September 2022 Summaries

The text discusses how continuous integration (CI) demands continuous testing and how shifting left can help prevent faulty code from spreading. It introduces Datadog's new Azure DevOps extension, which enables seamless incorporation of integration and end-to-end tests into existing CI/CD workflows on Azure Pipelines. The extension uses Datadog Synthetic Monitoring to bolster the shift-left strategy and proactively assess user experience at each step of the development process. It guides users through setting up the extension, implementing end-to-end tests in Azure Pipelines, monitoring test results, and optimizing CI pipeline performance using Datadog's CI Results Explorer and CI Visibility features. The text also mentions that Datadog offers visibility solutions for various CI providers, including Jenkins, CircleCI, GitHub Actions, and Azure Pipelines.

Datadog has released a new Azure DevOps extension that enables seamless integration and end-to-end testing in existing CI/CD workflows on Azure Pipelines, bolstering the shift-left strategy by proactively assessing user experience at each step of the development process. The extension allows users to continuously assess application performance using synthetic monitoring, which can be easily configured to test any URL at any point in the pipeline, including QA, staging, pre-production, and production environments. By incorporating Datadog Synthetic Monitoring with CI Visibility, users can gain deeper insight into their CI pipelines, identifying high error rates, excessive build durations, flaky tests, and more, and pair it with synthetic testing to test application workflows earlier and more frequently throughout the development process.

Azure Container Apps is a serverless platform that facilitates the deployment of containerized applications and microservices without the need to manage underlying cloud infrastructure. It automatically scales based on demand through Kubernetes event-driven autoscaling (KEDA) and integrates with the Distributed Application Runtime (DAPR) for a comprehensive deployment toolset. The integration with Datadog provides deep visibility into container apps by allowing the monitoring of metrics such as traces, logs, HTTP requests, and resource usage. Users can leverage Datadog to troubleshoot issues, track traffic patterns, detect cold starts, and manage resource allocation to optimize performance and costs. This integration offers a unified monitoring platform that combines Azure metrics with other technological data, providing a holistic view of application performance and infrastructure. Datadog offers a free 14-day trial for users to explore its Azure Container Apps monitoring capabilities.

In 2018, Datadog started building a design system called DRUIDS (Datadog Reusable User Interface Design System) to ensure consistency and efficiency across its expanding suite of products. The design system is not open source but the documentation site has been made public at druids.datadoghq.com. It aims to make workflows simple, powerful, and flexible for users while being easy to understand, implement, and contribute back to. Key features include a quick nav pattern, DRUIDS Loupe, links to source code, editable playgrounds, auto-generated API tables, and contribution guidelines. The design system is expected to evolve as the needs of Datadog and its customers change.

The new Datadog Certification Program aims to help users reinforce and validate their knowledge of the company's best-in-class monitoring platform. The program offers three separate exams: Datadog Fundamentals, Log Management Fundamentals, and APM and Distributed Tracing Fundamentals. Each exam consists of 90 multiple-choice questions that candidates will be given two hours to complete. Successful completion of the exams allows individuals to validate their skills and showcase their credentials in the form of badges that prove their proficiency in core aspects of the Datadog platform, including log management and application performance monitoring. The program is now live with test preparation materials available for each exam.

The Datadog team built a design system called DRUIDS, which is used across the platform to ensure a unified and efficient user experience. The system includes features such as quick navigation, contextual documentation, editable playgrounds for developers and designers, auto-generated API tables, and contribution guidelines to facilitate collaboration and evolution of the design system. To make it easy for users to understand and implement DRUIDS, the team has implemented tools like a command line wizard that generates scaffolding for new components, and made the documentation site public at druids.datadoghq.com. The goal is to make DRUIDS not just a design system but a living, breathing part of the Datadog platform that users can trust and contribute to.

The Datadog platform has evolved to meet the needs of organizations investing in cloud-based solutions and modernizations. To demonstrate their knowledge and understanding of observability best practices, Datadog offers a new Certification Program that validates practical comprehension of its key products and technologies. The program features three separate exams - Datadog Fundamentals, Log Management Fundamentals, and APM and Distributed Tracing Fundamentals - each focusing on a different aspect of the platform to gauge user competency. Successful completion of these exams can be achieved through in-person or remote testing, with test preparation materials available for candidates. The program is designed to help users reinforce their knowledge, gain credibility among recruiters or employers, and level up their monitoring skills.

