One of the largest Airline in the world chose Dynatrace, here is the customer case.
Including:
Vision and Goal / Challenges / Requirements / Why Dynatrace is Unique / ROI and TCO / Rollout Status / Solution Screenshots
Dynatrace redefined monitoring with AI powered 3rd Generation APM, User Experience Monitoring & Continuous Improvement, Cloud-native, Full Stack, Auto Everything, End-to-End, Easiest to Implement, Use and Maintain
Dynatrace: New Approach to Digital Performance Management - Gartner Symposium...Michael Allen
New cloud stacks, containers, micro-services, automation and DevOps is driving an explosion of application code and infrastructure complexity. It's now nearly impossible to solve the Digital Application Performance Management challenges with traditional tools and approaches. Hear how we are delivering on our vision for Digital performance management, and how the role of digital virtual assistants might transcend into your enterprise. Meet D.A.V.I.S.
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.
Monitoring with Dynatrace Presentation.pptxKnoldus Inc.
Dynatrace is an APM solution designed to automatically measure the performance of an application or micro-service, discover the topology and dependencies of your architecture, and determine if a problem is in the code or in the software and hardware infrastructure supporting your application. It is a one-end solution to diagnosing all stacks of your application with logs, metrics and traces, and that too, in real-time.
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.
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain the term SRE (Site Reliability Engineering) and introduce key metrics for an SRE team SLI, SLO, and SLA.
Youtube Channel here: https://www.youtube.com/playlist?list=PLm_COkBtXzFq5uxmamT0tqXo-aKftLC1U
Dynatrace: New Approach to Digital Performance Management - Gartner Symposium...Michael Allen
New cloud stacks, containers, micro-services, automation and DevOps is driving an explosion of application code and infrastructure complexity. It's now nearly impossible to solve the Digital Application Performance Management challenges with traditional tools and approaches. Hear how we are delivering on our vision for Digital performance management, and how the role of digital virtual assistants might transcend into your enterprise. Meet D.A.V.I.S.
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.
Monitoring with Dynatrace Presentation.pptxKnoldus Inc.
Dynatrace is an APM solution designed to automatically measure the performance of an application or micro-service, discover the topology and dependencies of your architecture, and determine if a problem is in the code or in the software and hardware infrastructure supporting your application. It is a one-end solution to diagnosing all stacks of your application with logs, metrics and traces, and that too, in real-time.
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.
According to Google, SRE is what you get when you treat operations as if it’s a software problem. In this video, I briefly explain the term SRE (Site Reliability Engineering) and introduce key metrics for an SRE team SLI, SLO, and SLA.
Youtube Channel here: https://www.youtube.com/playlist?list=PLm_COkBtXzFq5uxmamT0tqXo-aKftLC1U
SRE (service reliability engineer) on big DevOps platform running on the clou...DevClub_lv
SRE (service reliability engineer). The talk is to explain the SRE philosophy and the principles of production engineering and operations in clouds.
(Language – English)
Pavlo is ADOP (Accenture DevOps Platform) Service Reliability Team Lead, SRE practitioner. Has more then 18 years of IT experience in Ops and Dev.
Synthetic Monitoring Deep Dive - AppSphere16AppDynamics
Learn how to monitor end-to-end workflows from every corner of the world. Hear the basics of AppDynamics Synthetic Monitoring and its integration in the AppDynamics Unified Monitoring Platform. Dive into scripting and how it allows monitoring of complex end-to-end workflows via a set of real-world examples describing best practices and tips to write better scripts and avoid common pitfalls.
Key takeaways:
o What AppDynamics Synthetic Monitoring can do today, and where the technology is going
o See how Synthetic Monitoring complements Real User Monitoring and APM
o Overview of the best tools available to help you build scripts quickly and reliably
o Tips for handling complex websites, avoiding common pitfalls, and leveraging synthetic monitoring to run WebDriver scripts
For more information, go to: www.appdynamics.com
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.
