sprawling industry of tools —
frankly, more than the world needs.
“The MLOps market is completely saturated,” Reed says. “There
are hundreds of vendors providing different aspects of MLOps
to make it work end-to-end, and there’s limited innovation in
that market. There will be massive consolidation over the next
couple of years.”
That’s not at all to say that MLOps as a discipline is imploding.
Far from it, Ross says.
“If you track job listings with DevOps in the title over time, the
percentage has gone up quite a bit — it’s no longer just the
most technically progressive companies looking for those skills,”
he notes. “That will happen with the MLOps world as well.”
So start hiring and training today to get ahead of tomorrow’s
talent crunch.
19. Splunk IT+Observability Predictions 2023 | 19
Prediction
Increased concerns about ethical AI will
affect how ML is trained and maintained —
and create new roles to do it.
Our third look at the increasing pervasiveness of machine learning is in terms of evolving ethical
practices. Stories of unintended bias discovered in ML models regularly emerge. Fortunately, MLOps
practices will bring more standardization and transparency, making it easier to assess models for
fairness and to maintain and retrain to prevent biases from creeping in.
For more, we turned to Subho Majumdar who may not have
written the book on ML ethics, but he certainly co-wrote
a book on the topic (Practicing Trustworthy Machine
Learning, just published by O’Reilly). Majumdar is active with
multiple community efforts — Trustworthy ML initiative, Bias
Buccaneers and AI Vulnerability Database — which are looking
to guide and educate ML practitioners to develop ML models
that are fair, safe, robust, explainable and that preserve privacy.
Majumdar says that transparency, a necessary prerequisite of
fairness and other values, is increasingly important.
“Trustworthy ML involves operationalizing ML while
incorporating human values into your ML pipeline,” he
says. “The goal is to build trustworthy ML pipelines from the
beginning, so you don’t face biases and other problems in your
outputs after the models are deployed in the real world”.
20. Splunk IT+Observability Predictions 2023 | 20
Joe Ross points to model cards, which provide brief
documentation about an ML model that increases
transparency into the model and its outputs. A card would
describe a model’s uses and limitations, review bias and ethical
considerations, and detail the data and methods used to train
the model.
“And we’re seeing work at HuggingFace and other repositories
to ensure that we can understand the lineage of a model,” he
says. “This moves us toward being able to make scientific
demonstrations of bias in the model as part of a standard
review process that checks for a list of known biases.”
Bias checklists, he says, could become a standard part of ML
quality assurance, both when the model rolls out and over time,
as additional data alters its outputs.
In addition to new processes, concern with AI ethics will also
create new jobs. Majumdar foresees specific team roles for an
AI ethicist, and for a prompts engineer, who would focus on
how prompts not only influence the accuracy of the model’s
outputs, but its potential biases.
“As a community, we’re progressing toward providing
transparency to whomever the stakeholder is,” Majumdar
says. “If it’s the government, that would mean transparently
abiding by any regulations and compliance guidelines. If the
stakeholder is the consumer, there needs to be a way to file
a ticket or a complaint about any concerns on algorithmic
decision-making. There is already an AI Incident Database,
which tracks things that went wrong with deployed AI/
21. Splunk IT+Observability Predictions 2023 | 21
ML models. It’s kind of like the CDC’s vaccine effectiveness
database, where you can submit any problem that occurred
because of a vaccination. This is a complicated area, so it will
take a few years for the ML community to figure things out.
But I do think we are going to see more standards and best
practices on trust and transparency in ML.”
“Regulation is always behind the cutting edge technologies,
whether you’re talking about blockchain, ML, even
ecommerce,” says Mangesh Pimpalkhare, vice president
of product management for the Splunk platform. And he’s
hopeful that some of the worst outcomes we’ve seen to date
around data privacy and technologies such as social media
will provide learnings to shape the next wave of technology.
“The wildness of tech will continue, but it won’t take as long to
reach a responsible endpoint. It’s in the industry’s best interest
to establish effective self regulation ahead of lawmakers.
You see some of that now, with self-declarative responsible
AI initiatives.”
Kriss Deiglmeier, who leads Splunk’s social impact initiative,
agrees that regulation isn’t an immediate answer, and that
the public won’t be content to wait. “AI and data ethics are
becoming more important to business, and in the short term
it will be the responsibility of business to make their own
progress,” she says. “More regulation will follow, but it’ll be
different in each country or region.”
22. Splunk IT+Observability Predictions 2023 | 22
The Importance
of Resilience
The solution to a lot of problems in the ITOps world,
anywhere on the traditional-DevOps spectrum,
involves more time, money and people.
Throw all that at most problems, and most
problems can be resolved. Unfortunately,
the turbulent global economy that is
carrying us out of 2022 and into the new
year means tighter belts all around.
23. Splunk IT+Observability Predictions 2023 | 23
But that’s not so bad. It’s not like IT teams are generally throwing
around cash like a Kardashian on Rodeo Drive, anyway. IT leaders
have always understood how to make the most of limited resources
and focus on the most necessary wins. And that’s exactly the attitude
we’re seeing across the board among our customers: quick wins and
meaningful value.
“Leaders I talk to are very focused on extracting as much value as
effectively and quickly as possible out of their data,” says Chief
Customer Officer Katie Bianchi. “And they want their suppliers to
prescribe fast paths to value.”
