Statsig is a modern experimentation platform that provides crucial insight into how new features are received by your users, so you can make informed product decisions and deploy with confidence. Statsig automatically runs A/B tests on features as they’re rolled out, and measures their impact on key business metrics, such as user growth and engagement.

The ASP.NET Core framework provides cross-platform support for web development, giving you greater control over how you build and deploy your.NET applications. With the ability to run.NET applications on more platforms, you need to ensure that you have visibility into application performance, regardless of where your applications are hosted. In previous posts, we looked at instrumenting and monitoring a.NET application deployed via Docker and AWS Fargate.

Conviva is a platform that helps businesses gain real-time insight into the overall performance and playback quality of their streaming video content. With video streaming workflows, slow start-up times and playback errors can hinder user experience and ultimately drive customers away. With Conviva, you can view key Quality of Experience (QoE) metrics, including video playback failures, rebuffering ratios, and other business-critical data to help monitor and enhance your viewer experience.

Logs are an essential part of an effective monitoring strategy, as they provide granular information about activity that occurs anywhere in your system. In serverless environments, however, you have no access to the infrastructure that supports your applications, so you must rely entirely on logs from individual AWS services when troubleshooting performance issues.

Almost all tasks within a Linux system, whether it’s an application, system daemon, or certain types of user activity, are executed by one or more processes . This means that monitoring processes is key to detecting potentially malicious activity in your systems, such as the creation of unexpected web shells or other utilities.

Modern software development teams use CI/CD tools to ship features quickly and rely on best practices like shift-left testing to find application errors before they become user-facing bugs. But you still face the risk that any code you deploy could contain errors that your testing did not surface. To help you deploy with confidence and mitigate the effects of a bad deployment, Datadog APM now provides Automatic Faulty Deployment Detection.

Securing your environment requires being able to quickly detect abnormal activity that could represent a threat. But today’s modern cloud infrastructure is large, complex, and can generate vast volumes of logs. This makes it difficult to determine what activity is normal and harder to identify anomalous behavior. Now, in addition to threshold and new term –based Threat Detection Rules , Datadog Security Monitoring provides the ability to create anomaly.

When you’re running databases at scale, finding performance bottlenecks can often feel like looking for a needle in a haystack. In any troubleshooting scenario, you need to know the exact state of your database at the onset of an issue, as well as its behavior leading up to it.

Black Hat USA is one of the industry’s oldest and most well-established security events. Last year, the conference was held virtually for the first time in its history. This year’s conference brought together the best of both worlds, with a hybrid event that was held virtually and in person in Las Vegas. Historically, Black Hat has seen about 20,000 attendees at its in-person conference.

Serverless event-driven architectures are composed of AWS Lambda functions that regularly interact with databases, APIs, message queues, and other resources to facilitate complex workflows and functionalities. It is therefore crucial to monitor every component of your stack to ensure your applications perform optimally at scale. But traditionally, telemetry data for AWS resources has lived in silos, making it difficult to quickly get the context you need to debug issues.

Containers are lightweight, portable, easily scalable, and enable you to run multiple workloads on the same host efficiently, particularly when using an orchestration platform like Kubernetes or Amazon ECS. But containers also introduce monitoring challenges. Containerized environments may comprise vast webs of distributed endpoints and dependencies that rely on complex network communication.

Amazon Elastic File System (EFS) provides shared, persistent, and elastic storage in the AWS cloud. Like Amazon S3, EFS is a highly available managed service that scales with your storage needs, and it also enables you to mount a file system to an EC2 instance, similar to Amazon Elastic Block Store (EBS).

In Part 1 of this series, we looked at EFS metrics from several different categories—storage, latency, I/O, throughput, and client connections. In this post, we’ll show you how you can collect those metrics—as well as EFS logs—using built-in and external tools.

In Part 1 of this series, we looked at the key EFS metrics you should monitor, and in Part 2 we showed you how you can use tools from AWS and Linux to collect and alert on EFS metrics and logs. Monitoring EFS in isolation, however, can lead to visibility gaps as you try to understand the full context of your application’s health and performance.

From containerized workloads to microservice architectures, developers are rapidly adopting new technology to scale their products at unprecedented rates. To manage these complex deployments, many teams are increasingly moving their applications to third party–managed services and infrastructure, trading full-stack visibility for simplified operations.

When you migrate workloads from on-premise infrastructure into a public cloud, you can improve the performance, reliability, and security of your application, and you might also lower your costs.

The ASP.NET Core framework enables you to build and deploy .NET applications on a wide variety of platforms, each of which has different observability concerns. In a previous post, we looked at monitoring a containerized ASP.NET Core application. In this guide, we’ll show how Datadog provides visibility into ASP.NET Core applications running on AWS Fargate. We’ll walk through.