See how to Assess Your Application: https://www.castsoftware.com/use-cases/application-assessment
Assessing application development like the rest of the business
Well overdue, it is time to measure application development and
maintenance the same way as the rest of the business, based on not just how much work someone does, but how well they do the work. As we know, looking to see if the code works as expected is only a single measurement. Knowing how easy it will be to maintain over time, how flexible it is to change as required by business changes, how quickly new team members can understand the code and get working on it and how easily the application can be tested are just some of the things that we need to look at in order to understand the real quality of the work being done by application development teams. When these measurements are combined with ways of counting the productivity (quantity) of development teams, we can get a real understanding of how well the teams are performing and what return is being realized from the investment. These measurements can be assessed both for in-house development organizations as well as the work being done by outsourcers.
The applications delivered by IT are a significant differentiator between competitors and therefore it needs to be managed as a core business process. Held up against corporate standards and no matter how or where the development work is done, it must be done well and the resulting applications need to be able to withstand time.
See how to Assess Your Application: https://www.castsoftware.com/use-cases/application-assessment
1. Overview of DevOps
2. Infrastructure as Code (IaC) and Configuration as code
3. Identity and Security protection in CI CD environment
4. Monitor Health of the Infrastructure/Application
5. Open Source Software (OSS) and third-party tools, such as Chef, Puppet, Ansible, and Terraform to achieve DevOps.
6. Future of DevOps Application
Async API and Solace: Enabling the Event-Driven FutureSolace
Fran Méndez, founder of AsyncAPI, and Jonathan Schabowsky, senior architect at Solace, explain how the two companies are working together in this presentation from Gartner AADI.
What is observability and how is it different from traditional monitoring? How do we effectively monitor and debug complex, elastic microservice architectures? In this interactive discussion, we’ll answer these questions. We’ll also introduce the idea of an “observability pipeline” as a way to empower teams following DevOps practices. Lastly, we’ll demo cloud-native observability tools that fit this “observability pipeline” model, including Fluentd, OpenTracing, and Jaeger.
Getting started with Site Reliability Engineering (SRE)Abeer R
"Getting started with Site Reliability Engineering (SRE): A guide to improving systems reliability at production"
This is an intro guide to share some of the common concepts of SRE to a non-technical audience. We will look at both technical and organizational changes that should be adopted to increase operational efficiency, ultimately benefiting for global optimizations - such as minimize downtime, improve systems architecture & infrastructure:
- improving incident response
- Defining error budgets
- Better monitoring of systems
- Getting the best out of systems alerting
- Eliminating manual, repetitive actions (toils) by automation
- Designing better on-call shifts/rotations
How to design the role of the Site Reliability Engineer (who effectively works between application development teams and operations support teams)
Analyze key aspects to be considered before embarking on your cloud journey. The presentation outlines the strategies, approach, and choices that need to be made, to ensure a smooth transition to the cloud.
Microservices Architectures: Become a Unicorn like Netflix, Twitter and Hailogjuljo
Full day workshop about Microservices Architectures, from the basis to advanced topics like Service Discovery, Load Balancing, Fault Tolerance and Centralized Logging.
Many technologies are involved, like Spring Cloud Netflix, Docker, Cloud Foundry and ELK.
A separate deck describes all the lab exercises.
Microservices, DevOps, and Continuous DeliveryKhalid Salama
Continuous Delivery is the ability to get software changes - including new features, enhancements, configuration changes, and bug fixes - into production safely and quickly, in a sustainable way. In these slides, I am giving a very high-level introduction to microservices architecture, and why it is considered as enabler to continuous delivery. We cover the key characteristics of a microservice, some common concepts, architectural patterns, and implementation guidelines. In addition, we quickly cover the main concepts and activities in DevOps, which the Application Lifecycle Management process to support continuous delivery.
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
Solving 21st Century App Performance Problems Without 21 PeopleDynatrace
Delivering your application to users quickly and efficiently is vital to meeting customer expectations and revenue goals. As systems become ever more distributed and complex, this gets more and more difficult. Even a slight delay in identifying and resolving application performance issues could mean lost revenue and unhappy customers.
Because of their complex, distributed IT environment, 200+ production enterprise web services and associated middleware tools, Brian Bemiller, Leader of the SOA/Middleware Team at Westfield Insurance, and his team needed an APM solution that would improve end-user experience, reduce problem resolution time and move them from a reactive to proactive mode.
