Name: Top 3 Ways to Use Datadog to Optimize your Cloud Environment
Start: 2024-06-12T19:47:00Z
End: 2024-06-12T19:47:54.000Z
Location: BrightTALK
Rating: 0

Datadog is an observability and security platform that unifies metrics, traces, logs, and security signals for centralized visibility on dynamic environments. By bringing together data from every tool in a company’s stack, Datadog enables customers to easily monitor the health and performance of their cloud infrastructure and applications at scale. Datadog also offers 700+ fully-supported integrations and preset service dashboards to provide immediate time to value. No matter the industry, scale, or use case, Datadog’s solutions help teams consolidate tool sprawl, break down silos, reduce operational costs, and remain agile in the market. 

To understand the security posture of applications and adoption of DevOps practices that enhance security in 2024, Datadog evaluated real-world data from tens of thousands of organizations in the inaugural State of DevSecOps Report. 

Join security experts from Datadog alongside Jay Beale, CTO at InGuardians and Jeff McJunkin, Founder of Rogue Valley Information Security, as they share insights into the report findings.

State of DevSecOps Livestream

In the 2023 Container Report, we examined more than 2.4 billion containers run by tens of thousands of Datadog customers to understand how they are scaling and supporting their containerized environments.

Join Datadog and Solomon Hykes from Docker and Dagger.io as they share insights on:
• Trends in adoption for technologies such as serverless containers and GPU-based compute on containers
• How organizations are managing container costs and resources through ARM-based compute and horizontal pod autoscaling
• Popular workload categories and languages for containers

Container Usage Report Livestream

To understand the state of cloud costs in 2024, Datadog evaluated real-world AWS cloud cost data from hundreds of organizations. The State of Cloud Costs report provides data-driven insights on how emerging and legacy technologies, patterns of cloud resource usage, and participation in discount programs contribute to cloud costs.

Join experts from Datadog alongside Dan Gaj, Senior Architect, Cloud Infrastructure & Financials at Cvent, as they share insights into the report findings such as:
• Opportunities for cost optimization in containerized environments
• Impact of discount programs on costs including Savings Plans and Reserved Instances
• Adoption of new technologies like Arm-based processors and GPUs that enable AI capabilities"

State of Cloud Costs Livestream

See how you can use the Datadog platform to scale DevOps across your organization. In this session, you'll learn how to:

• Scale out organizational awareness using Service Catalog and Datadog Teams 
• Simplify governance for effective collaboration by building out the right levels of access and roles
• Customize permissions and clone apps with a click to streamline your workflows
• Empower developers to self-serve internally, easing the burden from central SRE teams

Elevate DevOps with Full-Scale Observability

Organizations across industries are racing to adopt Large Language Models (LLMs) to enhance intelligent assistants, AIOps, natural language query interfaces, and much more. But running LLMs in production and at an enterprise scale comes with unique challenges.

For organizational leaders and enterprise executives driving digital transformation on AWS, this exclusive Fireside Chat with Sajid Mehmood and Sherry Marcus offers a unique opportunity to gain strategic insights on AI observability, innovation, and team leadership.

Join us as we explore cutting-edge topics such as building and monitoring AI-driven applications, processing large-scale workloads using Amazon Bedrock, coding faster with generative AI using Amazon Q Developer, and Datadog, and leading AI & ML Engineering teams through the ever-evolving AI landscape.

What You’ll Learn:

- Discover the most exciting AI, Machine Learning (ML), and Large Language Model (LLM) capabilities on AWS in 2024
- Learn how organizations are leveraging AWS services like Amazon Bedrock, Amazon Q Developer, and Datadog LLM Observability to ship innovative AI products, accelerate go-to-market strategies, and maintain application observability across diverse environments.
- Hear from AWS and Datadog executives about the top customer applications, industries, and use cases driving the future of AI
- Gain insights on how AI/ML Engineering and DevSecOps leaders can help upskill and train teams to adapt and thrive in this rapidly evolving space

AWS AI Observability Summit

Join Datadog and AWS for a webinar on LLM observability with a focus on monitoring Amazon Bedrock. You’ll learn how to get the most out of your large language mod els, as well as Datadog’s intuitive platform.

We’ll discuss generative AI application observability product topics including:

-Hallucinations and other common pitfalls
-Agentic workflows and end-to end observability
-Troubleshooting issues and ensuring response quality

In this session, you’ll learn about generative AI deployment on Amazon Bedrock as well how Datadog LLM Observability monitors and improves the performance and quality!

LLMs on Amazon Bedrock: Monitoring Chat, Agentic Applications and More

웨비나 내용:
진에어의 사례를 바탕으로 아래 내용을 데모와 함께 알아봅니다.