Microsoft's .NET framework simplifies the development of cross-platform applications. Datadog Continuous Profiler now supports general profiling for .NET applications, including .NET Framework, .NET Core, and .NET 5+. This feature allows developers to compare code performance across different versions, time frames, and environments directly in production, enabling them to identify resource bottlenecks and improve user experience. The Continuous Profiler's flame graph helps optimize expensive methods, while method-level tracing and profile comparison features assist in troubleshooting high CPU consumption and latency. Datadog's profiler supports all languages targeting the .NET runtime, such as C#, F#, and Visual Basic, to provide deep visibility for all infrastructures.

The .NET framework simplifies cross-platform application development, and the Datadog Continuous Profiler now provides general support for .NET applications. This tool allows developers to compare code performance across different versions, time frames, and environments in production, enabling them to identify resource bottlenecks and improve user experience. The profiler is designed to be low-overhead and continuously collect application data without changing the .NET runtime behavior. It enables method-level tracing and profile comparison features to troubleshoot high CPU consumption and latency issues. With this tool, developers can optimize expensive methods, find specific lines of code degrading performance, and improve overall application performance.

The Datadog Audit Trail provides administrators and security team members with visibility into how users and teams within an organization use and interact with various Datadog products and observability data. It helps maintain a robust monitoring setup by tracking configuration changes, monitoring Datadog activity for security and usage insights, and enhancing the overall Datadog experience. Audit Trail enables investigations of unexpected issues by revealing when segments of the Datadog platform were accessed or modified and by whom. This feature is particularly useful for uncovering product-specific actions such as dashboard updates, log management configuration changes, and changes to custom metrics and tags. Additionally, it allows tracking the creation, deletion, and modification of Datadog API and APP keys, ensuring secure usage of the platform. By leveraging Audit Trail, organizations can optimize their monitoring efforts, identify potential security threats, and drive wider adoption of specific features for various use cases.

Datadog Audit Trail provides visibility into how users and teams within an organization use and interact with various Datadog products and observability data. It enables administrators to track configuration changes, monitor activity for security and usage insights, and set alerts on specific events that can impact monitoring efforts. With Audit Trail, organizations can identify issues quickly, establish a robust monitoring setup, and optimize the security and efficiency of their monitoring efforts by notifying on API key changes or unused Datadog products and features.

Amazon Virtual Private Cloud (Amazon VPC) is an AWS service that enables users to launch resources within their own virtual network. It offers high availability and security by allowing deployment in separate regions and across different Availability Zones. Key components of Amazon VPC include CIDR blocks, subnets, internet gateways, NAT gateways, route tables, and virtual firewalls. Configuring these components properly can help reduce the attack surface while ensuring functionality. Virtual firewalls such as access control lists (ACLs) and security groups provide granular control over traffic in and out of subnets and specific resources within a VPC. Monitoring network activity using tools like Datadog's AWS integration and Cloud SIEM platform can help detect potential attacks and ensure the security of your VPC.

Amazon Virtual Private Cloud (VPC) is an AWS service that enables the launch of AWS resources within a virtual network, providing high availability and security. To configure VPCs effectively, it's essential to choose the right CIDR block size, partitioning subnets into isolated segments for secure resource placement. Internet gateways and NAT gateways facilitate internet access, while route tables define traffic routing based on destination IP addresses. Virtual firewalls, including access control lists (ACLs) and security groups, can be used to fine-tune network traffic rules, controlling inbound and outbound traffic at the subnet level or specific resources within a VPC. By implementing these best practices, users can reduce their attack surface while ensuring application functionality and internet connectivity.

The text discusses the importance of Amazon VPC Flow Logs in enhancing the security of virtual private clouds by providing visibility into network activity, which allows for the verification of security policies and detection of potential attacks. Flow logs are crucial for understanding traffic patterns within a VPC, including the movement of data between subnets and EC2 instances, and are vital for identifying data exfiltration during security incidents. The document also explores how Datadog's AWS integration and Security Platform can be used to monitor and analyze these logs, offering solutions for capturing flow logs, setting up alerts, and detecting security threats such as brute force SSH and denial of service attacks. It further highlights the role of Datadog in providing comprehensive insights into the security posture of VPCs by leveraging its integration with other AWS services, ultimately facilitating the monitoring and management of network traffic across multiple VPCs.

In this month's feature, Stephanie Molano, a Commercial Account Executive at Datadog based in Florida, shares her journey to the company and how she leverages her cultural background to connect with clients and colleagues. She discusses her role as part of the commercial sales team, focusing on communicating the value of Datadog's product to the Latin American market. Stephanie also highlights her involvement in the company's Latinx Community Guild, which aims to create a sense of belonging for those who identify as Latinx or allies within the organization. She encourages others to join Datadog and experience its inclusive culture and growth opportunities.