Join Brian Bemiller to find out how Westfield Insurance:
Fixed a problem that caused a 2 minute user death spiral that 20 people couldn’t fix
Reduced the number of resources and time needed to solve problems
Improved MTTR from ‘too difficult to solve’ to 'solved in just minutes'
Realized 4x response time improvement to rate policies
Provided the business with application performance and quality visibility that resonates with them
View the full Webcast here: http://cpwr.it/GOcIk
SRE (service reliability engineer) on big DevOps platform running on the clou...DevClub_lv
SRE (service reliability engineer). The talk is to explain the SRE philosophy and the principles of production engineering and operations in clouds.
(Language – English)
Pavlo is ADOP (Accenture DevOps Platform) Service Reliability Team Lead, SRE practitioner. Has more then 18 years of IT experience in Ops and Dev.
Synthetic Monitoring Deep Dive - AppSphere16AppDynamics
Learn how to monitor end-to-end workflows from every corner of the world. Hear the basics of AppDynamics Synthetic Monitoring and its integration in the AppDynamics Unified Monitoring Platform. Dive into scripting and how it allows monitoring of complex end-to-end workflows via a set of real-world examples describing best practices and tips to write better scripts and avoid common pitfalls.
Key takeaways:
o What AppDynamics Synthetic Monitoring can do today, and where the technology is going
o See how Synthetic Monitoring complements Real User Monitoring and APM
o Overview of the best tools available to help you build scripts quickly and reliably
o Tips for handling complex websites, avoiding common pitfalls, and leveraging synthetic monitoring to run WebDriver scripts
For more information, go to: www.appdynamics.com
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.
See how to Assess Your Application: https://www.castsoftware.com/use-cases/application-assessment
Assessing application development like the rest of the business
Well overdue, it is time to measure application development and
maintenance the same way as the rest of the business, based on not just how much work someone does, but how well they do the work. As we know, looking to see if the code works as expected is only a single measurement. Knowing how easy it will be to maintain over time, how flexible it is to change as required by business changes, how quickly new team members can understand the code and get working on it and how easily the application can be tested are just some of the things that we need to look at in order to understand the real quality of the work being done by application development teams. When these measurements are combined with ways of counting the productivity (quantity) of development teams, we can get a real understanding of how well the teams are performing and what return is being realized from the investment. These measurements can be assessed both for in-house development organizations as well as the work being done by outsourcers.
The applications delivered by IT are a significant differentiator between competitors and therefore it needs to be managed as a core business process. Held up against corporate standards and no matter how or where the development work is done, it must be done well and the resulting applications need to be able to withstand time.
See how to Assess Your Application: https://www.castsoftware.com/use-cases/application-assessment
1. Overview of DevOps
2. Infrastructure as Code (IaC) and Configuration as code
3. Identity and Security protection in CI CD environment
4. Monitor Health of the Infrastructure/Application
5. Open Source Software (OSS) and third-party tools, such as Chef, Puppet, Ansible, and Terraform to achieve DevOps.
6. Future of DevOps Application
Async API and Solace: Enabling the Event-Driven FutureSolace
Fran Méndez, founder of AsyncAPI, and Jonathan Schabowsky, senior architect at Solace, explain how the two companies are working together in this presentation from Gartner AADI.
What is observability and how is it different from traditional monitoring? How do we effectively monitor and debug complex, elastic microservice architectures? In this interactive discussion, we’ll answer these questions. We’ll also introduce the idea of an “observability pipeline” as a way to empower teams following DevOps practices. Lastly, we’ll demo cloud-native observability tools that fit this “observability pipeline” model, including Fluentd, OpenTracing, and Jaeger.
Getting started with Site Reliability Engineering (SRE)Abeer R
"Getting started with Site Reliability Engineering (SRE): A guide to improving systems reliability at production"
This is an intro guide to share some of the common concepts of SRE to a non-technical audience. We will look at both technical and organizational changes that should be adopted to increase operational efficiency, ultimately benefiting for global optimizations - such as minimize downtime, improve systems architecture & infrastructure:
- improving incident response
- Defining error budgets
- Better monitoring of systems
- Getting the best out of systems alerting
- Eliminating manual, repetitive actions (toils) by automation
- Designing better on-call shifts/rotations
How to design the role of the Site Reliability Engineer (who effectively works between application development teams and operations support teams)
Analyze key aspects to be considered before embarking on your cloud journey. The presentation outlines the strategies, approach, and choices that need to be made, to ensure a smooth transition to the cloud.
