At the Datadog Summit, you will meet and learn from fellow community members, contributors, and Datadog staff. You'll get the latest product updates, learn how your fellow community are using Datadog to build cultures of observability, and participate in open discussions and guided training sessions. In the hands-on training, we'll walk through best practices for building better dashboards and alerts, developing custom agent integrations, and monitoring and instrumenting your containerized applications.
More sessions to be announced soon...
etc.venues Prospero House
241 Borough High St
London SE1 1GA, UK
Welcome (Ilan Rabinovitch)
Keynote (Amit Agarwal)
Workshop: Datadog 101
Workshop: Hands on with Distributed Tracing and Datadog APM
Workshop: Reducing MTTR with Log Management
Workshop: Containers and Kubernetes Monitoring Best Practices
Reception and NetworkingMarks Bar at the Hixter (16 Great Guildford St)
Throughout his 15 years of experience in enterprise software, Amit has worked in various business strategy and technical management roles to bring new products to market. Before Datadog, Amit was the Director of Product Management at Quest Software (now Dell), where he led the team responsible for application performance monitoring. Previously, Amit held product management roles at enterprise software firms including Datamirror (now IBM) and Embarcadero Technologies, and technical roles with 3D-medical imaging and mobile encryption software companies. Amit holds an MBA from the Schulich School of Business and a Masters in Computer Science from Dalhousie University.
Kirk Kaiser is a Developer Evangelist at Datadog, where he focuses on helping developers build more reliable, performant code with APM. Previously, he was the lead backend developer at Triller, scaling the app from zero to millions of users, and handling the traffic from being in the top 100 of iOS and Android stores at the same time. Kirk is also the author of a book teaching Python programming through art instead of print statements, called Make Art With Python.
Workshop: Tracing is a specialized form of logging that is designed to work effectively in large, distributed environments. When done right, tracing follows the path of a request across process and service boundaries. This provides a big step up in application observability and can help inform a developer why certain requests are slow, or why they might have behaved unexpectedly. This tutorial will familiarize users with the benefits of tracing and describe a general toolkit for emitting traces from applications in a minimally intrusive way. We will walk through a simple example app, which receives an HTTP request, and gradually instrument it to be observable via traces. We will discuss language constructs that can generate traces—namely decorators, monkey-patching and context managers—and give users pointers on how they might add tracing to their own applications and libraries. In the process, users will become familiar with the existing standards for modeling traces, and some of the challenges involved in adhering to this model in a distributed, asynchronous environment.
Hands-On with Distributed Tracing and Datadog APM
Matt Williams is a Technical Evangelist on Datadog's community team. He is passionate about the power of monitoring and metrics to make large-scale systems stable and manageable. So he tours the country speaking and writing about monitoring with Datadog. When he's not on the road, he's coding. You can find Matt on Twitter at @Technovangelist. Session: Workshop: Datadog 101.
Workshop: Transform yourself from a monitoring novice to a Datadog expert with hands-on training led by the engineers who build, maintain, and support Datadog. We’ll share best practices for building insightful dashboards and visualizations and tips for effective alerting and dive into container monitoring with Autodiscovery. Attendees will leave with hands-on experience using these techniques that they can bring home to their own environments for more effective monitoring.
Ilan Rabinovitch leads product and community teams at Datadog. Prior to joining Datadog, Ilan spent a number of years leading infrastructure and reliability engineering teams at organizations such as Ooyala and Edmunds.com.
Meghan is a product manager focused on Datadog's alerting and reporting platform. When she's not working with customers or calculating uptime, she's walking her dog around Brooklyn and tending to a surprisingly thriving garden.
Michael Gerstenhaber is a product director at Datadog, building products for Process and Container monitoring, and working with our IoT partners to design solutions for monitoring smart devices. Michael was previously an engineer at Cisco Systems where he contributed to a series of network and data center management tools, and later made a stopover in the video game industry, serving as director of product at Happy Cloud.
Managing and scaling workloads on Kubernetes
Brian manages teams and fixes problems. He is currently managing Intercom's internal developer productivity team, who owns Intercom's continuous integration, deployments, and developer environments.
Renaud is a product director at Datadog focused on log management. Prior to joining Datadog, Renaud was co-founder & Chief Product Officer at Logmatic.io (acquired by Datadog). Prior to Logmatic.io, Renaud lead development of high performance Business Intelligence solutions for financial institutions.
Pierre is a technical writer with the Datadog Community team. He began his career as a technical evangelist at Logmatic.io. Through documentation and outreach, he strives to ensure the highest level of communication and understanding between products and people.
Workshop: Gaining insights into application behavior by combining metrics, tracing, and logs can help you reduce mean time to detection and resolution of operational incidents, allowing you to address issues before your users notice service impact. With the help of hands-on labs, this workshop will take attendees from beginner to expert in log management with Datadog. Participants will walk through best practices for log collection and processing, and then dive into scenarios that will build experience with troubleshooting and monitoring techniques. Attendees will leave with hands-on experience with logging, plus strategies that will provide insights into application behavior and user experiences.
Reducing MTTR with Log Management
Anatoly is an engineer on Zendesk’s Capacity and Performance team where he partners with product teams on creative solutions for building efficient and reliable systems.
Managing Performance In a Cloud Migration
Dan is a long-time system administrator - he first installed on his PC in 1995 and never looked back. A veteran of the original dot com bubble, he founded a web hosting company in the late 90's, and has since worked in a variety of environments from start-ups to global corporations, including stints as a university lecturer and a day laborer. Today, Dan is a Technical Evangelist at Datadog, a role that allows him to satisfy his obsession with classifying and measuring things in general.
Workshop: Containers and orchestration are the new normal, but along with these new paradigms comes increased complexity and new observability concerns. In this workshop, we'll explore some common containerization scenarios, and learn how to install, configure, and instrument those containers effectively with Datadog. Next, we'll launch a Kubernetes cluster and explore how those monitoring principles apply to orchestrated environments. Attendees will gain valuable hands-on experience with both Docker and Kubernetes, and how they integrate with the Datadog platform.
Containers and Kubernetes Monitoring Best Practices