Track Welcome: Operating Dynamic Infrastructure [FutureStack]

Dec 2, 20160 likes182 views

New Relic

Track Welcome: Operating Dynamic Infrastructure Speaker: Matthew Flaming, VP of Engineering, New Relic

Dynamic Infrastructure
Matthew Flaming, VP Site Engineering
@mflaming

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informational purposes only and should not be construed as an offer, commitment, promise or obligation on behalf of New Relic,
Inc. (“New Relic”) to sell securities or deliver any product, material, code, functionality, or other feature. Any information provided
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COMPLEXITY
(like entropy)
Grows Over Time

• HW issues

• OS upgrades

• Disk space

• CPU usage
• HW issues

• OS upgrades

• Disk space

• CPU usage

• Network issues
• Noisy neighbors

• OS upgrades

• Disk space

• CPU usage

• Network issues

• SOA complexity

• HW issues

• Noisy neighbors

• OS upgrades

• Disk space

• CPU usage

• Network issues

• SOA complexity

• Container issues

• 3+ year lifespan

• a few hosts

• quarterly releases
• 1+ year lifespan

• tens of hosts

• monthly releases
• 6 month lifespan

• hundreds of VMs

• weekly releases
• 1 month lifespan

• thousands of
containers

• daily releases

“oh sh*t, scale, complexity, and
volatility are eating us alive!”
“Our architecture needs to be built
for scale and volatility, while
reducing complexity.”
Dynamic
Infrastructure
dynamic
infrastructure

Dynamic Infrastructure is a Design Pattern
Phoenix Servers Compute as a
Uniform Resource

Standardized
Shutdown hooks
Standardized
Conﬁg
Standardized
Health checks
Horizontally
Scaled
Stateless
or
Replicated

Thank you.
Matthew Flaming, VP Site Engineering
@mflaming

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I am a data scientist with a strong foundation in economics and a deep passion for AI-driven problem-solving. My academic journey includes a B.Sc. in Economics from Jahangirnagar University and a year of Physics study at Shahjalal University of Science and Technology, providing me with a solid interdisciplinary background and a sharp analytical mindset. I have practical experience in developing and deploying machine learning and deep learning models across a range of real-world applications. Key projects include: AI-Powered Disease Prediction & Drug Recommendation System – Deployed on Render, delivering real-time health insights through predictive analytics. Mood-Based Movie Recommendation Engine – Uses genre preferences, sentiment, and user behavior to generate personalized film suggestions. Medical Image Segmentation with GANs (Ongoing) – Developing generative adversarial models for cancer and tumor detection in radiology. In addition, I have developed three Python packages focused on: Data Visualization Preprocessing Pipelines Automated Benchmarking of Machine Learning Models My technical toolkit includes Python, NumPy, Pandas, Scikit-learn, TensorFlow, Keras, Matplotlib, and Seaborn. I am also proficient in feature engineering, model optimization, and storytelling with data. Beyond data science, my background as a freelance writer for Earki and Prothom Alo has refined my ability to communicate complex technical ideas to diverse audiences.

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Understanding Complex Development ProcessesProcess mining Evangelist

The fifth talk at Process Mining Camp was given by Olga Gazina and Daniel Cathala from Euroclear. As a data analyst at the internal audit department Olga helped Daniel, IT Manager, to make his life at the end of the year a bit easier by using process mining to identify key risks. She applied process mining to the process from development to release at the Component and Data Management IT division. It looks like a simple process at first, but Daniel explains that it becomes increasingly complex when considering that multiple configurations and versions are developed, tested and released. It becomes even more complex as the projects affecting these releases are running in parallel. And on top of that, each project often impacts multiple versions and releases. After Olga obtained the data for this process, she quickly realized that she had many candidates for the caseID, timestamp and activity. She had to find a perspective of the process that was on the right level, so that it could be recognized by the process owners. In her talk she takes us through her journey step by step and shows the challenges she encountered in each iteration. In the end, she was able to find the visualization that was hidden in the minds of the business experts.

