Logging your Java applications is essential to getting visibility into application performance and troubleshooting problems. But, with a variety of available libraries and configuration options, getting started logging in Java can be challenging.
Data drives every decision we make at Datadog. That includes decisions about when to leave the office to catch the train! A few years ago, Datadog engineers created MTAServiceChecker.com to provide ourselves and our fellow New Yorkers with detailed insight into New York’s subway system, the MTA. For a recent Datadog hackathon, Chuck Hagenbuch and I, part of our growing engineering team here in Boston, created a version of the service checker for our local system, the MBTA.
Alibaba Cloud provides a comprehensive suite of cloud computing services to power businesses across the globe. We are excited to announce that our new integration with Alibaba Cloud is now in public beta. While the Datadog Agent has always been able to provide visibility into Alibaba Cloud instances, this new integration now enables you to also monitor the health and performance of Alibaba Cloud services (load balancers, managed databases, and more) in Datadog.
Organizations that depend on distributed systems often write their applications in Go to take advantage of concurrency features like channels and goroutines (e.g., Heroku, Basecamp, Cockroach Labs, and Datadog). If you are responsible for building or supporting Go applications, a well-considered logging strategy can help you understand user behavior, localize errors, and monitor the performance of your applications.
IBM MQ is enterprise-grade message-oriented middleware (MOM). Previously known as MQSeries and renamed to WebSphere MQ, IBM MQ is known for its stability and reliability. Companies in industries ranging from financial services to retail to aviation use it as an integral part of their backend infrastructure. Datadog’s new IBM MQ integration enables users to collect key metrics and logs from their IBM MQ instances and visualize them with a customizable out-of-the-box dashboard.
Amazon DocumentDB is an AWS-managed document database service that supports MongoDB, the well known open source database. As a managed service, AWS automatically handles database management tasks, autoscales database clusters, and backs up your data to S3. DocumentDB implements the Apache 2.0 open source MongoDB 3.6 API, making it easy to migrate your existing MongoDB workloads to DocumentDB.
As application architecture moves from monoliths to microservices, observability has become a growing challenge. The services that make up a distributed application, and the many dependencies and communication pathways between them, are difficult to govern and observe. You can get more control and visibility of your application by including a service mesh—a layer of infrastructure that manages traffic among microservices.
Datadog is pleased to announce the availability of Synthetics, a whole new layer of visibility on the Datadog platform. By monitoring your applications and API endpoints via simulated user requests, Synthetics helps you ensure uptime, identify regional issues, track application performance, and manage your SLAs and SLOs. By unifying Synthetics with your metrics, traces, and logs, Datadog allows you to observe how all your systems are performing as experienced by your users.
Since its release in 1995, PHP has been one of the most popular server-side languages for building web applications. It supports a wide range of web servers, databases, and operating systems. PHP developers use popular frameworks like Laravel, Symfony, and Zend to deploy and manage sites that serve high volumes of traffic. To help you monitor PHP performance, identify bottlenecks, and optimize your users’ experience, we’re pleased to announce APM & distributed tracing for PHP.