• 신세틱(Synthetic) 모니터링과 실제 사용자 모니터링(RUM)을 활용해 실시간으로 사용자 경험을 최적화하는 방법
• 엔드투엔드 분산 추적, 다양한 유형의 텔레메트리 간의 매끄러운 상호작용, ML 기반 인사이트 및 근본 원인 분석으로 신속히 트러블슈팅하는 방법
• 가동 시간, SLO, 코어 웹 바이탈, 전환율과 이탈률 등 사용자 여정을 손쉽게 분석하고 다른 팀과 원활히 협업하는 법

진에어와 함께하는 UX/프론트엔드 모니터링

クラウドの利用が高度化しサーバーレスやコンテナの利用でトラフィックの急な拡大にも対応が容易になりました。その一方で、悪意あるアクセスや攻撃も増えています。

そういった複雑化するクラウド環境を可視化し、オブザーバビリティを実現できるSaaSがDatadogです。そして、Datadogはセキュリティ脅威のリアルタイムな検知と対処にも効果を発揮します。

本ウェビナーでは、クラウド環境全体を可視化する方法、セキュリティ脅威をリアルタイムに検知して対処する方法、開発・運用チームとセキュリティチームが連携してより早い段階からセキュリティを強化する方法などを事例とデモを交えてご紹介いたします。

クラウド環境の可視化とセキュリティを両立する方法

애플리케이션과 인프라 전반에 대한 Observability와 보안 위협의 감지 및 대응까지 한 번에 통합 관리하는 방법을 알아봅니다! 모든 팀이 한곳에서 쉽고 빠르게 가시성을 얻고 보안 위협을 감지함으로써 보다 편리하고 안정적으로 서비스를 운영할 수 있는 방법에 대해 알아볼 수 있습니다. 
학습 내용:
• 애플리케이션 보안 위협 실시간 탐지 및 대응 방안
• 멀티 클라우드 및 컨테이너 환경의 컴플라이언스 준수 확인 방안
• 다양한 보안 로그의 중앙집중식 관리 방안
• 보안 위협 시 자동화 대응 방안

생방송 진행 중 현장 상황으로 인해 원활히 보여드리지 못한 데모 부분은 현재 정상적으로 작동하고 있습니다. 지금 바로 https://survey.datadoghq.net/  여기에서 데모로 서비스도 직접 공격해보고, MSA 환경에서 Datadog을 통해 보안을 강화하는 방법을 직관적으로 알아보세요!

마이크로서비스 아키텍처(MSA) 보안 Best Practice

Developers are building modern applications with a multi-tier, service-oriented architecture and releasing code faster than ever. However, this pace of innovation also comes with an increased risk of vulnerabilities getting shipped to production. To better understand the current vulnerabilities and threats facing modern DevOps organizations, Datadog evaluated real-world data from thousands of customers.

Join Datadog and Avi Douglen, CEO of Bounce Security & Vice-Chair of OWASP, as they share insights on:
• Which vulnerabilities really matter
• Which threats actually present a risk to your organization (but also which threats don't)
• What characteristics of your applications and APIs have an impact on their risk

Application Security Report Livestream

In this special CUBE presentation of the Google Cloud Marketplace Marvels Series, John Furrier, executive analyst at theCUBE Research, welcomes Steven Orban, VP of migrations, ISVs and marketplace at Google Cloud, and Yrieix Garnier, VP of products at Datadog.

Find out more about SiliconANGLE and theCUBE’s coverage of the latest tech events and news https://siliconangle.com/events/

They discuss the rapid growth of the Google Cloud Marketplace, driven by software companies such as Datadog, which provide comprehensive observability solutions. Garnier highlights Datadog’s deep integration with Google Cloud services, aiding in seamless cloud migrations and breaking down team silos. 

Check out Datadog on the Google Cloud Marketplace: https://console.cloud.google.com/marketplace/product/datadog-public/datadog?pli=1

The discussion emphasizes the importance of interoperability, reliability and effective integration of new cloud services, with successful case studies showcasing the strategic partnership between Google Cloud and Datadog in enhancing system performance and customer satisfaction.

Read more: https://siliconangle.com/2024/08/07/datadogs-software-integrations-quick-expansion-google-cloud-marketplace-marketplacemarvels/

Datadog and Google | Google Cloud Marketplace Marvels Series

Datadog Digital Experience Monitoring (DEM) allows you to gain full observability into frontend errors and performance issues on web and mobile applications, while providing relevant troubleshooting context for quick remediation and analytics to enhance the user experience. 

In this webinar, you'll learn how to:
• Optimize user experience by monitoring your applications proactively and in real-time with Synthetic Monitoring and Real User Monitoring (RUM) 
• Troubleshoot issues faster with end-to-end distributed tracing, seamless correlations between all types of telemetry, and machine learning-based insights and root-cause analysis
• Easily analyze and share insights such as uptime, SLO, Core Web Vitals, and conversion and drop-off rates with other teams

Enhance User Experience and Frontend Performance

Serverless technologies have transformed how businesses approach application development, and have become an integral part of organizations’ tool set. In the 2023 State of Serverless report, we analyzed telemetry data of our customers’ serverless workloads to uncover insights and trends in the serverless landscape. 

