Cloud Native Architecture

A team runs a stateless web API whose traffic spikes unpredictably during marketing campaigns. Each pod is already sized correctly for a single request stream, but the application cannot benefit from more CPU or memory per instance because it is single-threaded. The team wants the application to handle sudden bursts of concurrent users automatically. Which autoscaling approach best fits this situation?

A large retail company runs Kubernetes in production but does not sell cloud native software. Their platform team wants to influence CNCF project roadmaps, share real-world adoption experiences, and get guidance on evaluating projects — without becoming maintainers of any project. Which CNCF community group is designed specifically for organizations in this position?

A startup has built an open-source tool that automates cloud native cost analysis. The team wants to donate the project to the CNCF to increase its visibility, gain neutral governance, and grow a broader contributor community. They are unsure which entry point in the CNCF process is appropriate for a brand-new, early-stage project seeking initial acceptance into the foundation. Which CNCF maturity level should they target for their initial project submission?

A platform team at your company is selecting an open source service mesh to adopt for a mission-critical production environment. Leadership requires that the chosen CNCF project demonstrates proven adoption, a healthy contributor community, and strong governance before it is trusted for production. Which CNCF project maturity level best signals that a project meets these criteria?

A platform team at your company is evaluating a new open-source tool they found in the CNCF landscape. They notice it was recently accepted into the CNCF at the earliest maturity level, has a small number of contributors, and is intended primarily for early adopters and experimentation rather than production-critical workloads. Which CNCF project maturity level best matches this description?

A cloud native platform team wants to contribute domain-specific expertise (such as storage or observability) to help review projects and produce best-practice guidance under the CNCF's technical governance structure. Which body within the CNCF is organized around specific technical domains to provide this kind of focused guidance and support to the Technical Oversight Committee?

A company wants to contribute an internal project to the CNCF and is researching how the foundation is governed. They want to understand which body is responsible for defining the technical vision, reviewing and approving new projects into the CNCF, and overseeing project maturity progression. Which group performs this role?

A platform team runs a stateless web service that experiences unpredictable traffic spikes throughout the day. During peak periods, response times degrade because there are too few replicas, while at night the fixed replica count wastes resources. The team wants the number of running Pods to increase and decrease automatically based on observed CPU utilization. Which cloud native autoscaling approach directly addresses this need?

A retail company runs a monolithic e-commerce application. During flash sales, only the checkout functionality experiences extreme load, but the team must scale the entire application to handle it, wasting resources on the product-catalog and user-profile components. The architecture team wants to redesign the system so that heavily-used functions can be scaled independently of lightly-used ones. Which cloud native architectural approach directly addresses this requirement?

A development team maintains a large monolithic application. Every small change to the billing feature requires redeploying and re-testing the entire application, causing slow release cycles and coordination overhead across teams. Leadership asks which cloud native architectural approach would best allow individual features like billing to be developed, deployed, and scaled independently.

An SRE team is building an observability strategy for a new microservices platform. They want to (1) alert when a service's error rate crosses a threshold over time, (2) inspect the exact stack trace and message emitted when a specific request failed, and (3) understand how a single user request flowed across six services to find where time was spent. Which combination of telemetry signals correctly maps to these three needs, in order?

A platform team runs an e-commerce application composed of a dozen microservices. Customers report that checkout is intermittently slow, but each individual service reports healthy CPU, memory, and error rates. The team needs to determine which service in the request path is introducing the delay and how much time is spent in each hop. Which observability signal is best suited to answer this question?

Your organization runs services written in Go, Java, and Python. The platform team wants to instrument all of them to emit metrics, logs, and traces using a single, vendor-neutral set of APIs and SDKs, so the backend observability tool can be swapped later without rewriting application instrumentation. Which CNCF project is designed to meet this requirement?

Your operations team wants to build a dashboard that shows aggregated CPU and memory utilization trends across all pods over time, and to trigger an alert when memory usage crosses a threshold for 5 minutes. Which observability signal and tool combination is best suited for this requirement?

A platform team is adding monitoring to a new microservice. They deploy Prometheus and want it to begin collecting the service's metrics. The service already exposes numeric metrics in the Prometheus text format at an HTTP path. What must happen for Prometheus to start gathering these metrics using its standard model?

A startup runs an image-thumbnail generator that is triggered only when users occasionally upload photos—sometimes hundreds per minute during promotions, but often zero requests for hours overnight. The team wants to minimize compute cost during idle periods while still handling sudden bursts without manual capacity planning. Which cloud native approach best fits this workload?

A team runs an image-processing function that is triggered only when users occasionally upload photos. Between uploads, there can be hours of no activity, and the team wants to avoid paying for idle compute while still handling sudden bursts of uploads automatically. Which cloud native architectural approach best fits these requirements?