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Descriptor matching and Lowe's ratio test
Match by nearest-neighbor descriptor distance; Lowe's ratio test keeps a match only if the best is clearly better than the second-best, rejecting ambiguous ones.
SIFT versus SURF versus ORB
SIFT is most accurate but slow with float descriptors; SURF approximates SIFT for speed; ORB is fast, binary, and free, ideal for real-time and embedded.
SIFT scale and rotation invariance
Scale-space extrema via difference-of-Gaussians give scale invariance; a dominant gradient orientation gives rotation invariance; the descriptor is a normalized gradient histogram.
Image gradients, Sobel, and Canny
The gradient measures local intensity change in x and y; Sobel approximates it via convolution kernels; Canny uses gradient magnitude and direction plus non-max suppression and hysteresis.
Harris corner detector and corner stability
Harris finds points where intensity changes strongly in all directions using the structure tensor of gradients; corners are well localized in two directions, unlike edges.
Image rotation: forward versus inverse mapping
Forward mapping sends source pixels to non-integer destinations, leaving holes and overlaps; inverse mapping iterates over output pixels, finds the source location, and interpolates.
Removing salt-and-pepper noise
Use a median filter; it replaces a pixel with the neighborhood median so extreme outliers are discarded.
Lens distortion and camera calibration
Radial distortion bends straight lines (barrel/pincushion), tangential comes from lens-sensor misalignment; calibrate with a known pattern to estimate intrinsics and distortion coefficients.
RGB versus HSV color spaces
RGB mixes three light channels; HSV separates hue, saturation, value so color identity decouples from brightness.
Migrating a stateful monolith to the cloud
Assess and inventory, pick a migration pattern like rehost or replatform, handle data migration and cutover, mitigate downtime and data-loss risk.
Diagnosing slow auto-scaled PaaS workloads
Application metrics like request latency, throughput, and DB query time; infrastructure metrics like CPU, memory, and scaling lag.
Blue/green versus canary deployments
Blue/green flips all traffic between two full environments; canary shifts a small slice gradually while watching metrics.
High availability versus fault tolerance
HA minimizes downtime via redundancy and failover; fault tolerance survives failure with zero interruption.
Difference between metrics and logs
Metrics are aggregated numeric time series good for trends and alerting; logs are discrete timestamped event records good for detailed root-cause analysis.
Design a multi-tenant model serving platform
Share infrastructure to cut cost while enforcing tenant data isolation, fair resource allocation against noisy neighbors, and per-tenant performance via quotas and autoscaling.
Event bus versus message queue for triggers
A queue is point-to-point buffered work for one consumer group; an event bus routes and filters one event to many decoupled subscribers. Event bus wins when many independent services must react.
Optimize cost of a big-data analytics platform
Storage tiering and lifecycle plus compression and partitioning; compute via spot instances, right-sizing, and efficient file formats; query and pipeline optimization to scan less data.
Strangler Fig with serverless and an event bus
API Gateway acts as the routing facade, new features run as Lambda functions, an event bus decouples and fans out to new services, and traffic shifts feature by feature until the monolith…
Configure a Kubernetes Horizontal Pod Autoscaler
HPA adjusts replica count toward a target CPU metric, needs the metrics server and pod resource requests, and scales a deployment between min and max.
When to choose bare metal over a VM
Bare metal suits latency-sensitive or high-throughput workloads needing no hypervisor overhead, single-tenant isolation for compliance, or direct hardware and licensing access.