Orchestration Model
What a cluster scheduler decides for you: where a workload lands, how many copies run, and what happens when one dies. Interviewers ask because running a container and running a fleet differ.
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- Declarative Workload Specs4 questions
- Co-Located Container Groups5 questions
- Long-Running & Batch Workloads5 questions
- Control Loop & Reconciliation5 questions
- Scheduling & Placement Constraints5 questions
- Self-Healing & Rescheduling5 questions
- Control vs Data Plane5 questions
- Shared Clusters & Quotas4 questions
questions
page 2 of 2A change request moves an order service's workload spec from three copies to six and swaps its image digest — what can the reviewer conclude, and what must they check elsewhere?
basics
~20 sThe diff proves intent and nothing else: exactly these two fields are being changed, and the document is the complete statement of what is wanted. Whether six copies fit, what defaults apply unseen, and what is running today are all read elsewhere.
On a shared cluster, when is dedicating a group of hosts to one workload class worth the capacity it strands?
basics
~20 sDedicated hosts are worth it when the workloads genuinely differ in the hardware they need, the interference they can tolerate, or the separation required of them — not when one team simply wants to be treated as more important.
A batch job declares 500 required completions with 20 attempts running at once — what does the platform count, and when does it stop?
basics
~20 sIt counts clean finishes, not started attempts. The at-once number is only a width limit: the platform keeps roughly that many attempts in flight, tops them up as each one ends, and marks the job finished when 500 have succeeded.
What must a team's own controller do to reconcile a new declared object type the way the platform's built-in loops do?
basics
~20 sA custom controller must register a declared type, be triggered by an object's identity rather than an event payload, re-read declared and live state on every pass, act idempotently, and report progress instead of failing terminally.
On a managed control plane, which failures become the provider's problem and which stay yours?
basics
~20 sThe provider runs the deciding half — the API, its state store and that store's backups — and is the only party who can repair it. Hosts, node agents, workloads and the declared state you put in stay yours.
A batch group's work container exits successfully but its metrics helper keeps running — why does the group never finish?
basics
~20 sCompletion is a property of the group, not of one member. A run-to-completion group is done only once its members have stopped, so a helper with no exit condition keeps the group alive and the run never records success.
A network fault makes twenty hosts stop reporting at once - what is the risk if the platform replaces everything they were running?
basics
~20 sMass replacement can turn an observation problem into a real outage: the surviving hosts cannot hold the whole fleet, every replacement pays a cold start at once, and if the hosts were never down, the cluster has just doubled its running workloads.
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