IDC 1도 모르는 개발자가 DevOps를 만났을때

•

17 likes•2,173 views

주은 안

Technology

Agenda
1. Who am I?
2. The main problems we’ve solved
- Multi-Region deployment
- MSA (Orchestration, Service discovery, CI/CD, Secret management)
- SPA
3. Conclusion

Mathpresso - Backends Dev (Django)
MyMusicTaste - DataOps
MyMusicTaste - DevOps
Who am I?

Agenda
1. Who am I?
2. The main problems we solved
- Multi-Region deployment
- MSA (Orchestration, Service discovery, CI/CD, Secret management)
- SPA
3. Conclusion

Multi-region deployment
Top 5 countries our users are in are from all diﬀerent continents.
MMT is a truly global service.

Multi-region deployment
Database was our major concern
for us and multi region deployment

MSA
Polyglot programming
API Gateway registration
Getting secrets from vault cluster
Xray integration
…..etc..…

MSA
Cost of Fargate
ECS cluster with 342 running tasks
26 container instances of type m4.xlarge

MSA
Cost of Fargate
ECS: $3,806.40/month
Fargate: $4,930.87/month
A 30% increment in cost
for a similarly-sized cluster.

MSA
CI/CD
Build new Image of application
Push the latest image to ECR
Inject conﬁgurations to terraform
Create new revision task deﬁnition
Update ECS Service

MSA
Getting secrets when the application is initialized

SPA
The problems with s3 web hosting…
CORS, OG, SEO …. Etc
Should we build our server side rendering system?

SPA
Lambda@Edge
CloudFront
(mymusictaste.com)
SPA bucket
ALB
Ordered cache behaviour
Default cache behaviour

SPA
CloudFront
(mymusictaste.com)
Viewer request
Viewer response
Check headers
for recognizing bots
Build response
made of OG or SEO data
If request is from bots

SPA
CloudFront
(mymusictaste.com)
SPA bucket
Origin request
Origin response
Check the URI is for JS ﬁles
Change the URI
from the path requested by user to index.html
If the URI is not for JS ﬁles

Similar to IDC 1도 모르는 개발자가 DevOps를 만났을때

The Serverless experience is revolutionary and will grow to dominate the future of Cloud. Function-as-a-Service (FaaS) however—with its ephemeral, stateless, and short-lived functions—is only the first step. FaaS is great for processing-intensive, parallelizable workloads, moving data from A to B providing enrichment and transformation along the way. But it is quite limited and constrained in what use-cases it addresses well, which makes it very hard/inefficient to implement general-purpose application development and distributed systems protocols. What’s needed is a next-generation Serverless platform and programming model for general-purpose application development in the new world of real-time data and event-driven systems. What is missing is ways to manage distributed state in a scalable and available fashion, support for long-lived virtual stateful services, ways to physically co-locate data and processing, and options for choosing the right data consistency model for the job. This talk will discuss the challenges, requirements, and introduce you to our proposed solution: Cloudstate—an Open Source project building the next generation Stateful Serverless and leveraging state models such as Event Sourcing, CQRS, and CRDTs, running on Akka, gRPC, Knative, Kubernetes, and GraalVM, in a polyglot fashion with support for Go, JavaScript, Java, Swift, Scala, Python, Kotlin, and more.

Cloudstate—Towards Stateful Serverless

Jonas Bonér

Broadcast Music Inc - Release Automation Rockstars!

ghodgkinson

Serverless .NET on AWS

Wojciech Gawroński

Tracing in the world of micro services has become a standard with people using distributed tracers like Zipkin, Jaeger, Appdash etc. But, with so many different tracers, its confusing to choose one tracer and then painful to replace a tracer. That's where OpenTracing comes in. OT provides a consistent, vendor-neutral API to allow users to choose whatever distributed tracer they need and can change the tracer with just an O(1) operation.

Tracing Micro Services with OpenTracing

Hemant Kumar

Learn how Verizon is adopting the Amazon Aurora PostgreSQL-compatible edition for their mission-critical applications. Verizon has a history of adopting best of breed database technologies as they continue to serve their 140M+ customers. As Verizon moves its enterprise applications to the cloud, database performance and reliability are the key considerations. With heavy dependence on commercial databases, learn how a large enterprise like Verizon evaluated performance, reliability and operational characteristics of Amazon Aurora, and was able to create internal momentum behind adoption of open source technologies by showcasing early wins. This session also highlights best practices for using Amazon Aurora and the newly-announced RDS Performance Insights.