Microservices Architectures: Become a Unicorn like Netflix, Twitter and Hailogjuljo
Full day workshop about Microservices Architectures, from the basis to advanced topics like Service Discovery, Load Balancing, Fault Tolerance and Centralized Logging.
Many technologies are involved, like Spring Cloud Netflix, Docker, Cloud Foundry and ELK.
A separate deck describes all the lab exercises.
Microservices, DevOps, and Continuous DeliveryKhalid Salama
Continuous Delivery is the ability to get software changes - including new features, enhancements, configuration changes, and bug fixes - into production safely and quickly, in a sustainable way. In these slides, I am giving a very high-level introduction to microservices architecture, and why it is considered as enabler to continuous delivery. We cover the key characteristics of a microservice, some common concepts, architectural patterns, and implementation guidelines. In addition, we quickly cover the main concepts and activities in DevOps, which the Application Lifecycle Management process to support continuous delivery.
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
Solving 21st Century App Performance Problems Without 21 PeopleDynatrace
Delivering your application to users quickly and efficiently is vital to meeting customer expectations and revenue goals. As systems become ever more distributed and complex, this gets more and more difficult. Even a slight delay in identifying and resolving application performance issues could mean lost revenue and unhappy customers.
Because of their complex, distributed IT environment, 200+ production enterprise web services and associated middleware tools, Brian Bemiller, Leader of the SOA/Middleware Team at Westfield Insurance, and his team needed an APM solution that would improve end-user experience, reduce problem resolution time and move them from a reactive to proactive mode.
Join Brian Bemiller to find out how Westfield Insurance:
Fixed a problem that caused a 2 minute user death spiral that 20 people couldn’t fix
Reduced the number of resources and time needed to solve problems
Improved MTTR from ‘too difficult to solve’ to 'solved in just minutes'
Realized 4x response time improvement to rate policies
Provided the business with application performance and quality visibility that resonates with them
View the full Webcast here: http://cpwr.it/GOcIk
Unified Monitoring Webinar with Dustin WhittleAppDynamics
Listen to the recorded webinar here: https://www.appdynamics.com/lp/q3-unified-monitoring-webinar/
Dustin Whittle, AppDynamics' Director of Web Engineering, covers
-the problems and struggles with monitoring tools today
-how to identify and resolve critical issues before your customers are impacted
-how AppDynamics provides one approach for unified monitoring
And much, much more!
Keynote presentation from CMG Conference explaining the challenges in management and now monitoring and business visibility provided by modern APM tools is critical to business execution
3 areas of Digital Performance Management:
-Application Performance Management
-Digital Experience Management
-Cloud/Container/Infrastructure Monitoring
Gain New Insights by Analyzing Machine Logs using Machine Data Analytics and BigInsights.
Half of Fortune 500 companies experience more than 80 hours of system down time annually. Spread evenly over a year, that amounts to approximately 13 minutes every day. As a consumer, the thought of online bank operations being inaccessible so frequently is disturbing. As a business owner, when systems go down, all processes come to a stop. Work in progress is destroyed and failure to meet SLA’s and contractual obligations can result in expensive fees, adverse publicity, and loss of current and potential future customers. Ultimately the inability to provide a reliable and stable system results in loss of $$$’s. While the failure of these systems is inevitable, the ability to timely predict failures and intercept them before they occur is now a requirement.
A possible solution to the problem can be found is in the huge volumes of diagnostic big data generated at hardware, firmware, middleware, application, storage and management layers indicating failures or errors. Machine analysis and understanding of this data is becoming an important part of debugging, performance analysis, root cause analysis and business analysis. In addition to preventing outages, machine data analysis can also provide insights for fraud detection, customer retention and other important use cases.
