Pivotal Cloud Foundry Metrics

Quickly Troubleshoot Cloud-Native Applications

Pivotal Cloud Foundry Metrics stores and graphically represents logs, metrics, and event data from applications running on Pivotal Cloud Foundry to help engineers better understand application health and performance. With Pivotal Cloud Foundry Metrics, engineers diagnose system failures and related issues in minutes, not hours!

Quickly Diagnose System Failure and Latency

Metrics, logs, and event data are aggregated and displayed via intuitive, interactive visualizations. Use Trace Explorer to understand the scale of interactions between components.

Accurately Identify Issues with Complete Data

Pivotal Cloud Foundry Metrics includes all system data, so there’s no need to slog through several monitoring and logging interfaces. And because everyone sees the same, complete data, there’s no more arguing over which system has the best data.

Every Engineer Becomes a Better Troubleshooter

To accelerate incident resolution times, SREs need context. That’s exactly what Pivotal Cloud Foundry Metrics delivers with Trace Explorer. Engineers no longer need intimate knowledge of the holistic system to find issues.

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Troubleshooting App Health and Performance with PCF Metrics
Pivotal Cloud Foundry Metrics Overview

Pivotal Cloud Foundry Metrics helps operators and developers better understand the health and performance of Pivotal Cloud Foundry and all apps running on the platform. The module helps teams answer these questions:

  • What went wrong and when? Application metrics provide the answer. Metrics reveals the time window when high network latency occurs and average response times.
  • Why did it go wrong? Logs and metrics - such as API calls, exact response times, parameters passed, etc. - together usually provide enough information to figure out why latency occurred.
  • Who is the culprit behind what went wrong? Events include external bits of information such as when app source code was changed and whether an app was moved to another container on an underperforming cell. Correlating events with metrics and logs is often the final piece of the puzzle.

More about Pivotal Cloud Foundry Metrics




Integration Features

Automate periodic backups and allow for restoring from a backup if needed.

Dynamically scale the service as bound applications require more or less capacity.

Version choice. Operators can let developers choose between multiple versions of the software when creating an instance.

Get visibility into details of service operation through standard monitoring and logging tools for products and Pivotal Cloud Foundry. Receive alerts about detected problems faster problem resolution.

Option for fully automated management of the service on Pivotal Cloud Foundry. Monitoring, failure recovery, and software updates with zero-to-minimal downtime.

The service is documented with instructions for setup and operation.

Multi-Availability Zone support. Make use of multiple availability zones in cloud deployments to support failover.


How it Works

Pivotal Cloud Foundry Metrics displays the following:

  • Container Metrics: A visual graph of CPU, memory, and disk usage percentages.
  • Network Metrics: A visual graph of requests, HTTP errors, and response times.
  • Application Events: A visual graph of update, start, stop, crash, SSH, and staging failure events.
  • Logs: A list of application logs that can be searched, filtered, and downloaded for further interrogation.
  • Trace Explorer: A visual graph that traces requests between applications and their endpoints, along with the corresponding logs.

Read the documentation

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