Operations | Monitoring | ITSM | DevOps | Cloud

Datadog

Collecting Pivotal Cloud Foundry logs and metrics

So far in this series we’ve explored Pivotal Cloud Foundry’s architecture and looked at some of the most important metrics for monitoring each PCF component. In this post, we’ll show you how you can view these metrics, as well as application and system logs, in order to monitor your PCF cluster and the applications running on it.

Key metrics for monitoring Pivotal Cloud Foundry

In the first part of this series, we outlined the different components of a Pivotal Cloud Foundry deployment and how they work together to host and run applications. In this article we will look at some of the most important metrics that PCF operators should monitor. These metrics provide information that can help you ensure that the deployment is running smoothly, that it has enough capacity to meet demand, and that the applications hosted on it are healthy.

Pivotal Cloud Foundry architecture

Pivotal Cloud Foundry (PCF) is a multi-cloud platform for the deployment, management, and continuous delivery of applications, containers, and functions. PCF is a distribution of the open source Cloud Foundry developed and maintained by Pivotal Software, Inc. PCF is aimed at enterprise users and offers additional features and services—from Pivotal and from other third parties—for installing and operating Cloud Foundry as well as to expand its capabilities and make it easier to use.

Monitoring in the Cloud

Build an effective framework for monitoring AWS infrastructure and applications, however large or dynamic they may be. The elasticity and nearly infinite scalability of the AWS cloud have transformed IT infrastructure. Modern infrastructure is now made up of constantly changing, often short-lived components. This has elevated the need for new methods and new tools for monitoring.

Log analytics and dashboarding in Datadog

Achieving optimal performance can be challenging when you depend on separate platforms to monitor service health and to manage your logs. When data about your systems is spread across multiple platforms, investigating issues—and ultimately resolving them—takes longer and requires expertise with more tools. It takes more effort to identify real customer impact, as well as to verify that your responses to an incident are having the desired effect.

Datadog APM gains 3 superpowers: Trace Search, Service Map & Watchdog

Since we made Datadog APM generally available last year, we have continually added new features and support for new languages and frameworks to ensure that you can monitor every aspect of application performance. Datadog APM helps companies such as Airbnb, Square, and Zendesk to optimize application performance and deliver top-notch customer experiences.

Key metrics for AWS monitoring

Since 2006, Amazon Web Services (AWS) has spurred organizations to embrace Infrastructure-as-a-Service (IaaS) to build, automate, and scale their systems. Over the years, AWS has expanded beyond basic compute resources (such as EC2 and S3), to include tools like CloudWatch for AWS monitoring, and managed infrastructure services like Amazon RDS for database management.