PPT Presented at Morton's Steak House in San Francisco. It covers the Monitoring Redefined message as well as how Dynatrace transformed to maintain market share in the new world.
Monitoring Consumer Digital ExperienceThousandEyes
Internet-facing applications rely on multiple dependencies for delivery, including ISPs, DNS, CDNs and 3rd party APIs. If you’re tasked with keeping your applications available and high-performing, you need to know when and where issues occur across the delivery network, so you can rapidly address them.
ThousandEyes enables you to monitor Internet-facing applications from the vantage of your consumer and SMB customers. This presentation will show you how you can improve your customers’ digital experience, reduce churn and improve MTTR.
An overview of Transpara's Visual KPI software for real-time dashboards, KPIs and alerts. Visual KPI is a single lightweight layer that lets you view operations and other data from many data sources at the same time, visualized in real-time on any device.
How the Big Data of APM can Supercharge DevOpsCA Technologies
In the age where applications reign supreme, your organizations must be agile in application performance management and app development in order to meet the market demands and stay competitive. Even with mature APM solutions, developer, test and operations teams are strained by operational complexity, accelerated release schedules, and big data challenges to quickly find the root cause of issues affecting end user experience.
The power of advanced analytics and data science can help us make the most of the vast cache of APM data we collect and help our DevOps teams supercharge user experience. It’s time to take some of the load off of our humans and let technology make it easier to focus on meaningful changes in user, application and system behavior. Analytics are becoming a valuable component of APM solutions to redefine triage, improve application quality, and delight the end-user.
In a webcast on August 7th, 2014, Ken Godskind, Chief blogger and Analyst, APMExaminer.com shared how the big data of APM can supercharge your DevOps transformation. Chris Kline, Senior Director, CA Technologies followed Ken and discussed how the Advanced Behavior Analytics capability of CA APM can assist in this journey.
Ken and Chris used this slide set during the webcast which can be viewed at http://goo.gl/TZYEuq
Practical Tips for Ops: End User MonitoringDynatrace
Practical Tips for Ops: End User Monitoring
Watch replay here: https://info.dynatrace.com/apm_wc_devops_journey_series_end_user_monitoring_na_registration.html
Companies that have adopted DevOps Best Practices have 2555x faster lead times* in delivering new features to their end users. However, speed of delivery is not the only success metric! Success must also be measured on how end-users react to the speed of innovation.
Getting insights into how your end-users react to the changes you deploy allows you to share valuable feedback to the Dev and Biz teams. The teams can then see clearly how their changes impacted end-users and where fine tuning can improve infrastructure performance.
In this webcast Andreas Grabner, Chief DevOps Activist, and Brian Chandler, Systems Engineer, share practical tips that IT groups can start to implement quickly. You'll learn:
• Best approach for monitoring end-user mobile versus desktop versus tablet versus service end-points
• How to evaluate network bandwidth requirements by app, service and feature; to better understand and optimize resource consumption
• How to optimize your delivery chain in depth by understanding who is using your app, where, and on what device
• Clear view on which features are being used the most, the least, and what kind of behavior can be observed that is useful in tuning performance
If you are stuck in analysis paralysis, get insights that you can apply today!
*In addition, companies using DevOps are two times more likely to exceed profitability, market share and productivity goals (from the State of DevOps report by Puppet Labs 2016)
Similar to Customer case - Dynatrace Monitoring Redefined (20)
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
2. confidential
Customer’s vision & goal
Goal = monitor infrastructure
+ apps + users across 15,500
app/web servers in 5 months
our customers
a service
impact
3. confidential
Understand
User & Business
Impact
Know
Performance
Issues
Prioritise
Resolutions
Siloed tooling
& data
Faster
Troubleshoot
Customer’s challenges
See how
Applications
Interact
End-to-End
Visibility &
Control
Labour Intense &
Manual Processes
• 76% of high severity issues were identified by customers (only 24% detected by previous monitoring tools)
• High severity issues would result in 50+ people on a “war room “ bridge
• Multiple tools used by different silos – long recovery times from issues and no proactiveness
4. confidential
User Experience
Application
Services & processes
Platform
IaaS
Physical
Real-time application topology discovery
Anomaly detection
Business impact analysis
Problem and root-cause analysis
BizDevOps insights & analytics
Automation & Orchestration Collaboration & Workflow Big data analytics
API integrations
Requirements
5. Better data makes Dynatrace artificial intelligence and automation possible
Mobile
Application
Code
Database
Network
Container
Micro-service
Browser
SyntheticServer
Mainframe
Log & Events
API
Cloud
high fidelity, full stack data
All transactions, all the time
Connected end-to-end
PurePath + Smartscape
Real-time dependency detectionAuto instrumentation
Automated workflows
Automated problem detection
Automated root cause analysis
Causation gives answers
Automation
Automate the effort
Natural language interface
Automated business impact
OneAgent/Singleproduct
Advanced analytics
Expert knowledge built-in
Self learning A.I.