DAT332_How Verizon is Adopting Amazon Aurora PostgreSQL for Enterprise Workloads

Amazon Web Services

Cloudstate - Towards Stateful Serverless

Lightbend

AWS re:Invent 2016: Life Without SSH: Immutable Infrastructure in Production ...

Amazon Web Services

StrongLoop Overview

Shubhra Kar

What if you were told that within three months, you had to scale your existing platform from 1,000 req/sec (requests per second) to handle 300,000 req/sec with an average latency of 25 milliseconds? And that you had to accomplish this with a tight budget, expand globally, and keep the project confidential until officially announced by well-known global mobile device manufacturers? That’s what exactly happened to us. This session explains how The Weather Company partnered with AWS to scale our data distribution platform to prepare for unpredictable global demand. We cover the many challenges that we faced as we worked on architecture design, technology and tools selection, load testing, deployment and monitoring, and how we solved these challenges using AWS.

(ARC346) Scaling To 25 Billion Daily Requests Within 3 Months On AWS

Amazon Web Services

Fraud Detection and Prevention on AWS Speaker: Andrew Kane, Solutions Architect, AWS AI and real-time analytics are increasingly being used to quickly identify financial fraud. In this session, we will also give an overview of how to build and train a model to identify fraudulent card transactions from bona fide ones. We will also describe an architecture that allows you to feed live transaction data into a Machine Learning model to provide a real-time authentic / fraudulent classification of that transaction.

Fraud Detection and Prevention on AWS using Machine Learning

Amazon Web Services

Viadeos Segmentation platform with Spark on Mesos

Cepoi Eugen

Amazon EMR is one of the largest Hadoop operators in the world, enabling customers to run ETL, machine learning, real-time processing, data science, and low-latency SQL at petabyte scale. In this session, we introduce you to Amazon EMR design patterns such as using Amazon S3 instead of HDFS, taking advantage of both long and short-lived clusters, and other Amazon EMR architectural best practices. We talk about lowering cost with Auto Scaling and Spot Instances, and security best practices for encryption and fine-grained access control. Finally, we dive into some of our recent launches to keep you current on our latest features.

Design patterns and best practices for data analytics with amazon emr (ABD305)

Amazon Web Services

Achieve big data analytic platform with lambda architecture on cloud

Scott Miao

Fraud Detection with Amazon Machine Learning on AWS

Amazon Web Services

Understand the Microservices Architecture concepts Understand Event Sourcing and CQRS Understanding Domain Driven Design Understanding Functional Reactive Programming Understanding Distributed Transaction Management Understanding Microservices Messaging Setting up Micro services Infrastructure (API Gateway, Service Discovery, Load Balancer, Circuit Breaker) https://github.com/meta-magic/microservice_workshop

Microservices Part 3 Service Mesh and Kafka

Araf Karsh Hamid

SUMMARY : We all have the contradictory feeling to deliver not-so-bad projects, with no-so-bad performances. But what really is an perfectly optimized project ? For you : optimized PHP code & SQL queries For your boss : the customer who never complains For the customer : own experience on his workstation For the business : who really know and care ? For end-user : who can really know the end-user experience (could be millions of users) ? Without losing interest on technical aspects (PHP, MySql, Solr, Varnish, CDN, etc.) & softwares (new relic, jmeter, etc.), this presentation will send a feedback from real projects to : How to integrate performances within the project scope ? What & how to measure & collect smart metrics ? Enlarge the scope : from your dev workstation to the end-user… in china ! Experience level: Intermediate Session Track: Performance

Web performance optimization

Kaliop-slide

Top 8 WCM Trends 2010

David Nuescheler

The Scout24 Data Platform powers all reporting, ad hoc analytics and machine learning products at AutoScout24 and ImmobilienScout24. In this talk, we will take a technical deep dive into our modern, cloud-based big data platform. We will discuss our evolution of approaches to ingestion, ETL, access control, reporting, and machine learning with a focus on in-the-trenches learnings gained from our many failures and successes as we migrated from a traditional Oracle Data Warehouse to an AWS-based data lake.

