Lesson 1Choosin partition key an sort key patterns fi tasks an histories (composite keys, prefixes)Learn how fi choose effective partition an sort key patterns fi tasks an history items. Explore composite keys, key prefixes, an design tradeoffs dat impact query flexibility, scalability, an write distribution in production systems, yuh know.
Composite key design fi task an history itemsUsin key prefixes fi group related task recordsDesignin keys fi even write an read distributionPatterns fi time-ordered task history queriesLesson 2Backup, restore, an point-in-time recovery considerations fi task data an history logsLearn how fi protect task an history data wid backups an recovery options. Understand on-demand backups, point-in-time recovery, restore workflows, an how fi design schemas an processes dat support safe, testable recovery, mi fren.
Enablin an managin point-in-time recoveryCreatin an restorin on-demand backupsDesignin restore workflows fi task tablesTestin recovery an minimizin data lossLesson 3Data serialization an attribute types: strings, numbers, maps, lists, booleans, an tradeoffs fi complex attributesExplore DynamoDB attribute types fi task data, includin strings, numbers, maps, lists, an booleans. Learn serialization strategies fi complex fields, tradeoffs fi nested structures, an how choices affect indexin an query costs, yuh hear.
Usin scalar types fi core task attributesMaps an lists fi flexible metadata fieldsStorin timestamps an numeric countersTradeoffs a nested an complex attributesLesson 4Item attribute design: task item schema wid types (taskId, title, description, status, updatedAt, metadata)Define a clear schema fi task items, includin identifiers, titles, descriptions, status, timestamps, an metadata. Learn type choices, required versus optional fields, an patterns dat support evolution widout migrations, seen.
Core fields: taskId, title, an descriptionModelin status an updatedAt consistentlyDesignin flexible metadata structuresSchema evolution widout heavy migrationsLesson 5Access patterns mappin: queries fi single task, task history ordered by time, listin recent tasks, pagination strategiesMap real access patterns to DynamoDB queries fi tasks an histories. Learn fi query a single task, fetch ordered history, list recent tasks, an implement pagination usin key conditions, filters, an careful sort key design, yuh know.
Queryin a single task an its latest stateFetchin task history ordered by timestampListin recent or active tasks efficientlyPagination wid LastEvaluatedKey an limitsLesson 6Primary key an secondary index strategies: GSIs an LSIs fi alternative queries (by status, by user)Design primary keys an secondary indexes fi support alternative queries, such as by status or user. Learn when fi use GSIs versus LSIs, index key choices, projected attributes, an how indexes affect cost an throughput, mi bredda.
Choosin primary keys fi main task accessDesignin GSIs fi status-based queriesIndexes fi queryin tasks by user or ownerProjection choices an index cost impactsLesson 7Modelin conditional updates an optimistic concurrency wid ConditionalExpression an attribute_exists/attribute_not_existsModel safe concurrent updates to tasks usin DynamoDB conditions. Learn optimistic concurrency wid version attributes, ConditionalExpression, an attribute_exists checks fi prevent lost updates an enforce business rules, yuh see.
Version attributes fi optimistic concurrencyUsin ConditionalExpression in updatesattribute_exists an attribute_not_exists usageHandlin conditional check failures safelyLesson 8Item attribute design: history item schema wid types (taskId, eventId, status, previousStatus, changedBy, timestamp, reason)Design a robust schema fi task history items, includin identifiers, status transitions, audit fields, an reasons. Learn how fi choose attribute types, enforce consistency, an support efficient queries an analytics on task lifecycle events, true.
Core identifiers: taskId an eventId choicesModelin status an previousStatus transitionsCapturin changedBy, timestamp, an reasonChoosin attribute types fi history fieldsLesson 9DynamoDB table selection an rationale fi single-table vs multi-table designsUnderstand when fi use a single DynamoDB table versus multiple tables fi task trackin. Compare isolation, cost, an operational complexity, an learn how fi align table design wid microservices, ownership, an access patterns, yuh know.
When a single table fits task trackin needsWhen multiple tables are di better choiceModelin ownership an service boundariesCost, limits, an operational tradeoffsLesson 10DynamoDB best practices: capacity modes, write patterns, conditional writes, atomic counters, transactions, an TTL fi old history entriesApply DynamoDB best practices to task trackin workloads. Compare capacity modes, design efficient write patterns, use conditional writes, atomic counters, transactions, an TTL fi manage old history entries an control storage growth, seen.
Choosin between on-demand an provisioned capacityDesignin write patterns fi hot task itemsUsin conditional writes an atomic countersTransactions an TTL fi agin history data