Learn from experts from the serverless community and members of the Datadog product team as they share insights on:
• The steady growth and adoption of serverless technologies across clouds and emerging platforms
• The benefits of migrating to serverless and container-based serverless workloads
• Best practices to deliver performant, secure, and cost-effective applications

State of Serverless Report Livestream

Get a deep dive and demo of Datadog APM. Chris Gatt, Lead SRE at Service Victoria joins to share how he utilizes Datadog Application Performance Monitoring to optimize performance across engineering teams.

Troubleshoot, Optimize, and Secure Applications Faster ft. Chris Gatt - Lead SRE, Service Victoria

As organizations increasingly leverage generative AI in their applications, ensuring end-to-end observability throughout the development and deployment lifecycle becomes crucial. This webinar showcases how to achieve comprehensive observability when deploying generative AI applications on AWS using Amazon Bedrock and Datadog.
Amazon Bedrock streamlines the development and scaling of large language models (LLMs), enabling teams to experiment with foundation models, customize them with their data, and securely integrate them into applications. Complementing this, Datadog’s solution provides deep insights into the behavior, performance, and cost of LLM-powered applications.
Through discussion and a live demo, attendees will learn how to monitor advanced LLM applications using Amazon Bedrock, while leveraging Datadog to monitor and troubleshoot real-world issues such as unexpected responses, model cost spikes, and performance degradations. The webinar highlights best practices for maintaining reliability, positive end-user experiences, and responsible AI practices throughout the application lifecycle.
By combining the power of Amazon Bedrock and Datadog, organizations can confidently deploy and scale generative AI applications while ensuring end-to-end observability, enabling them to unlock the full potential of this transformative technology.
In this webinar, you will learn:
● How Datadog can help solve for complexities created by generative AI and LLM’s
● How the Datadog SageMaker integration can access resource metrics—including CPU, GPU, memory, and network usage data—for all training and inference nodes. 
● Learn about Datadog’s 2 new OOTB dashboards to better monitor model endpoints and jobs, where customers receive immediate time to value by gaining insights into resource utilization, error, and latency metrics.

Monitor your AWS generative AI Stack with Datadog

In an environment of continuous change one constant remains: uncertainty. As the global economic outlook continues to be an area of concern, engineering leaders are facing increasing pressure to reduce IT costs. 

The primary methods of achieving cost efficiencies include reducing, controlling, and optimizing costs. Typically, businesses reduce spend first, but this can result in diminished productivity and output. Finding ways to control and optimize costs can actually be a more effective means of streamlining spending over the long term. 

In this webinar, you will hear from industry leaders at Citizens Bank, Samsung SmartThings and Stitch Fix as they share the best practices they instilled to:
• Build a cost-conscious culture
• Consolidate multiple monitoring tools
• Manage organization-wide cloud infrastructure to eliminate unused resources
• Optimize application resource consumption
• Decrease data storage costs

The Top 5 Ways to Reduce IT Costs with Monitoring and Observability

In the rapidly evolving landscape of software development, embracing innovation is critical. In this session, we will explore how Datadog’s pre-production observability and Tabnine’s Generative AI can help your team redefine the tempo and efficiency of your software development lifecycle.


We will cover the following topics in depth:

-How to accelerate releases with Tabnine's AI-assisted coding
-Advantages of single modal models
-The future of the software development lifecycle (SDLC)
-How Datadog’s observability into CI pipelines and IDEs further elevates developer productivity and minimizes time to market for your applications.

Join us to learn how you can redefine the pace and efficiency of your software releases.

Accelerate Release Velocity with Observability and Generative AI

Datadog's Generative AI integrations are designed to provide visibility into your applications and services that make use of large language models. With these integrations, you can effectively monitor the performance of your AI stack.

We will provide a detailed demonstration of how these integrations work and how the various pieces fit together as a whole when deploying models or developing your own. By taking a layered approach, we will delve into specific topics related to each layer, ensuring that the entire process is covered.

The webinar will cover the following topics in depth:
-Infrastructure
-Data Storage
-Serving and Deployment
-Models
Key Takeaways:
-The challenges of maintaining a competitive advantage in the evolving AI landscape
-An understanding of the AI tech stack layers and how they are used to build LLMs, GenAI solutions, and more.
-How Datadog’s suite of AI integrations help you optimize the health and performance of your AI tech stack.

Learn How to Monitor Your Generative AI Tech Stack with Datadog

Datadog’s unified observability platform provides SREs with the tools needed to help teams identify inefficiencies and optimize their cloud.

Watch this webinar to learn how to: 
• Get complete visibility into their infrastructure to understand performance and identify improvements across hosts, containers and serverless resources
• Optimize application performance and cost by monitoring your services’ health and code efficiency alongside your infrastructure’s resource consumption
• Create true cost ownership by leveraging north star unit economics and embedding cost data into the day-to-day of each team in your organization

Top 3 Ways to Use Datadog to Optimize your Cloud Environment

Observability

Data Analytics

Log Management

Application Management

Monitoring

Dashboards

Infrastructure Management

Troubleshooting

Metrics

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Top 3 Ways to Use Datadog to Optimize your Cloud Environment

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