DevOps Analytics

Development operations (DevOps) is a set of processes and practices to prepare for and manage the application lifecycle. By implementing a DevOps methodology, you can shorten your development schedule and greatly improve the quality of your application and customer experience, by identifying and addressing issues earlier in the production lifecycle and by increasing the performance of your application. Typically, DevOps is divided into four phases of the application lifecycle:

1. Planning
2. Development
3. Deployment
4. Operations

DevOps analytics is the process of collecting, analyzing, reporting, and visualizing data throughout the process of all four stages of DevOps production.

For each phase of the application lifecycle, you should be following a process to collect, analyze, report, and visualize the data:

1. Define your goals and KPIs.
2. Extract logs, collect events, and collect relevant data.
3. Calculate your KPI results and publish them to your dashboards and reports.
4. Update the process to improve efficiency and identify more impactful data to analyze, insights gained,

To gain insights from the data, you may want to set up three types of reporting solutions:

• Visualization dashboards
• Automated reports
• Custom reports

DataOps is a methodology that applies the processes and practices from DevOps, Agile methodology, and Lean manufacturing to automation-based data methods. You establish a data lifecycle that includes preparing and collecting your data, storing your data, processing the data, analyzing the data, visualizing the data to showcase insights, distributing the insights, archiving data that is no longer active or needed, and then deleting or destroying the data. The process exists to establish and maintain data integrity, security, and usability.

Azul Intelligence Cloud (IC) provides the kind of DevOps analytics that can help you shorten your development schedule and greatly improve the quality of your application and customer experience, by identifying and addressing issues earlier in the production lifecycle and by increasing the performance of your application.

Specifically, IC provides the following capabilities:

• Code Inventory: Identify unused and dead code that can be removed to improve code maintainability. Because IC runs on production code, it can identify code that is actually in use, as well as code that is never loaded by the JVM. With continuous monitoring over time, you can ensure that developers work only on active code, which can significantly improve a team’s development velocity. Learn more about Code Inventory. Learn more about Code Inventory.
• Vulnerability Detection: Identify Common Vulnerabilities and Exposures (CVEs), aka vulnerabilities at the class level to dramatically reduce false positives. Most vulnerability detectors, such as Software Composition Analysis (SCA) tools, operate at the jar level on non-production code and therefore generate far too many alerts that must be investigated, resulting in cybersecurity burnout. Learn more about Vulnerability Detection.
• JVM Inventory: Continuously identify all JVMs in use across the extended enterprise so you can better control costs and risks. IC reports key data such as the vendor, when the JVM was last run (if ever), and the application it ran so you can better identify unsanctioned, unused and unlicensed instances.

Intelligence Cloud works on any JVM or Java distribution, including OpenJDK distributions from Azul, Oracle, Amazon (Corretto), Microsoft, RedHat, and Eclipse Temurin (Adoptium).