Scheduling
Scheduling is the planning and coordination of when and in what order activities or computational work occur, potentially assigning them to available resources subject to constraints.
Data Pipelines with Apache Airflow, Second Edition
A schedule is a rule that specifies when a workflow should run.
- How it is used
- Automates DAG runs for recurring data processing instead of requiring manual triggers.
- How deep it goes
- Works through schedule parameters, catchup, and trigger-versus-interval timing; defers asset-based scheduling.
- Examples
- Uses daily website-event statistics and a midnight-UTC cron timetable with dated output files.
- What you can do after
- Operate/configure it by setting DAG dates, a timetable, and catchup to control current and historical runs.
Read how Data Pipelines with Apache Airflow, Second Edition explains scheduling →
Acing the Certified Kubernetes Administrator Exam, Second Edition
The process of deploying applications to Kubernetes by assigning their pods to suitable execution resources.
- How it is used
- Deploys and places Kubernetes workloads while supporting node selection, resource allocation, configuration, and exam-oriented administration tasks.
- How deep it goes
- Defines scheduler assignment and resource checks, then works through labels and selectors; it stops short of deeper scheduler internals.
- Examples
- Demonstrates labeling kind-worker as disktype=ssd, selecting it in pod YAML, and verifying the running pod with kubectl output.
- What you can do after
- Operate/configure pod placement by labeling nodes, editing YAML selectors, applying workloads, and verifying their assigned nodes.
Read how Acing the Certified Kubernetes Administrator Exam, Second Edition explains scheduling →
Kubernetes in Action, Second Edition
Scheduling is the process of selecting suitable compute nodes on which workloads should run.
- How it is used
- Places application pods on worker nodes so Kubernetes can run and maintain containerized workloads.
- How deep it goes
- Explains pod assignment, Kubelet reaction, image startup, and replacement behavior without detailing node-selection rules.
- Examples
- Uses a kubectl deployment, Pending pod output, scheduling events, image pulling, container creation, and startup.
- What you can do after
- Operate scheduling indirectly by creating a deployment and inspecting pod status and scheduling events with kubectl.
Read how Kubernetes in Action, Second Edition explains scheduling →
Architecture Modernization: Socio-technical alignment of software, strategy, and structure
A timeline is a chronological visual arrangement of domain events that represents the sequence of activities or occurrences in a business domain.
- How it is used
- Uses a chronological event arrangement to help groups map business knowledge, tell an end-to-end story, and identify conversations.
- How deep it goes
- Explains construction, sorting, walk-through, notation, and chunking, while deliberately avoiding rigid precision about domain boundaries.
- Examples
- Uses business events, seeded whitespace, hot spots, terminology notes, and grouped event sequences as concrete artifacts.
- What you can do after
- Apply it via EventStorming to map a business process, surface uncertainty, and compare possible domain or subdomain groupings.
D3.js in Action, Third Edition
A timeline is a visual representation that arranges events or measurements along an ordered temporal dimension.
- How it is used
- Uses timelines to explore how events, measurements, and related categories change across periods.
- How deep it goes
- Explains data classification, visual encodings, D3 axes, and brushing, but stops short of a complete timeline implementation.
- Examples
- Demonstrates Van Gogh’s paintings, drawings, letters, cities, and Nobel laureate years through timelines and selectable ranges.
- What you can do after
- Build it from scratch by mapping attributes to timeline encodings and adding D3 brushing to filter a selected time range.
Read how D3.js in Action, Third Edition explains scheduling →
Related concepts
- workflow jobconfigures · A workflow job is an executable unit of work that groups tasks or steps with the logic and requirements needed to run them.
- node selectorconfigured by · A node selector is a Kubernetes scheduling constraint that restricts a pod or workload to nodes having specified matching labels.
- ant colony optimizationaddressed by · Ant colony optimization is a population-based probabilistic optimization technique in which artificial agents use simulated pheromone trails to guide the search for good solutions.
- poduses · A Kubernetes Pod is the smallest deployable unit in Kubernetes, grouping one or more co-located containers that share networking and other resources.
- parallelismuses · Parallelism is the concurrent execution of multiple computational operations, often across multiple processing resources.
- sequential processinguses · The execution of operations one after another in a defined order, without overlapping their progress.
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