Why ?
6. confidential
100x faster
to implement
Max coverage, lowest
cost
ROI and TCO validated by customer
Faster
implementation
Lower resources
overhead Reduced MTTR Fewer tools
• Single agent
implementation
• Full stack, continuous
auto-discovery
• Auto-baselining and
dependency mapping
1/10th of the people
Easiest & lowest TCO
• AI-based problem
identification
• Automated root cause
analysis
• Pre-configured
dashboards, easy agile
customization
20x faster MTTR
Optimal UX
• Single root cause
identified for fast
remediation
• Understand business
impact – focus on
what matters
• Auto-remediation
with accuracy &
confidence
All-in-one,
Nothing like it
• End-to-end: all users,
all apps, all digital
channels
• Full-stack: all data, all
layers, all technologies
• One complete source
of truth, vs a “suite”
of disparate data sets
1/10th the TCO of other solutions
Scalability
100x scale
Grow w/out barriers
• Horizontally scaling
cluster architecture
• Scales beyond 100,000
hosts
• Only solution with true
high availability for
web-scale
7. Goal = monitor infrastructure + apps + users across 15,500
app/web servers in 5 months
First install = 1,870 web/app servers instrumented in 6 hours
3 months in = deployed across top 21 most critical apps and 9,361 web/app servers
Rollout status
Rollout goal was achieved within the 5 months given!
11. 500+ engineers in R&D makes it all possible
66% more than nearest competitor
# of customer
reported incidents
is now negligible
33% faster revenue
realization
Test cycle times
reduced by 4x
Constantly innovating
7 years a leader in Gartner
#1 market share leader
OpenShift Primed Partner
AWS Advanced Technology Partner
Technology partner
Docker Certified
Azure Partner
OpenStack Certified
3x more market shares than others MQ leaders
Realistic results
Editor's Notes
(they literally called out that we “redefined monitoring” in the way Dynatrace works) they were ready to have more meetings and sessions with us.
Let’s dig into artificial intelligence more deeply so that we don’t confuse the buzz word with what Dynatrace actually delivers today. It’s important to understand the foundational underpinnings of Dynatrace AI and it starts with the fact that Dynatrace captures all transactions –all users – all the time // as well as all of the associated full-stack analytics. // This in turn provides the type of 100% high-fidelity data necessary to enable real-time dependency detection and ultimately…self-learning Artificial Intelligence. //
This approach to artificial intelligence leads to true Problem Detection at the root cause, not just more robust incident detection. Meaning that Dynatrace will automatically point to the likely cause of a problem and eliminate the alert storm that is typically the result of the many minor incidents that are contributing to the problem but not the problem itself.
And all of this is fully automated and can be accessed via dashboards, natural language interfaces like Alexa and Siri or you can hook it up to Slack and leverage bi-directional instant messaging.
No other monitoring tool can achieve this. Their data is spotty with snapshots, sampling and it’s not truly full stack. With spotty data, A.I. algorithms are useless. Without A.I., everything must be done with human operators. This does not scale.
Use this slide to demonstrate that deployments with Dynatrace are different. They are fast – fully automated. Ultra-low TCO.
We have thousands of customers around the world that trust us and for as long as the Gartner APM magic quadrant has existed, Dynatrace has been a Leader in that quadrant…a fact that no other company can claim. Now let’s look at some relevant examples of how Dynatrace can support your specific use cases…
