Hazelcast is a distributed, in-memory computing platform for processing large data sets with extremely low latency. Its in-memory data grid (IMDG) sits entirely in random access memory, which provides significantly faster access to data than disk-based databases. And with high availability and scalability, Hazelcast IMDG is ideal for use cases like fraud detection, payment processing, and IoT applications.
HiveMQ is an open source MQTT-compliant broker for enterprise-scale IoT environments that lets you reliably and securely transfer data between connected devices and downstream applications and services. With HiveMQ, you can provision horizontally scalable broker clusters in order to achieve maximum message throughput and prevent single points of failure.
Browser (or UI) tests are a key part of end-to-end (E2E) testing. They are critical for monitoring key application workflows—such as creating a new account or adding items to a cart—and ensuring that customers using your application don’t run into broken functionalities. But browser tests can be difficult to create and maintain. They take time to implement, and configurations for executing tests become more complex as your infrastructure grows.
Logs provide a wealth of information that is invaluable for use cases like root cause analysis and audits. However, you typically don’t need to view the granular details of every log, particularly in dynamic environments that generate large volumes of them. Instead, it’s generally more useful to perform analytics on your logs in aggregate.
RethinkDB is a document-oriented database that enables clients to listen for updates in real time using streams called changefeeds. RethinkDB was built for easy sharding and replication, and its query language integrates with popular programming languages, with no need for clients to parse commands from strings. The open source project began in 2012, and joined the Linux Foundation in 2017.
Understanding how your users experience your application is critical—downtime, broken features, and slow page loads can lead to customer churn and lost revenue. Last year, we introduced Datadog Browser Tests, which enable you to simulate key user journeys and validate that users are able to complete business-critical transactions.
Creating security policies for the devices connected to your network is critical to ensuring that company data is safe. This is especially true as companies adopt a bring-your-own-device model and allow more personal phones, tablets, and laptops to connect to internal services. These devices, or endpoints, introduce unique vulnerabilities that can expose sensitive data if they are not monitored.
Datadog’s AWS integration brings you deep visibility into key AWS services like EC2 and Lambda. We’re excited to announce that we’ve simplified the process for installing the AWS integration. If you’re not already monitoring AWS with Datadog, or if you need to monitor additional AWS accounts, our 1-click integration lets you get started in minutes.
Google Cloud Platform (GCP) is a suite of cloud computing services for deploying, managing, and monitoring applications. A critical part of deploying reliable applications is securing your infrastructure. Google Cloud Audit Logs record the who, where, and when for activity within your environment, providing a breadcrumb trail that administrators can use to monitor access and detect potential threats across your resources (e.g., storage buckets, databases, service accounts, virtual machines).
Microsoft Azure is a cloud computing platform for building, deploying, and managing global-scale applications. With a wide range of offerings, including dozens of different services, Azure provides tools for users to create large and sophisticated systems for hosting any type of workload. But with the huge number of configuration options and resource types, understanding the health and performance of your applications in Azure can be challenging.
