Cache shared flag rules or configuration separately from evaluated results. Evaluate each request with its current tenant context; if you cache a result, include the flag key and every context attribute that can change the decision in the cache identity. Then set an explicit maximum age and decide what the application does before synchronization and during an outage. No single TTL is safe for every provider, SDK, tenant, or flag.
First decide what the cache contains
A feature-flag evaluation is not just a lookup by flag name. Its result can depend on the evaluation context: for example, a tenant identifier or other targeting attributes. OpenFeature describes context as information supplied for dynamic evaluation, and its specification requires an optional string targeting key to identify the subject of an evaluation. OpenFeature’s Evaluation Context specification
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That makes two different caching strategies easy to confuse:
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- Evaluated-result cache: Stores an outcome such as “on” or “off” for a particular flag and context. The entry is safe to reuse only when the next evaluation has the same decision-relevant context and uses suitably current rules.
For an application-level result cache, a reasonable identity is a canonical representation of the flag key, tenant identity, all other targeting attributes that can affect the result, and—if available and needed for invalidation—the rules or configuration version. This is an application design, not a vendor-prescribed universal key format. Omitting an attribute that changes targeting can return one tenant’s decision to another tenant, or reuse a result after that tenant’s relevant attributes change.
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Choose where evaluation happens
The cache boundary depends on the SDK type. LaunchDarkly distinguishes server-side SDKs, which can receive rulesets in trusted infrastructure and evaluate locally, from client-side SDKs, which rely on the service for flag rules and receive evaluated results. See LaunchDarkly’s SDK type guidance.
| Approach | What is cached or evaluated | What to account for |
|---|---|---|
| Server-side local evaluation | The SDK can cache a shared ruleset and evaluate it in-process with the request’s tenant context. LaunchDarkly | Pass the relevant context on every evaluation. A shared ruleset does not make evaluated results interchangeable across tenants. |
| Client-side evaluation | The client-side SDK relies on the service for rules and receives evaluated results. LaunchDarkly | Use only client-safe data and credentials. Client environments are inspectable; do not put server-side SDK keys in them. |
| Configuration retrieval through a local agent | AWS AppConfig Agent polls for configuration updates and caches configuration locally for applications to retrieve through localhost. AWS AppConfig retrieval guidance | Confirm the agent’s update and persistence behavior for your deployment; local retrieval does not itself establish a universal maximum age. |
These approaches are not interchangeable in every system. Compare request latency, network dependence, exposure of targeting rules or identifiers, and the operational consequences of using old configuration. The right choice depends on where trusted evaluation can occur and how harmful a stale decision would be.
Set a maximum staleness policy, not a guessed TTL
A cache’s refresh mechanism tells you how it is updated; it does not automatically define how old a value may safely be for your product. LaunchDarkly documents streaming updates by default and polling as an option. It also says its SDK uses a local feature store if the connection is lost, and that the default in-memory cache does not expire. Those are LaunchDarkly-documented behaviors, not guarantees for other providers or SDK versions. LaunchDarkly architecture documentation
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteAWS AppConfig Agent polls and keeps configuration locally available, but the retrieval documentation does not establish a cross-provider or universally safe tenant-specific TTL. AWS AppConfig retrieval guidance Choose an allowed age according to the impact of applying an old setting, and verify the actual refresh and persistence semantics of the SDK or agent version you deploy.
- For a low-impact presentation choice, serving a last-known value briefly during a provider outage may be acceptable.
- For a high-impact permission, billing, or safety decision, define whether stale data is prohibited, whether the operation must stop, or whether a conservative code-defined fallback is safer.
- Specify what happens when the allowed age is exceeded: reject the cached result, use a fallback, or block the dependent operation. Do not leave this to an accidental cache default.
Define startup, outage, and recovery behavior
Before the first successful synchronization, there may be no current ruleset to evaluate. A fallback can therefore be returned while a provider initializes. OpenFeature’s Web SDK guidance recommends waiting for provider readiness to prevent evaluations defaulting during initialization. OpenFeature Web SDK
- At startup: For an operation that cannot safely use a default, gate it on provider readiness or synchronization. For a less critical feature, choose an explicit default and document its effect.
- During disconnection: Decide whether the implementation may use a last-known local value, a code-defined fallback, or neither. Apply the maximum-age rule rather than assuming local availability means freshness.
- After reconnection: Confirm that updated configuration is observed and that application-level evaluated-result entries are invalidated or versioned as appropriate. A refreshed shared ruleset alone does not make a separately cached result current.
Keep tenant context explicit and isolated
Supply the relevant context to each evaluation instead of relying on attributes remembered from a previous request, unless the SDK contract explicitly guarantees the behavior you need. LaunchDarkly says the relevant attributes must be supplied for targeting, while OpenFeature treats evaluation context as input to dynamic evaluation. LaunchDarkly flag evaluation guidance OpenFeature Evaluation Context
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- Trace the attributes used by each flag’s targeting rules; include every decision-changing attribute in any evaluated-result cache identity.
- Keep tenant-scoped values out of shared result entries unless tenant identity and all relevant context are part of the key.
- On the client, expose only data and credentials intended for an inspectable environment; keep server-side SDK credentials on trusted infrastructure. LaunchDarkly’s SDK type guidance
Decide whether rollout assignments should move
Some deployments should let tenants receive a newer configuration as a rollout advances; others need a tenant or user to remain on one version for the duration of the deployment. AWS AppConfig documents entity-based gradual deployments that keep a user or segment on the same version during the deployment period across compute resources. AWS AppConfig deployment guidance Treat that as an AppConfig capability, not a general guarantee about other providers. If version pinning matters, make it an explicit rollout requirement rather than an accidental result of a long-lived cache.
Quick Recap
Best Value
A practical implementation checklist
- List the flags and configuration values whose decisions depend on tenant context; identify the attributes that can change each decision.
- Choose whether the SDK caches shared rules/configuration and evaluates per request, or whether the application also needs evaluated-result caching.
- If caching results, define a tenant-safe, decision-complete cache identity and a deliberate invalidation or versioning approach.
- Write the maximum tolerated staleness and the behavior for startup, disconnection, and age-limit expiry for each risk class of flag.
- Verify readiness, refresh cadence, and persistence behavior against the documentation for the exact provider and SDK or agent version in use; do not infer them from another product’s behavior.
- Decide whether rollout assignments can advance continuously or must remain pinned to a version, then confirm the chosen provider supports the required behavior.
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