2022 Partner Theater Presentations

Imagine you wake up to your Slack blowing up. Alerts are going off and users are complaining. You go straight to your Datadog dashboard and can see right away there’s a problem. But what caused it? Thanks to the Zebrium widget on your dashboard, you can just scroll down a bit farther and immediately see a summary of the root cause!

In this presentation we’ll explain how machine learning can help speed up troubleshooting for incidents where the root cause might be hidden inside the huge volume of logs modern environments generate, helping on-call engineers remediate issues faster.

Two of the main pain points in modern cost management are understanding your Kubernetes expenditure and determining how to appropriately attribute the costs of a multi-tenant environment to your customers.

In this talk, we will share the story of how Finout tackled these two issues using Datadog: We will show how Finout built a Kubernetes costs view based on Datadog container metrics. We will then look at how you can correlate those costs to other Datadog metrics so you could build your company’s unit economics and eventually assign those costs to your customers.

You can expect technical descriptions of how we built this integration, plus tips and tricks on how to do it in your own environment.

Once you know your per-customer’s expenditures you can:

• Give easy answers to finance and C-level stakeholders about the business aspect of cloud usage.
• Identify your biggest and smallest customers based on revenue.
• Easily explain why your bills went up and if that’s a good thing.

As organizations continue to expand their cloud footprint, managing costs without risking application performance is a priority. Because of this, Arm processors have become popular for their efficient, cost-effective processing power. Microsoft Azure’s new series of Azure Virtual Machines are powered by Ampere Altra Arm-based processors, which provide excellent price-performance for scale-out and cloud-native workloads.

In this theater presentation, learn how Azure customers can migrate their compute-heavy workloads to this new architecture and see improved performance and cost savings.

OpenTelemetry (OTel) is a Cloud Native Computing Foundation (CNCF) initiative that provides open, vendor-neutral standards and tools for instrumenting services and applications. Many organizations use OpenTelemetry’s collection of APIs, SDKs, and tools to collect and export observability data from their environment to their preferred backend.

As part of Datadog’s ongoing commitment to OpenTelemetry (OTel), we offer multiple solutions to ensure that OpenTelemetry users have the flexibility to easily send their metrics, traces, and logs to Datadog.

In this session, we will walk through a live product demo that will show how you can use OTel and Datadog to get full visibility into your infrastructure and applications. We will also explore different data ingestion paths you can use to derive maximum value out of your OTel usage with Datadog.

Amazing digital experiences can help brands delight their customers and help differentiate from competitors—and ultimately generate more sales. But to deliver these experiences, brands need to gain insights from every user interaction, which is a serious challenge for teams that use legacy, tag-based analytics tools.

In this session, we will look at how Datadog Real User Monitoring (RUM) and Session Replay provide an end-to-end view of your frontend browser and mobile applications. You will learn how RUM and Session Replay give you a real-time perspective of your users, so that you can proactively troubleshoot, review, analyze, and improve user experiences at scale. Together, these solutions minimize your blindspots across user journeys so that you can deliver perfect digital experiences.

With more and more of our employees working from home, reliant on everything from a working laptop with good home WiFi to solid infrastructure health and performant SaaS apps to get their work done – focus must shift from traditional IT to a new, hybrid digital workplace model focused on “Digital Employee Experience”. Delivering these experiences requires a comprehensive strategy to holistically observe and remediate across the enterprise technology stack.

Datadog and 1E (DEX market leader) are pioneering a convergence of Digital Employee Experience (DEX), Application Performance Management (APM) and Real User Monitoring (RUM). This convergence: Application Experience Management (AXM) delivers the holistic insights and automation resulting in greater business outcomes.

By the end of this session, learn how Datadog and IE can help you improve digital experiences for your whole workforce and empower your IT teams to evolve from a cost centre to a strategic enabler of change.

When a database fails, applications can break in unexpected ways and data can be lost. The cause of failures could lie in the underlying infrastructure, the database schema, or even the queries themselves. Without unified access to critical information about your databases and the queries they run, it can be difficult for disparate teams to efficiently collaborate and resolve the issue.