The Scout24 Data Platform (A Technical Deep Dive)

RaffaelDzikowski

FINRA’s analytics platform unlocks the value in capital markets data by accelerating trade analytics and providing a foundation for machine learning at scale. The platform enables FINRA’s analysts to perform discovery on petabytes of trade data to identify instances of potential fraud, market manipulation, and insider trading. By centralizing all data in S3, FINRA’s architecture offers improved agility, scalability, and cost effectiveness. Analytics services such as Amazon EMR and Amazon Redshift have freed FINRA’s data scientists from the constraints of desktop tools, allowing them to apply machine learning techniques to develop and test new surveillance patterns. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator. At the end of this session, you’ll have an understanding of how to apply FINRA’s architecture to trade analytics and other financial services use cases, including meeting regulatory requirements such as the Consolidated Audit Trail (CAT) reporting.

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

Amazon Web Services

Architecting a Next Generation Data Platform

hadooparchbook

Similar to IDC 1도 모르는 개발자가 DevOps를 만났을때 (20)

Cloudstate—Towards Stateful Serverless

Broadcast Music Inc - Release Automation Rockstars!

Serverless .NET on AWS

Tracing Micro Services with OpenTracing

DAT332_How Verizon is Adopting Amazon Aurora PostgreSQL for Enterprise Workloads

Cloudstate - Towards Stateful Serverless

AWS re:Invent 2016: Life Without SSH: Immutable Infrastructure in Production ...

StrongLoop Overview

(ARC346) Scaling To 25 Billion Daily Requests Within 3 Months On AWS

Fraud Detection and Prevention on AWS using Machine Learning

Viadeos Segmentation platform with Spark on Mesos

Design patterns and best practices for data analytics with amazon emr (ABD305)

Achieve big data analytic platform with lambda architecture on cloud

Fraud Detection with Amazon Machine Learning on AWS

Microservices Part 3 Service Mesh and Kafka

Web performance optimization

Top 8 WCM Trends 2010

The Scout24 Data Platform (A Technical Deep Dive)

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

Architecting a Next Generation Data Platform

Recently uploaded

Data Cloud, More than a CDP by Matt Robison

Anna Loughnan Colquhoun

Advantages of Hiring UIUX Design Service Providers for Your Business

Pixlogix Infotech

Tata AIG General Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Rafal Los

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

UK Journal

Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

debabhi2

Join our latest Connector Corner webinar to discover how UiPath Integration Service revolutionizes API-centric automation in a 'Quote to Cash' process—and how that automation empowers businesses to accelerate revenue generation. A comprehensive demo will explore connecting systems, GenAI, and people, through powerful pre-built connectors designed to speed process cycle times. Speakers: James Dickson, Senior Software Engineer Charlie Greenberg, Host, Product Marketing Manager

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

DianaGray10

What are drone anti-jamming systems? The drone anti-jamming systems and anti-spoof technology protect against interference, jamming, and spoofing of the UAVs. To protect their security, countries are beginning to research drone anti-jamming systems, also known as drone strike weapons. The anti-jam and anti-spoof technology protects against interference, jamming and spoofing. A drone strike weapon is a drone attack weapon that can attack and destroy enemy drones. So what is so unique about this amazing system?

What Are The Drone Anti-jamming Systems Technology?

Antenna Manufacturer Coco

Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

Driving Behavioral Change for Information Management through Data-Driven Gree...

Enterprise Knowledge

This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.

Powerful Google developer tools for immediate impact! (2023-24 C)

wesley chun

What is a good lead in your organisation? Which leads are priority? What happens to leads? When sales and marketing give different answers to these questions, or perhaps aren't sure of the answers at all, frustrations build and opportunities are left on the table. Join us for an illuminating session with Cian McLoughlin, HubSpot Principal Customer Success Manager, as we look at that crucial piece of the customer journey in which leads are transferred from marketing to sales.

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

HampshireHUG

Developing An App To Navigate The Roads of Brazil

V3cube

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

Axa Assurance Maroc - Insurer Innovation Award 2024

The Digital Insurer

As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments

TrustArc

The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

Artificial Intelligence: Facts and Myths

Joaquim Jorge

Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

apidays

The value of a flexible API Management solution for Open Banking Steve Melan, Manager for IT Innovation and Architecture - State's and Saving's Bank of Luxembourg Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The value of a flexible API Management solution for O...

apidays

MySQL Webinar, presented on the 25th of April, 2024. Summary: MySQL solutions enable the deployment of diverse Database Architectures tailored to specific needs, including High Availability, Disaster Recovery, and Read Scale-Out. With MySQL Shell's AdminAPI, administrators can seamlessly set up, manage, and monitor these solutions, ensuring efficiency and ease of use in their administration. MySQL Router, on the other hand, provides transparent routing from the application traffic to the backend servers in the architectures, requiring minimal configuration. Completely built in-house and supported by Oracle, these solutions have been adopted by enterprises of all sizes for their business-critical applications. In this presentation, we'll delve into various database architecture solutions to help you choose the right one based on your business requirements. Focusing on technical details and the latest features to maximize the potential of these solutions.

