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SUSE OpenStack Cloud Crowbar Monitoring is an out-of-the-box solution for monitoring OpenStack-based cloud environments. It is provided as a cloud service to users. SUSE OpenStack Cloud Crowbar Monitoring meets different challenges, ranging from small-scale deployments to high-availability deployments and deployments with high levels of scalability.
The core of SUSE OpenStack Cloud Crowbar Monitoring is monasca, an open source Monitoring as a Service solution that integrates with OpenStack. The key features of SUSE OpenStack Cloud Crowbar Monitoring form an integral part of the monasca project. SUSE OpenStack Cloud Crowbar Monitoring extends the source code base of the project through active contributions.
Compared to the monasca community edition, SUSE OpenStack Cloud Crowbar Monitoring provides the following added value:
Packaging as a commercial enterprise solution
Enterprise-level support
The key features of SUSE OpenStack Cloud Crowbar Monitoring address public as well as private cloud service providers. They include:
Monitoring
Metrics
Log management
Integration with OpenStack
SUSE OpenStack Cloud Crowbar Monitoring is a highly scalable and fault tolerant monitoring solution for OpenStack-based cloud infrastructures.
The system operator of the cloud infrastructure and the service providers do not have to care for system monitoring software any longer. They use SUSE OpenStack Cloud Crowbar Monitoring to check whether their services and servers are working appropriately.
SUSE OpenStack Cloud Crowbar Monitoring provides comprehensive and configurable metrics with reasonable defaults for monitoring the status, capacity, throughput, and latency of cloud systems. SUSE OpenStack Cloud Crowbar Monitoring users can set their own warnings and critical thresholds and can combine multiple warnings and thresholds to support the processing of complex events. Combined with a notification system, these alerting features enable them to quickly analyze and resolve problems in the cloud infrastructure.
The Metrics agent is responsible for querying metrics and sending them to the Monitoring Service for further processing.
Metrics are self-describing data structures that are uniquely identified by a name and a set of dimensions. Each dimension consists of a key/value pair that allows for a flexible and concise description of the data to be monitored, for example, region, availability zone, service tier, or resource ID.
The Metrics Agent supports various types of metrics including the following:
System metrics, for example, CPU usage, consumed disk space, or network traffic.
Host alive checks. The agent can perform active checks on a host to determine whether it is alive using ping (ICMP) or SSH.
Process checks. The agent can check and monitor a process, for example, the number of instances, memory size, or number of threads.
HTTP endpoint checks. The agent can perform up/down checks on HTTP endpoints by sending an HTTP request and reporting success or failure to the Monitoring Service.
Service checks. The agent can check middleware services, for example, MySQL, Kafka, or RabbitMQ.
OpenStack services. The agent can perform specific checks on each process that is part of an OpenStack service.
Log metrics. The agent can check and monitor the number of critical log entries in the log data retrieved from the cloud resources.
Your individual agent configuration determines which metrics are available for monitoring your services and servers. For details on installing and configuring a Metrics Agent, see Deployment Guide using Crowbar.
As soon as an agent is available, you have access to the SUSE OpenStack Cloud Crowbar Monitoring monitoring features. You work with a graphical user interface that is seamlessly integrated into your cloud infrastructure. Based on OpenStack horizon, the user interface enables access to all monitoring functionality and the resulting large-scale monitoring data. A comfortable dashboard visualizes the health and status of your cloud resources.
SUSE OpenStack Cloud Crowbar Monitoring provides functions for alarm and notification management. Template-based alarm definitions allow for monitoring a dynamically changing set of resources without the need for reconfiguration. While the number of underlying virtual machines is changing, for example, this ensures the efficient monitoring of scalable cloud services. Alarm definitions allow you to specify expressions that are evaluated based on the metrics data that is received. Alarm definitions can be combined to form compound alarms. Compound alarms allow you to track and process even more complex events. Notifications can be configured in order to inform SUSE OpenStack Cloud Crowbar Monitoring users when an alarm is triggered.
With the increasing complexity of cloud infrastructures, it is becoming more and more difficult and time-consuming for the system operator to gather, store, and query the large amounts of log data manually. To cope with these problems, SUSE OpenStack Cloud Crowbar Monitoring provides centralized log management features.
SUSE OpenStack Cloud Crowbar Monitoring stores the log data in a central database. This forms the basis for visualizing the log data for the SUSE OpenStack Cloud Crowbar Monitoring users. Advanced data analysis and visualization of the log data is supported in a variety of charts, tables, and maps. Visualizations can easily be combined in dynamic dashboards that display changes to search queries in real time.
The log data from a large number of sources can be accessed from a single dashboard. Integrated search, filter, and graphics options enable system operators to isolate problems and narrow down potential root causes. SUSE OpenStack Cloud Crowbar Monitoring thus provides valuable insights into the log data, even with large amounts of data resulting from highly complex environments.
Based on OpenStack horizon, the customizable dashboards are seamlessly integrated into your cloud infrastructure. They enable user access to all log management functionality.
GUI-based alarm and notification management is also supported for log data. Based on a template mechanism, you can configure alarms and notifications to monitor the number of critical log events over time. Compound alarms can be created to analyze more complex log events. This automation of log handling guarantees that you can identify problems in your their infrastructure early and find the root cause quickly.