In this session, you will learn how Datadog Database Monitoring (DBM) enables DBAs, SREs, and application developers to identify performance issues at a glance and quickly improve database efficiency. We will demonstrate how DBM lets you find the root cause of any issue by providing deep visibility into wait events, active connections, query performance, and explain plans, allowing you to reduce database costs, increase efficiency and uptime, and streamline collaboration between all stakeholders.

Code profiling allows you to measure code performance by surfacing the most time- and resource-consuming lines of code. However, code profilers are often viewed as complex tools that are used only by experienced engineers and limited to non-production environments. Worse still, when profiling bottlenecks are discovered and addressed, developers are often missing critical observability context (like logs and traces) to better understand overall performance impact within systems.

In this session, you will learn how you can address these challenges with Datadog Continuous Profiler, which provide low overhead, always-on code profiling on every production host and a simple way to instrument additional metrics, traces, and logs on-demand from the Datadog UI. You will leave this session understanding how these two products fit into your observability journey with Datadog, allowing anyone on your team to troubleshoot and resolve bottlenecks quickly, reduce CPU and memory consumption, and lower cloud costs.

In addition to building modern applications with a multi-tier, service-oriented architecture, software engineers are releasing code faster than ever. That pace of innovation comes with an increased risk of introducing performance regressions, and problems that affect end users can occur at any level in the technology stack. To catch such problems before they cascade and become critical, frontend and backend teams need a single source of truth so they are not blindsided in pivotal moments and can avoid context switching and redundant manual work.

In this session, frontend and backend developers will learn how to achieve end-to-end visibility into the user experience and application performance using Datadog Real User Monitoring (RUM) and Application Performance Monitoring (APM). Learn how frontend and backend teams can have a shared view to quickly understand where a problem has originated and who is responsible for fixing the issue.

Hear how the team at ClickUp is applying these tools and services in their org. You will leave this session with a better understanding of how to monitor and troubleshoot your entire technology stack in a single view to quickly detect, triage, and resolve customer-facing problems.

Companies around the world have identified how sharing real-time data with employees and teams can make a real impact on business results. However, these same organizations struggle with how to easily and securely share dashboards across large teams, especially with today’s distributed workforce.

In this session, we will provide a look at the importance of sharing real-time data with employees and the most common methods for doing so. We’ll also provide five easy steps anyone can take to bring their dashboards to life on large-format displays, easily reaching and engaging more employees, efficiently and securely. We will present data from Skykit’s State of Data Visualization in the Office report as well as case studies on the power of sharing dashboards with team members across an organization.

Over the past 8 years, the AllCloud and Datadog partnership has grown to implement the Datadog platform across hundreds of customers - and the partnership continues to grow stronger every day. This presentation will touch on the continued growth of the partnership and provide insight into the newly released AllCloud Managed Monitor solution, which combines AWS expertise with real-time infrastructure and application data from Datadog to provide customers with actionable alerts and powerful visualizations that ensure full-stack observability.

AllCloud will share the main challenges of the customers while migrating to the cloud and their needs for monitoring platform including support.

Visibility into the health and performance of your application is essential for managing uptime. But what happens when there is a problem and every second before taking action matters? Deploying a fix or an update might not be fast enough to avoid customer impact. By pairing LaunchDarkly’s feature-management platform with Datadog’s observability platform, software teams can improve application reliability. You can turn observable insights from Datadog into action with LaunchDarkly’s ability to disable broken features or alter configurations in milliseconds, maintaining uptime without redeployment.

This session will cover three integrations that LaunchDarkly provides for Datadog and how developers and teams can make use of them to increase control while decreasing MTTR:

• Audit Log Events: Send audit log events to Datadog to add context to your observability metrics.
• Datadog Widget: Configure feature flags within your Datadog Dashboard using our widget, giving you control over your feature flags right where you need it.
• Flag Triggers: Automatically disable broken features when a metric reaches a certain threshold with Flag Triggers.

