Name: Optimize the Performance of Your Vector Database with Datadog and Weaviate
Start: 2024-06-12T16:17:00Z
End: 2024-06-12T16:17:50.000Z
Location: BrightTALK

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. 

Datadog Detect is a virtual mini-conference dedicated to helping security teams modernize detection and response by applying engineering best practices. Hear from industry experts for a series of technical talks on methods for optimizing recall and precision, improving detection logic, and leveraging classification approaches to help SOCs shift from reactive alerting to proactive threat defense.

Datadog Detect: Securing the Control Plane and Beyond

Building on the success of our inaugural report, we've analyzed real-world security data from tens of thousands of organizations.  In this roundtable discussion, security leaders from Datadog, Wolfpack Security, Light Frame, and Sourcegraph share insights from our 2025 DevSecOps Report and discuss how DevOps practices go hand-in-hand with strong security measures.

State of DevSecOps Livestream 2025

To better understand the vulnerabilities and threats facing modern DevOps organizations, Datadog analyzed security posture data from a sample of thousands of organizations that use AWS, Azure, or Google Cloud. In this roundtable discussion, security experts from Datadog were joined by Chris Farris, Cloud Security Evangelist and AWS Security Hero at PrimeHarbor Technologies, and Michael St.Onge, Head of Technical Services at Tamnoon.

State of Cloud Security Livestream

Hear how detection engineers, security leaders, and DevOps practitioners are transforming detection and response—from alert tuning to automation and Detection-as-Code. You’ll see real-world strategies from Datadog, Snowflake, FireMon, and more, and walk away with ideas you can apply immediately.

Datadog Detect

Stay secure. Act fast. Datadog Incident Response brings monitoring, paging, and resolution together in one streamlined workflow. With real-time observability built in, your team can make smarter decisions, respond faster, and reduce downtime — all without compromising security.

Reduce Downtime: One Platform for Monitoring, Paging, and Resolving Incidents

Nous avons le plaisir d’annoncer la publication de notre rapport State of DevSecOps 2025. Fort du succès de notre première édition,  pour vous offrir une vision actualisée des pratiques DevSecOps les plus efficaces. Notre session exclusive :
• Des insights approfondis sur l’alliance idéale entre pratiques DevOps modernes et sécurité robuste.
• Des stratégies concrètes  pour implémenter l'infrastructure en tant que code, les déploiements cloud automatisés et les identifiants éphémères dans les pipelines CI/CD afin de renforcer la sécurité et l’efficacité inter-équipe.
• Une discussion d’experts avec l'équipe sécurité de Datadog et Jean Burellier, Principal Software Engineer & Tech Lead Platform chez Sanofi

State of DevSecOps

新しくリリースされた Datadog Incident Response について詳しくご説明をするウェビナーを開催いたします。オブザーバビリティデータがインシデント対応プロセスに統合されたことで、インシデントの発生から解決に至るまでの過程がより早く、スムーズになったことをぜひご確認ください。

Datadog Incident Response の主な機能:
   • オンコールスケジュールとエスカレーション設定により、適切な担当者に確実に届くページング
   • ページングからのインシデント宣言をおこない、重要なコンテキストを即時に共有
   • チーム間でのシームレスなコラボレーションを実現し、検討内容やアクティビティをタイムラインに同期
   • MTTD (平均検出時間) と MTTR (平均復旧時間) をリアルタイムで追跡し、AI でポストモーテムをワンクリック生成

ダウンタイムを削減！監視、ページング、インシデント対応を一元化

As log volumes increase and observability architectures grow more complex, relying on fragmented legacy solutions makes agility, cost control, and predictability nearly impossible. Without a modern approach, teams struggle to adapt to evolving observability needs while staying within budget.

Watch this webinar to hear Datadog Engineers discuss how to to boost logging efficiency, scalability, and visibility - while maximizing resources. Discover how to:
• Control log volumes and costs through proactive processing and intelligent routing
• Optimize log retention and maximize storage for all logging use cases
• Reduce migration risks while transitioning to modern observability and security tools

Control log volumes and costs while boosting visibility

In this joint webinar with AWS and Datadog, we’ll demonstrate how to architect and monitor cloud migrations with frameworks from AWS, diagrams, and reports from Cloudcraft as well as monitoring and documentation with Datadog.

With a real-world migration example, we’ll show how all of these tools work together to support principles from both the AWS Cloud Adoption Framework and the Well-Architected Framework.

We’ll give you concrete examples of how to:

Compare and contrast before and after architecture diagrams using Cloudcraft
Implement AWS recommendations during migration
Managing and optimize cloud costs

Architecting your Cloud Migration: Focus on Monitoring Security and Cost management with AWS and Datadog

Discover how AWS-native tools, combined with Datadog’s observability platform, can streamline deployments, reduce the risks of modernization, and ultimately enable engineering teams to unlock the full potential of cloud-based productivity.

Using Observability to Support Your AWS Modernization Journey

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

When it comes to deploying AI solutions, vector databases are often used over traditional relational databases due to their efficiency and effectiveness in managing high-dimensional data. Weaviate is the cloud-native open source vector database that developers often turn to. Datadog’s Weaviate integration monitors the performance of your vector databases by surfacing metrics like resource usage and query performance; this allows you to optimize the performance of your databases so that you can build, deploy, and monitor AI solutions with confidence.

The following topics will be covered in more depth:

-Introduction to vector search 
-Building AI Native applications with Weaviate
-Monitoring health and performance of Weaviate databases

Optimize the Performance of Your Vector Database with Datadog and Weaviate

DevOps

Generative AI

IT Monitoring

Observability

Cloud

Dashboards

Application Monitoring

Vector Database

Database Management

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Optimize the Performance of Your Vector Database with Datadog and Weaviate

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