VMware vRealize Operations and vRealize Log Insight assist cloud service providers to provide services across physical, virtual, and cloud infrastructures. Both can together correlate structured and unstructured data from applications to storage in a simple, easy-to-use, unified console. This is achieved by providing control over performance, capacity, and configuration for accurate future-planning, which helps in taking proactive action with policy-based configuration. vRealize Log Insight adds value to vRealize Operations by providing real-time log management based on intelligent grouping with innovative search capabilities for a quick resolution and enhanced operational analytics.

The following table shows Log Intelligence (LInt) core to VMware Cloud on AWS features:

DevOps end-to-end troubleshooting with Wavefront and Log Intelligence has the ability to cross-launch based on context (time, source, and custom tags ) and to extract metrics from logs.

The following diagram shows the data movement flow across Wavefront and Log Intelligence:

Developer teams get precise data from the Log Analytics tool after going through extensive filtering and they push this data to the Wavefront dashboard to get the desired output, which will help them to enhance application capabilities. This is a continuous cycle and all three tightly integrate with each other to achieve the final common objective.

Log Intelligence metrics have the following features:

• Ability to provide Number of critical errors and the along with number of warnings
• Uses Wavefront as the centralized alerting dashboard
• Forwards alerts raised from logs to Wavefront
• Cross-launch of Alerts related to logs correlation
• Application-aware correlation and cross-launches
• Content across both metrics and log

Wavefront is a cloud-native metrics-monitoring and analytics platform that is specifically designed to handle the high scale of modern cloud applications' velocity and dynamism. DevOps and developer teams who run true cloud-native apps (such as Box, and so on) use Wavefront to monitor their cloud services. Wavefront has capability to reach an unprecedented scale. The Wavefront platform collects metrics from distributed applications, containers, microservices, hybrid public cloud infrastructure, and even business data. Once metric data is in the Wavefront time-series database, we can apply powerful and flexible analytics in the form of the Wavefront Query Language.

Engineers use Wavefront to understand the performance of their cloud services and distributed applications at an unprecedented scale. We get instant visibility across all of our cloud services. We can troubleshoot faster and proactively alert and detect the leading indicators of anomalies with Wavefront. We have instant access and unified visibility drives agility in code release, enabling the same visibility across everything. Once Wavefront enters an organization, its adoption spreads across hundreds of engineers, enabling a self-service approach.

Wavefront is easy to implement and easy to scale with its analytics engine, the Wavefront Query Language, which has over 100 analytics functions within the Wavefront Query Language. It's easy to customize dashboards with analytics-driven visibility across cloud applications and infrastructures. Wavefront pricing is defined as per rate of ingestion and per host with vRealize Operations Manager. Customers can see metric rate consumption clearly, tweak it as needed, and use it for budgeting without any hidden costs. Wavefront data sources are native metrics ingestion by integrating open source agents, API, code libraries and events, metrics from logs, and other tools (DevOps and so on) . It can easily scale up to 4,000,000 packets per second (pps) . It has enterprise adoption across thousands of engineers within developer/DevOps teams. Wavefront has already proven SaaS offerings and successfully integrated with popular SaaS apps such as Box, Lyft, Intuit, Workday, and so on across thousands of developers.

Wavefront supports container technology, such as Docker, Pivotal Container Service (PKS), Kubernetes, and Elastic Container Service (ECS), out of the box. Container metrics are added and scaled without any issues or performance degradation. It is built from the ground up to scale. Greenfield customers can also leverage LInt/Insight with Wavefront while non-greenfield customers can opt for conversion of logs to metrics for other logging tools.

Wavefront is not an Access Policy Manager (APM) tool, but ingests APM metrics as any other APM tool. It also supports correlation with any other long term trending data source. It also supports code instrumentation with open source libraries, delivers applications visibility (StatsD, Micrometer, and DropWizard), and is ideal for microservices and dynamic custom applications at a high scale. Wavefront can complement existing APM tools. It supports predictive forecasting with Holt-Winters and Autoregressive Integrated Moving Average (ARIMA) forecasting algorithms. It can also integrate with more than 125 applications, and supports Azure, GCP, and AWS.