In this talk you will gain an understanding of how to use feature flags to deliver software quickly and with less risk. You will also learn how to utilize LaunchDarkly in tandem with Datadog in order to gain real-time insights with each product launch and act upon them immediately using our integrations.

Application migrations are rarely a stress-free endeavor. From installing agents at the source to validating data and configurations at the destination, there are multiple possible points of failure as you move services over. These problems are only exacerbated if your organization uses a variety of monitoring tools and mechanisms.

In this session, you will learn how Datadog’s single-pane-of-glass approach to observability and monitoring across all your workloads can simplify your migration journey. By making use of Datadog’s out-of-the-box integrations and unified approach, you can easily measure, compare, and contrast the performance of your applications down to the code level before, during, and after your migration.

Whether cloud-hosted or on-premise, more and more organizations are using Kubernetes to deploy their applications. AWS provides tools to make it easier for organizations to run and scale their containerized applications, including Amazon Elastic Kubernetes Service (EKS), a managed Kubernetes service, and EKS Blueprints, a collection of infrastructure-as-code modules that make it easy to bootstrap a Kubernetes cluster with any additional tools required for their environment. This includes Datadog, which makes it easier to manage and scale Kubernetes operations through its observability and monitoring capabilities.

In this session, AWS and Datadog experts show you how simple it is to set up Datadog using EKS Blueprints, as well as how Datadog’s platform helps you understand and monitor every aspect of your EKS environment.

Google Cloud Run is a fully-managed platform for deploying and scaling serverless containerized microservices on Google-managed infrastructure. Cloud Run accelerates productivity by letting teams focus on developing and deploying apps, without creating clusters. But, visibility into the health and performance of serverless applications can be challenging.

We are excited to partner with the Datadog team to bring Datadog’s leading observability solution to Google’s Cloud Run. In this session, we’ll look at how the purpose-built Datadog Agent provides Cloud Run users insights into their serverless apps viafull application tracing, custom metric support, enhanced metric capabilities, and logging ingestion Datadog.

When developing an application, monitoring can be a painful afterthought. Implementing monitoring on top of existing priorities requires significant effort and resources. For Accenture, this is especially challenging as we support more than 1,100 unique and distributed applications deployed across a multi-cloud landscape.

Join this session to learn how Accenture successfully sets a NoOps approach with Datadog monitoring enablement by embedding Datadog into the software development lifecycle. You’ll learn new patterns that work for applications running on containers and that can be applied to other cloud technologies (e.g., serverless functions).

Developer portals like Cortex.io have become critical for businesses to run efficient engineering organizations—especially as the number of services and engineers those organizations manage scales. Cortex.io automatically catalogs all internal services and infrastructure along with their dependencies, ownership, and live data from third-party tools. It then enables engineering organizations to drive adoption of best practices, enforce service maturity standards, and run organization-wide migrations through actionable insights that are personalized for individual teams.

In this session, you will learn more about why companies adopt developer portals, how to maximize their impact, and how they can help your team reduce the organizational complexity that comes with running a service-oriented architecture.

Google Cloud’s Eventarc uses loosely coupled services that react to state changes in order to asynchronously route and deliver events between Google services, SaaS platforms, and your own apps. For example, you can use Eventarc and Datadog to build closed-loop monitoring and remediation for your systems, whether they are in the cloud or on-prem. In the session, we’ll walk through how to use a Datadog monitor set on vCPU utilization to create an event. We’ll use Eventarc to have that event call on Cloud Functions to initiate a scale-up procedure, automatically adding a node to our cluster and averting an infrastructure outage.

In this session, you will learn how you can integrate Eventarc and Datadog together to automatically remediate issues before they cause problems for your customers.