Stephanie Molano, a Commercial Account Executive at Datadog, shares her journey to the company, where she began after graduating in 2020 and was drawn by Datadog's focus on innovation and its potential to make a cultural impact. As part of the Commercial Sales team, Stephanie focuses on communicating the value of the Datadog product to the Latin American market. She describes her day-to-day role as diverse, involving project management, negotiation, sales consulting, and presenting products to clients. The culture of the Commercial Sales team is characterized by passion, ambition, and a collaborative team-first approach. Stephanie has grown in her career, starting as a Sales Development Representative and progressing to Account Executive and now coleader of the Latinx Community Guild, an initiative that aims to empower individuals from Latin American backgrounds to feel valued and connected at work. The company values diversity and inclusion, with the Latinx Community Guild providing a safe space for employees to share their cultural heritage and connect with others who share similar backgrounds. Datadog is currently hiring for open roles around the world, offering the opportunity to join a growing team and experience #DatadogLife.

Hardware Sentry is a hardware monitoring solution that provides granular visibility into on-premise infrastructure's health and energy consumption. It helps organizations understand their financial and ecological footprint by reporting energy usage in terms of actual Watt-hours, dollar cost, and CO2 emissions. The integration with Datadog Marketplace allows users to track sustainability metrics alongside the health, status, and resource utilization of on-prem hosts from a unified view. Hardware Sentry's out-of-the-box dashboards and alerts help maintain comprehensive infrastructure health and sustainability visibility while providing insights into reducing carbon footprint and operating costs.

The Hardware Sentry integration is now available in the Datadog Marketplace, allowing users to monitor their on-prem infrastructure's health and energy consumption. The integration provides granular visibility into hardware components' performance and energy usage, enabling organizations to reduce their carbon footprint and operating costs. Out-of-the-box dashboards and custom alerts provide a unified view of infrastructure health and sustainability metrics, including site heating margin, power consumption, and battery charge thresholds. This enables users to track issues with their hardware and make data-driven decisions to optimize their site's ambient temperature, predict maintenance needs, and ensure compliance with emissions regulations. The integration is now generally available, and new customers can get started with a 14-day free trial.

Amazon Virtual Private Cloud (Amazon VPC) is an isolated and secure virtual network that allows users to deploy resources while restricting their exposure to the internet. With the integration of Amazon Kinesis Data Firehose, users can now easily send VPC flow logs from Amazon Kinesis Data Firehose to Datadog for comprehensive monitoring and analysis. This integration simplifies the process of ingesting, transforming, and streaming real-time data to data stores and analytics platforms. By leveraging Datadog Log Management, users can search, filter, group, and analyze their VPC flow logs in real time, as well as perform analytics on high-cardinality log data to uncover trends and anomalies.

Amazon Virtual Private Cloud (VPC) flow logs can be used to monitor and analyze network traffic in an isolated and secure virtual network. This allows for better understanding of traffic patterns, optimization of security posture, and troubleshooting of connectivity and configuration issues. Amazon VPC already integrates with Amazon CloudWatch Logs and Amazon S3, but now also has a native integration with Amazon Data Firehose, which enables seamless and reliable streaming of VPC flow logs to Datadog for comprehensive monitoring and analysis. With this integration, customers can leverage powerful data transformation capabilities in Data Firehose to process, enrich, and aggregate their logs before delivering them to destinations of choice. Once the flow logs are sent to Datadog, customers can easily search, filter, and group their logs by various attributes, perform analytics on high-cardinality log data to uncover trends, and add visualizations to dashboards for better monitoring and correlation.

LambdaTest is a cloud-based platform that facilitates both real-time and automated testing across more than 3,000 browsers, devices, and operating systems, utilizing frameworks like Selenium and Appium. It offers a seamless integration with Datadog, available through the Datadog Marketplace, allowing users to visualize testing metrics via an out-of-the-box dashboard, which aids in monitoring test suite performance and identifying potential issues. This integration enables users to report bugs directly from LambdaTest to Datadog Incident Management, allowing for efficient bug investigation and resolution processes. Users can customize the LambdaTest dashboard to better suit their needs, incorporating real user monitoring data to prioritize bug fixes affecting customer experience. Datadog customers can access these features through a LambdaTest subscription, while non-customers can explore Datadog with a 14-day free trial.