24. Splunk IT+Observability Predictions 2023 | 24
“Digital transformation is one of those things
that you can’t completely deprioritize,” says
Chief Strategy Officer Ammar Maraqa. “But
organizations will be more nimble, with
more incremental funding and a sharp focus
on results.”
And a lot of that focus will be on resilience,
both observability into performance or
security of data and systems. In terms of
performance, it’s one of the chief values any
digital organization can offer (and we’re all digital orgs now).
“Systems have to be resilient, because customer expectations have
grown exponentially in our high-speed world,” Bianchi says. “Application
performance and availability are at the heart of a great customer
experience and a growing, innovative business.”
But as high as expectations have grown, we’ve also seen the tremendous
evolution of the technologies that help us meet those needs. From
observability to automation to machine learning, we predict that IT teams
will have the tools and techniques to succeed.
25. Splunk IT+Observability Predictions 2023 | 25
Contributors
Kriss Deiglmeier
Kriss is Splunk’s chief of social impact and
Splunk Global Impact. She is recognized
as a social innovator, is a frequent speaker
at global events, and was recently listed
among the “50 Most Influential Women in
U.S. Philanthropy” by Inside Philanthropy.
Garth Fort
Garth joined Splunk in 2021 as SVP and chief
product officer. He came from AWS, where he
was director of product management and then
general manager, after a two-decade tenure
at Microsoft.
Dhiraj Goklani
Dhiraj is Splunk’s vice president of observability
in APAC, where he applies more than two
decades of experience in the tech industry
to helping grow the observability market in
the region.
Katie Bianchi
Katie is Splunk’s senior vice president and
chief customer officer. Previously, she was
vice president of customer success at GE
Digital, and hasheld leadership roles in
product management, business development,
services, marketing and operations across
industries, including aviation, power
generation, and oil and gas.
Patrick Coughlin
Patrick, Splunk’s VP of GTM strategy and
specialization, comes from a deep security
background. He was co-founder and CEO of
TruSTAR, a cyber intelligence management
platform acquired by Splunk. Previously, he led
cybersecurity and counterterrorism analyst
teams for the U.S. government and private
sector clients.
Simon Davies
As senior vice president and general manager
in APAC, Simon is responsible for the full
portfolio of Splunk solutions in the Asia-
Pacific and Japan markets. He is a veteran of
Microsoft, Salesforce, Oracle and Citibank.
26. Splunk IT+Observability Predictions 2023 | 26
Petra Jenner
Petra is SVP and general manager in EMEA for
Splunk. Previously, she held leadership roles at
Salesforce, Microsoft, Checkpoint and Pivotal.
She holds a Masters Degree in Business and IT,
and studied International Management at
the Stanford Graduate School of Business
in Singapore.
Lily Lee
Lily is a senior manager of security solutions
strategy at Splunk. She leads a global
team of industry and product experts that
support Splunk’s security business and serve
as thought leaders and trusted advisors
for Splunk customers, partners and the
security community.
Subho Majumdar
Subho is a senior applied ML researcher in
Splunk’s threat science group. Previously he
was with AT&T Data Science and AI Research.
A cofounder of multiple community efforts in
ML, Subho recently co-authored Practicing
Trustworthy Machine Learning.
Ammar Maraqa
Ammar is Splunk’s senior vice president and
chief strategy officer. Back in the day, he led
corporate strategy at Cisco, was part of the
M&A team there, held product roles at Dell,
and started his career as a consultant with
Bain & Co.
Mala Pillutla
As GVP of observability, Mala leads
observability business growth strategy and
execution at Splunk. Before coming to Splunk,
she held leadership roles at organizations
including ServiceNow and IBM, where she led
and scaled high-value GTM organizations.
Mangesh Pimpalkhare
Mangesh is vice president of product
management for Splunk Platform. As a
product executive, he has had more than 15
years of operating experience and more than
eight years of venture capital experience
in diverse software (SaaS), systems and
technology companies.
27. Splunk IT+Observability Predictions 2023 | 27
Robert Pizzari
Robert is Splunk’s vice president of security in
the APAC region. Previously, he held leadership
roles at Check Point, FireEye, Trustwave
and Cisco.
John Reed
John is a Principal Product Manager at Splunk.
His responsibility includes the strategy and
execution of initiatives across Machine
Learning and Core Search. Previously, John
was a product manager at AWS, where he
worked across the AI/ML service portfolio.
Joe Ross
Joe is senior principal applied scientist at
Splunk. Before joining Splunk, he worked in
senior data scientist roles at SignalFx (before
it was acquired by Splunk) and Ayasdi. He
has a background in mathematics, and has
publications in pure math and statistics.
Gary Steele
Gary is the president and CEO of Splunk
and a member of our board of directors.
Prior to joining Splunk in 2022, Gary was the
founding CEO of Proofpoint, where he led the
company’s growth from an early-stage start-
up to a leading, publicly traded security-as-a-
service provider.
Mark Woods
Splunk’s chief technical advisor in EMEA,
Mark has been an engineer, consultant,
entrepreneur and CTO. He helps executive
teams and international policymakers
understand the seismic potential of data-
driven approaches.
Spiros Xanthos
Spiros is the general manager of observability
at Splunk. Previously he was the CEO and
Founder of Omnition, an observability
platform for cloud-native applications that
pioneered no-sample tracing and co-created
OpenTelemetry until it was acquired by Splunk
in 2019.