To complement distributed tracing, runtime metrics, log analytics, synthetic testing, and real user monitoring, we’ve made another addition to the application developer’s toolkit to make troubleshooting performance issues even faster and simpler. Today, we’re excited to introduce Profiling—an always-on, production profiler that enables you to continuously analyze code-level performance across your entire environment, with minimal overhead.
Amazon Managed Streaming for Apache Kafka (MSK) is a fully managed service that allows developers to build highly available and scalable applications on Kafka. In addition to enabling developers to migrate their existing Kafka applications to AWS, Amazon MSK handles the provisioning and maintenance of Kafka and ZooKeeper nodes and automatically replicates data across multiple availability zones for high availability.
Istio is an open source service mesh that was released in 2017 as a joint project from Google, IBM, and Lyft. By abstracting the network routes between services from your application logic, Istio allows you to manage your network architecture without altering your application code. Istio makes it easier to implement canary deployments, circuit breakers, load balancing, and other architectural changes, while also offering service discovery, built-in telemetry, and transport layer security.
In Part 1, we showed you the metrics that can give you visibility into your Istio service mesh and Istio’s internal components. Observability is baked into Istio’s design—Mixer extracts attributes from traffic through the mesh, and uses these to collect the mesh-based metrics we introduced in Part 1. On top of that, each Istio component exposes metrics for its own internal workings.
In Part 2, we showed you how to use Istio’s built-in features and integrations with third-party tools to visualize your service mesh, including the metrics that we introduced in Part 1. While Istio’s containerized architecture makes it straightforward to plug in different kinds of visualization software like Kiali and Grafana, you can get deeper visibility into your service mesh and reduce the time you spend troubleshooting by monitoring Istio with a single platform.
Web server logs and other access logs from technologies such as NGINX, Apache, and AWS Elastic Load Balancing (ELB) provide a wealth of key performance indicators (KPIs) for monitoring the health and performance of your application and understanding your users’ experience. These logs tell you how long pages take to load, where errors are occurring, which parts of your application are requested the most, and much more.
Last year, we introduced Watchdog to help Datadog APM users detect performance problems in their services by applying machine learning algorithms to automatically surface anomalies. Today, we’re excited to announce Watchdog for Infra, which expands the scope of Watchdog to automatically provide ongoing visibility into the health and performance of your infrastructure with no setup required.
In a world where the applications we run are constantly changing, the number of monitored metrics and events is skyrocketing, and responsibility for system components is fragmented across teams, it becomes increasingly difficult to pinpoint possible root causes of an issue in a timely manner. To address this challenge, we’re introducing Metric Correlations, which automatically finds candidates for the causes of an issue by searching your system for correlated metrics.
SAP HANA is a data analytics platform that uses an in-memory, column-oriented data store to efficiently execute transactional (OLTP) and analytical (OLAP) queries. It can perform these queries against its own tables, or against data that resides in remote, non-SAP databases like Hadoop or SQL Server. SAP HANA also serves as the database behind SAP’s S/4HANA ERP platform. Datadog’s new integration helps you better understand the health and performance of your SAP HANA systems.
Cilium is an open source technology that delivers network security to large-scale containerized environments at the packet and application levels. Cilium integrates easily with your Kubernetes clusters, either self-managed or managed services (e.g., Amazon EKS, Google GKE, and Microsoft AKS). You can also deploy Cilium to Docker environments using Mesos.
