Exam objectives — ASTRA Tech Sales Associate
D1. Solution architecture, integration and operating boundaries — 14.6%
D1.1 Given a scenario, trace the components supporting a customer-facing feature and distinguish their jobs.
Example concepts: application, connector, source system, identity.
D1.2 Given a scenario, trace a user request to its confirmed business result and identify an unverified hand-off.
Example concepts: request, response, persisted result.
D1.3 Given a scenario, interpret the sending and receiving API contracts and identify necessary field or meaning translations.
Example concepts: field types, lookup rules, pagination.
D1.4 Given a scenario, distinguish authentication from permission for a named operation.
Example concepts: identity, scope, denied action.
D1.5 Given a scenario, classify a cloud offer by what its provider and customer actually operate.
Example concepts: SaaS, PaaS, IaaS, separate services.
D1.6 Given a scenario, interpret freshness and response-time evidence without conflating display responsiveness with current data.
Example concepts: snapshot age, update cadence.
D2. Cloud and solution economics — 14.6%
D2.1 Given a scenario, compare cloud service boundaries against the customer’s ability to operate them before comparing prices.
Example concepts: operating obligations, staffing dependency.
D2.2 Given a scenario, separate software rights, one-time delivery and recurring service commitments.
Example concepts: entitlement, acceptance, service scope.
D2.3 Given a scenario, derive a billable quantity under the specified usage rule.
Example concepts: meter, unit, rounding.
D2.4 Given a scenario, compare alternative user quantities across an equivalent term.
Example concepts: seat-months, contracted period.
D2.5 Given a scenario, calculate an in-scope first-year cost without omitting or double-counting included work.
Example concepts: fees, internal allocation, cash cost.
D2.6 Given a scenario, interpret commitment thresholds and identify unverified financial assumptions.
Example concepts: minimums, overage, unknown work.
D2.7 Given a scenario, distinguish a spending notification from an enforced limit and sequence the approved response.
Example concepts: billing lag, continuity, approval.
D3. Security, assurance and operational trust — 12.5%
D3.1 Given a scenario, translate a described security event into the customer consequence and a testable requirement.
Example concepts: confidentiality, integrity, availability.
D3.2 Given a scenario, evaluate who is included in an identity-control test and identify coverage exceptions.
Example concepts: population, enforcement, exclusions.
D3.3 Given a scenario, trace the actual location and access boundary for each relevant data store or path.
Example concepts: primary, logs, backup, exports.
D3.4 Given a scenario, distinguish service restoration time from the point to which data can be restored.
Example concepts: RTO, RPO, evidence timestamp.
D3.5 Given a scenario, match assurance evidence to the exact control, population, period and claim.
Example concepts: control scope, expiry, test.
D4. AI value, quality and safe-use decisions — 12.5%
D4.1 Given a scenario, select a bounded AI use case consistent with approved inputs, reviewer availability and action authority.
Example concepts: drafting, deterministic alternatives, exclusions.
D4.2 Given a scenario, separate retrieved source evidence from model-generated content and unsupported assertions.
Example concepts: grounding, provenance, retention.
D4.3 Given a scenario, choose task-sufficient inputs under the stated data-use contract.
Example concepts: minimisation, identity routing, prohibited fields.
D4.4 Given a scenario, test an AI answer against the cited evidence rather than confidence language.
Example concepts: source support, correction, review.
D4.5 Given a scenario, calculate a measured workflow outcome after human review and rework.
Example concepts: eligible volume, quality denominator, time.
D4.6 Given a scenario, distinguish an instruction embedded in content from valid execution authority.
Example concepts: injection, attempted action, gateway result.
D5. Technical-commercial translation and defensible recommendations — 12.5%
D5.1 Given a scenario, construct a bounded integration or data-flow claim from the supplied component evidence.
Example concepts: sender, receiver, data, unknown paths.
D5.2 Given a scenario, identify a test and delivery-scope decision before promising the customer an integrated outcome.
Example concepts: acceptance sequence, included services.
D5.3 Given a scenario, recommend a conditional offer using operating fit, cost and documented gates.
Example concepts: price boundary, open dependencies.
D5.4 Given a scenario, turn a vague customer request into a measurable acceptance criterion.
Example concepts: actor, scope, timing, evidence.
D5.5 Given a scenario, calculate operational effort while separating modeled capacity from realised cash savings.
Example concepts: baseline, mix, exclusion.
D6. Discovery, stakeholders and decision sequencing — 10.4%
D6.1 Given a scenario, identify the highest-value unresolved discovery question behind a customer request.
Example concepts: outcome, owner, integration dependency.
D6.2 Given a scenario, identify who can approve each business, technical and commercial decision.
Example concepts: seniority versus authority, gate.
D6.3 Given a scenario, sequence the missing facts and decisions required before committing a proposal.
Example concepts: dependencies, owner, next action.
D7. Partner, channel and contracting boundaries — 10.4%
D7.1 Given a scenario, distinguish reseller, referral and separately contracted service responsibilities.
Example concepts: contract, bill, implement, support.
D7.2 Given a scenario, apply permission and approval limits to a partner claim or customer message.
Example concepts: discount, customer choice, exception.
D7.3 Given a scenario, prepare a conditional buyer/partner handover naming evidence, unresolved gates and next owners.
Example concepts: scope, review, hand-off.
D8. Evidence governance, approvals and responsible claims — 12.5%
D8.1 Given a scenario, identify which assurance document can be shared with a recipient under its stated conditions.
Example concepts: approval, named contacts, channel.
D8.2 Given a scenario, sequence the authorised response to a reported incident without inventing impact findings.
Example concepts: observed facts, owner, wording.
D8.3 Given a scenario, classify exact questionnaire claims by support, contradiction or missing evidence.
Example concepts: status, exception, next owner.
D8.4 Given a scenario, apply version-bound human approval to a changed draft or high-impact action.
Example concepts: approval record, changed content, gateway.
D8.5 Given a scenario, convert AI marketing claims into a bounded proposal with evidenced results and open release gates.
Example concepts: quality sample, retention, permitted stage.