Latency is the number every feed buyer asks about and many vendors avoid. FeedsAI.com should face it head on. Here is how to evaluate feed latency SLAs, publish them, and keep them honest.
Define latency precisely
Vague latency claims erode trust. Define what you measure.
- End-to-end latency. Time from source publication to availability in the product or API.
- Component latency. Break down ingest, normalization, enrichment, and delivery times separately.
- Percentiles. Use p50, p90, and p95 to show real performance, not just best-case scenarios.
- Scope. Make clear whether the SLA applies to all sources or a subset. Some feeds have inherent delays.
Instrumentation to match the definition
You cannot evaluate feed latency SLAs without accurate instrumentation.
- Timestamp stamps. Capture source timestamp, fetch time, ingest time, enrichment completion, and delivery time.
- Clock sync. Keep system clocks synchronized with NTP. Clock drift ruins latency math.
- Synthetic probes. Create test items and track how fast they move through the pipeline. Use them to validate instrumentation.
- Customer perspective. Measure from the edge (API response or webhook delivery) not just internal stages.
Reporting that buyers understand
Make latency visible and legible.
- Dashboards. Publish real-time dashboards that show latency by source and by region.
- Status page. Include latency charts on the status page, not only uptime.
- Release notes. When you improve latency, note the change and the new baseline. When you regress, explain and commit to a fix window.
Set SLAs with attainable targets
Promises must match capability.
- Baseline first. Measure for at least a month before setting SLAs. Use that baseline to set ambitious but realistic targets.
- Tiered SLAs. Offer different latency targets for different feeds. For example, market-moving feeds at p95 under 4 seconds, long-form research under 30 seconds.
- Maintenance windows. Declare windows when latency may spike and how you mitigate it.
- Credits and remedies. Spell out what happens when you miss the SLA: service credits, escalation, and root-cause reports.
Runbooks and alerting
Evaluation is continuous.
- Threshold alerts. Alert when latency approaches SLA thresholds, not just when it breaches. Give teams room to intervene.
- Escalation paths. Define who responds to latency incidents and what authority they have to shed load or adjust pipelines.
- Backpressure. Implement backpressure and circuit breakers to prevent cascading failures when downstream systems slow down.
- Post-incident reviews. Publish summaries and remediation steps for latency incidents just like uptime events.
Engineering choices that lower latency
- Parallelism. Process ingestion, enrichment, and delivery in parallel where safe. Avoid serial chains when not required for correctness.
- Hot caches. Cache recent items and common queries near the edge to avoid repeated trips to slower storage.
- Batch wisely. Batch small items to reduce overhead but keep batch sizes small enough to meet percentile targets.
- Profiling. Profile each stage monthly. Small optimizations in parsing and serialization often deliver big wins.
Negotiating SLAs with customers
- Baseline sharing. Bring real data to the table: p50, p90, p95 per source. Invite customers to validate with their own probes.
- Scope clarity. Separate SLAs by source class. Market-moving data gets stricter targets than long-form research.
- Credits and make-goods. Offer meaningful service credits when you miss targets and back them with public incident reports.
- Customization guardrails. Avoid bespoke latency promises that cannot be monitored. Keep variations documented and testable.
Communicate with customers
Transparency builds trust.
- Shared dashboards. Give enterprise customers access to latency metrics for their own feeds.
- Change notifications. Announce ingest or enrichment changes that could affect latency before they roll out.
- Documentation. Include latency measurement methods in your docs so customers can reproduce results.
Customer-side validation tips
- Edge probes. Encourage customers to run probes from their own regions to compare with your published metrics.
- Replay checks. Show how to replay missed events after an outage so teams regain confidence quickly.
- Joint reviews. Offer quarterly latency reviews where you and the customer validate metrics and refresh expectations.
Positioning under FeedsAI.com
A credible domain needs credible numbers.
- Lead with latency in your marketing: “FeedsAI.com publishes latency like uptime.”
- Offer trial feeds with public latency stats so prospects can benchmark quickly.
- Build pricing tiers that align with latency guarantees.
- Keep publishing progress as improvements land.
Evaluating feed latency SLAs is about honesty and instrumentation. With disciplined measurement and transparent communication, FeedsAI.com can make latency a selling point instead of a risk.