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In today's tech landscape, where application systems are numerous and complex, real-time monitoring during deployments has transitioned from being a luxury to an absolute necessity. Ensuring that all the components of an application are functioning as expected during and immediately after deployment while also keeping an eye on essential application metrics is paramount to the health and functionality of any software application. This is where Datadog steps in — a leading monitoring and analytics platform that brings visibility into every part of the infrastructure, from front-end apps to the underlying hardware. In tandem with this is Ansible, a robust tool for automation, particularly in deployment and configuration management. In this article, we will discover how Datadog real-time monitoring can be integrated into Ansible-based deployments and how this integration can be leveraged during deployments. This concept and methodology can be applied to similar sets of monitoring and deployment tools as well. Why Integrate Real-Time Monitoring in Deployments? In the ever-evolving realm of DevOps, the line between development and operations is continuously blurring. This integration drives a growing need for continuous oversight throughout the entire lifecycle of an application, not just post-deployment. Here's why integrating Datadog with your deployment processes and within your deployment scripts is both timely and essential: View the full article

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At the KubeCon + CloudNativeCon Europe 2022 event, Datadog announced it made support for the OpenTelemetry Protocol (OTLP) generally available in the agent software it provides to instrument applications. Ilan Rabinovitch, senior vice president of product and community at Datadog, said that capability eliminates the need to install a separate OpenTelemetry collector to aggregate metrics, […] The post Datadog Adds Support for OpenTelemetry Protocol appeared first on DevOps.com. View the full article

OpenTelemetry 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 our ongoing commitment to OpenTelemetry, we are proud […] The post Ingest OpenTelemetry Traces and Metrics with the Datadog Agent appeared first on DevOps.com. View the full article

Datadog expands its existing support for OpenTelemetry by enabling native OpenTelemetry Protocol ingestion in the Datadog Agent NEW YORK, NY, May 16, 2022 – Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, announced today the general availability of OpenTelemetry Protocol (OTLP) support in the Datadog agent. This new capability brings the […] The post Datadog Announces OpenTelemetry Protocol Support appeared first on DevOps.com. View the full article

The new offerings help organizations easily manage the increasing complexity of Kubernetes environments NEW YORK, NY, May 16, 2022 — Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced a number of enhancements to its platform that simplify the monitoring and security of Kubernetes environments. While orchestrated container environments are growing […] The post Datadog Enhances Monitoring and Security for Kubernetes appeared first on DevOps.com. View the full article

You can now send logs from AWS Lambda functions directly to a destination of your choice by using AWS Lambda Extensions. AWS Lambda Extensions are a new way for monitoring, observability, security, and governance tools to integrate with Lambda, and today, you can use extensions that send logs to the following providers: Datadog, New Relic, Sumo Logic, Honeycomb, Lumigo, and Coralogix. View the full article

Algorithmia today launched a performance monitoring for machine learning (ML) model that tracks algorithm inference and operations metrics generated by the enterprise edition of its namesake platform for building these models. Company CEO Diego Oppenheimer said Algorithmia Insights provides a level of observability into ML models that DevOps teams have come to expect from applications. […] The post Algorithmia Allies With Datadog on MLOps Observability appeared first on DevOps.com. View the full article

Before we dive into the specifics of each alternative to Datadog, let's address the most critical point: scaling. Datadog is great for users who need to do a little bit of everything, but Datadog's biggest weakness is scaling. View the full article

BigPanda Inc. and Datadog today announced they will integrate their respective platforms to make it easier to form artificial intelligence for automating IT operations (AIOps) to consume data generated by the Datadog IT monitoring service. The two companies are pledging to invest in a go-to-market partnership to create a comprehensive platform for monitoring, analytics and […] The post Datadog Allies with BigPanda on AIOps appeared first on DevOps.com. View the full article

Do you wish you could use CloudWatch, but don't want to go all-in on AWS products? There's AWS Lambda, EKS, ECS, CloudWatch and more. View the full article

This post was co-authored by Sreekanth Thirthala Venkata, Principal Program Manager, Visual Studio and .NET. Microsoft Azure enables customers to migrate and modernize their applications to run in the cloud, in coordination with many partner solutions. One such partner is Datadog, which provides observability and security tools for users to understand the health and performance of their applications across hybrid and multi-cloud environments. But configuring the necessary integrations often requires navigating between the Azure portal and Datadog. This adds complexity, takes time, and makes it difficult to troubleshoot if things aren’t working. To reduce the burden of managing across multiple portals, we worked with Datadog to create an integrated Datadog solution on the Azure cloud platform. Available via the Azure Marketplace, this solution provides a seamless experience for using the Datadog’s cloud monitoring solution in Azure. “The Microsoft cloud is the first to enable a seamless configuration and management experience for customers using third-party solutions like Datadog. With Datadog, customers are empowered to use this experience to monitor their Azure workloads and enable an accelerated transition to the cloud.” —Corey Sanders, Corporate Vice President, Microsoft Solutions With the new Azure integration with Datadog, organizations can now fully map their legacy and cloud-based systems, monitoring real-time data during every phase of the cloud transition, and ensure that migrated applications meet performance targets. This integration combines Azure’s global presence, flexibility, security, and compliance with Datadog's logging and monitoring capabilities to create the best experience for enterprises. Through this unified experience, customers will be able to: Provision a new Datadog organization and configure their Azure resources to send logs and metrics to Datadog—a fully managed setup with no infrastructure for customers to setup and operate. Seamlessly send logs and metrics to Datadog. The log-forwarding process has been completely automated; rather than building out a log-forwarding pipeline with Diagnostic Settings, Event Hubs, and Functions, you can configure everything with just a few clicks. Easily install the Datadog agent on VM hosts through a single-click. Streamline single-sign on (SSO) to Datadog—a separate sign in from the Datadog portal is no longer required. Get unified billing for the Datadog service through Azure subscription invoicing. "Observability is a key capability for any successful cloud migration. Through our new partnership with Microsoft Azure, customers will now have access to the Datadog platform directly in the Azure console, enabling them to migrate, optimize and secure new and migrated workloads." —Amit Agarwal, Chief Product Officer, Datadog Here’s a quick look at this integrated experience: Acquire and setup the Datadog solution Now let’s follow the step-by-step process to acquire and setup the Datadog solution: Procuring the Datadog app: Azure customers can procure the Datadog app through the Azure Marketplace. Provisioning in the Azure portal: After procuring in Azure Marketplace, customers can seamlessly provision Datadog as an integrated service on Azure via the Azure portal. Configuring logs and metrics: Customers create a Datadog resource in Azure and configure which Azure resources send logs and metrics and to Datadog. Installing Datadog agent: Customers can install the Datadog agent as an extension on virtual machines (VMs) and app services with a single click. Access via SSO: Customers access Datadog from the Azure portal through a streamlined SSO experience and configure Datadog as a destination for logs and metrics from Azure services. Next steps Sign up for the preview of the new Datadog integration with Azure. The preview will be available on Azure Marketplace starting October 2020. Read more about the Azure Monitor partner integration with Datadog. View the full article