The race to net-zero emissions has started. But without the proper visibility into the energy usage of your infrastructure, you are at a standstill. Hardware Sentry fills this gap with its specialized OpenTelemetry Collector—now available through Datadog’s Marketplace—enables you to collect raw hardware metrics, including health data of hardware components, processors, disks, network, power consumption, temperatures, and more.

In this session, we will teach you how to get the most out of this new integration. We will walk through using the built-in dashboards and monitors to report the CO₂ emissions of your infrastructure, reduce its carbon footprint, and lower operating costs by safely optimizing the temperature of a server room.

DevSecOps teams are challenged with delivering code that is secure and compliant, and to do so with speed at each stage of the software development lifecycle. In this session, we will look at how JFrog’s integration with Datadog provides DevOps and DevSecOps teams with actionable insights to achieve greater compliance, security, and software delivery performance. We’ll cover how the integration delivers a robust dashboard with visibility into logs, violations, usage metrics of artifacts and repositories, and system performance to answer questions like:

• What is the most requested artifact?
• What are the most popular repositories?
• Who are your heaviest users?
• For security, which users are doing bad things? From which IPs?

Join us to learn how to get the most out of the JFrog platform with Datadog.

Working with data has always been the hardest part of developing applications. As applications evolve and requirements change, so do the technologies used to support them. The adoption of different data stores, the creation of data transfer processes, and the increasing complexity of query access patterns can introduce a lot of friction into the software development lifecycle.

In this session we will learn how MongoDB and the document model can eliminate some of that friction by consolidating your data onto a single database that can support these evolving requirements, doing so at scale and with performance in mind.

Ten years ago, the word serverless appeared. For developers, it meant the promise of no longer having to worry about backend infrastructure; they could focus on application logic.

Whether you’ve been using serverless technology since it’s launch or re only now in preliminary talks about how to use it, join me for a brief history of serverless and learn how you can build serverless applications on Cloudflare.

We’ll tackle common questions such as:

• What are the advantages of serverless?
• Who uses serverless functions?
• What workloads are best for serverless technology?
• Can you run serverless functions at the edge?

And if you’re asking yourself, “What even is serverless?” we’ll answer that as well.

Infinitive is a Gold-tier Datadog Consulting Partner. We understand what it means to live in a rapidly changing globalized business climate with changing customer expectations. Organizations are being forced to anticipate, adapt to, and accelerate changes faster than their competitors. We provide various business units (e.g., CXOs, DevSecOps, SREs) the insights needed for rapid root cause analysis, visualization of key performance indicators, and early detection of system problems. We will share how Infinitive partners with Datadog to drive actionable insights via observability.

Specifically, in this session, we will share how to minimize the time to a return on investment in your Datadog instrumentation and observability practices.

The majority of data breaches are caused by misconfigurations. This is heavily driven by the multitude of possible cloud configuration options, potential lean staffing, and the businesses need to move swiftly. AWS offers customers a variety of options to secure their workloads: IAM configurations to define who can modify and run cloud workloads; network configurations to set which resources a workload can communicate with; a suite of encryption facilities to ensure integrity and confidentiality—the list goes on. It’s essential to ensure these configurations follow best security practices to reduce the probability of a data breach.

In this session, you will learn how Datadog Cloud Security Posture Management (CSPM) helps continuously maintain security and compliance best practices across your AWS assets. In addition to ensuring compliance this product helps mitigate risk and offer prescriptive guidance on options to remediate vulnerable resources.

Customers who use Datadog and PagerDuty for incident response see faster acknowledgment of incidents and a lot more responder focus on resolving issues. But did you know that advanced PagerDuty and Datadog customers can further drive down MTTR and get even more efficiency out of their incident response?

In this session we’ll dive deeper into how these two approaches work together, with a special focus on how to take advantage of Datadog monitors along with PagerDuty’s Automated Diagnostics for Public Cloud Environments and you will learn:

• How first responders can use Datadog monitors and PagerDuty Automated Diagnostics to resolve problems in public cloud environments
• How to use prebuilt diagnostics for Public Cloud Environment services available for PagerDuty