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Process Mining and Official Statistics - CBSProcess mining Evangelist

Johan Lammers from Statistics Netherlands has been a business analyst and statistical researcher for almost 30 years. In their business, processes have two faces: You can produce statistics about processes and processes are needed to produce statistics. As a government-funded office, the efficiency and the effectiveness of their processes is important to spend that public money well. Johan takes us on a journey of how official statistics are made. One way to study dynamics in statistics is to take snapshots of data over time. A special way is the panel survey, where a group of cases is followed over time. He shows how process mining could test certain hypotheses much faster compared to statistical tools like SPSS.

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How to regulate and control your it-outsourcing provider with process miningProcess mining Evangelist

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This lecture provides a foundational understanding of Artificial Intelligence (AI), exploring its history, core concepts, and real-world applications. Students will learn about intelligent agents, machine learning, neural networks, natural language processing, and robotics. The lecture also covers ethical concerns and the future impact of AI on various industries. Designed for beginners, it uses simple language, engaging examples, and interactive discussions to make AI concepts accessible and exciting. By the end of this lecture, students will have a clear understanding of what AI is, how it works, and where it's headed.

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Track Welcome: Operating Dynamic Infrastructure [FutureStack]

1. Dynamic Infrastructure Matthew Flaming, VP Site Engineering @mflaming

2. This document and the information herein (including any information that may be incorporated by reference) is provided for informational purposes only and should not be construed as an offer, commitment, promise or obligation on behalf of New Relic, Inc. (“New Relic”) to sell securities or deliver any product, material, code, functionality, or other feature. Any information provided hereby is proprietary to New Relic and may not be replicated or disclosed without New Relic’s express written permission. Such information may contain forward-looking statements within the meaning of federal securities laws. Any statement that is not a historical fact or refers to expectations, projections, future plans, objectives, estimates, goals, or other characterizations of future events is a forward-looking statement. These forward-looking statements can often be identified as such because the context of the statement will include words such as “believes,” “anticipates,”, “expects” or words of similar import. Actual results may differ materially from those expressed in these forward-looking statements, which speak only as of the date hereof, and are subject to change at any time without notice. Existing and prospective investors, customers and other third parties transacting business with New Relic are cautioned not to place undue reliance on this forward-looking information. The achievement or success of the matters covered by such forward-looking statements are based on New Relic’s current assumptions, expectations, and beliefs and are subject to substantial risks, uncertainties, assumptions, and changes in circumstances that may cause the actual results, performance, or achievements to differ materially from those expressed or implied in any forward-looking statement. Further information on factors that could affect such forward-looking statements is included in the filings New Relic makes with the SEC from time to time. Copies of these documents may be obtained by visiting New Relic’s Investor Relations website at ir.newrelic.com or the SEC’s website at www.sec.gov. New Relic assumes no obligation and does not intend to update these forward-looking statements, except as required by law. New Relic makes no warranties, expressed or implied, in this document or otherwise, with respect to the information provided.

3. A Brief History of Ops

4. A Brief History of Ops

5. A Brief History of Ops

6. A Brief History of Ops

7. COMPLEXITY (like entropy) Grows Over Time

8. • HW issues • OS upgrades • Disk space • CPU usage • HW issues • OS upgrades • Disk space • CPU usage • Network issues • Noisy neighbors • OS upgrades • Disk space • CPU usage • Network issues • SOA complexity • HW issues • Noisy neighbors • OS upgrades • Disk space • CPU usage • Network issues • SOA complexity • Container issues

9. • 3+ year lifespan • a few hosts • quarterly releases • 1+ year lifespan • tens of hosts • monthly releases • 6 month lifespan • hundreds of VMs • weekly releases • 1 month lifespan • thousands of containers • daily releases

10. EMBRACE The Problem

11. “oh sh*t, scale, complexity, and volatility are eating us alive!” “Our architecture needs to be built for scale and volatility, while reducing complexity.” Dynamic Infrastructure dynamic infrastructure

12. Dynamic Infrastructure is a Design Pattern Phoenix Servers Compute as a Uniform Resource

13. Know Your Herd

14. INFRASTRUCTURE As CODE

15. Spec Build Test Deploy Promote Monitor

16. CODE Defines INFRASTRUCTURE

17. Standardized Shutdown hooks Standardized Conﬁg Standardized Health checks Horizontally Scaled Stateless or Replicated

18. TOMORROW Is An Inexact Science

19. Thank you. Matthew Flaming, VP Site Engineering @mflaming

20. APPENDIX

21. WELCOME TO FUTURESTACK 16