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Miguel Araújo

Finology Group – Insurtech Innovation Award 2024

The Digital Insurer

Recently uploaded (20)

Data Cloud, More than a CDP by Matt Robison

Advantages of Hiring UIUX Design Service Providers for Your Business

Tata AIG General Insurance Company - Insurer Innovation Award 2024

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Exploring the Future Potential of AI-Enabled Smartphone Processors

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

What Are The Drone Anti-jamming Systems Technology?

Driving Behavioral Change for Information Management through Data-Driven Gree...

Powerful Google developer tools for immediate impact! (2023-24 C)

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

Developing An App To Navigate The Roads of Brazil

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments

Artificial Intelligence: Facts and Myths

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

Apidays New York 2024 - The value of a flexible API Management solution for O...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Finology Group – Insurtech Innovation Award 2024

IDC 1도 모르는 개발자가 DevOps를 만났을때

2. Agenda 1. Who am I? 2. The main problems we’ve solved - Multi-Region deployment - MSA (Orchestration, Service discovery, CI/CD, Secret management) - SPA 3. Conclusion

3. Mathpresso - Backends Dev (Django) MyMusicTaste - DataOps MyMusicTaste - DevOps Who am I?

10.

11. Managed Service

12.

13. Agenda 1. Who am I? 2. The main problems we solved - Multi-Region deployment - MSA (Orchestration, Service discovery, CI/CD, Secret management) - SPA 3. Conclusion

14.

15. Multi-region deployment Top 5 countries our users are in are from all diﬀerent continents. MMT is a truly global service.

16. Multi-region deployment Database was our major concern for us and multi region deployment

17. Multi-region deployment

18. Multi-region deployment

19. Multi-region deployment

20. Multi-region deployment

21. MSA

22. MSA Applications in the chaos

23. MSA

24. MSA

25. MSA Polyglot programming API Gateway registration Getting secrets from vault cluster Xray integration …..etc..…

26. MSA

27. MSA

28. MSA

29. MSA Fully managed container service

30. MSA Motivation to move to Fargate

31. MSA Constraints of Fargate

32. MSA Cost of Fargate ECS cluster with 342 running tasks 26 container instances of type m4.xlarge

33. MSA Cost of Fargate ECS: $3,806.40/month Fargate: $4,930.87/month A 30% increment in cost for a similarly-sized cluster.

34. MSA Service discovery

35. MSA CI/CD Build new Image of application Push the latest image to ECR Inject conﬁgurations to terraform Create new revision task deﬁnition Update ECS Service

36. MSA Secret management

37. MSA

38. MSA

39. MSA Getting secrets when the application is initialized

40. SPA

41. SPA The problems with s3 web hosting… CORS, OG, SEO …. Etc Should we build our server side rendering system?

42. SPA Lambda@Edge

43. SPA Lambda@Edge CloudFront (mymusictaste.com) SPA bucket ALB Ordered cache behaviour Default cache behaviour

44. SPA CloudFront (mymusictaste.com) Viewer request Viewer response Check headers for recognizing bots Build response made of OG or SEO data If request is from bots

45. SPA CloudFront (mymusictaste.com) SPA bucket Origin request Origin response Check the URI is for JS ﬁles Change the URI from the path requested by user to index.html If the URI is not for JS ﬁles

46. SPA CloudFront (mymusictaste.com) SPA bucket Origin request Origin response Check the URI is for JS ﬁles Change the URI from the path requested by user to index.html If the URI is not for JS ﬁles

47. Agenda 1. Who am I? 2. The main problems we solved - Multi-Region deployment - MSA (Orchestration, Service discovery, CI/CD, Secret management) - SPA 3. Conclusion

48. Conclusion

49. Conclusion

50. Conclusion

51. Conclusion scale out of teams ……

52. Conclusion

53. Conclusion

54. Conclusion Thanks for listening!

IDC 1도 모르는 개발자가 DevOps를 만났을때

Recommended

Recommended

More Related Content

Similar to IDC 1도 모르는 개발자가 DevOps를 만났을때

Similar to IDC 1도 모르는 개발자가 DevOps를 만났을때 (20)

Recently uploaded

Recently uploaded (20)

IDC 1도 모르는 개발자가 DevOps를 만났을때