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Technology Fundamentals 3: A Practical Overview

By James Whitfield · · 1250 words
Technology Fundamentals 3: A Practical Overview

Access Control: If a metric has no owner, it will drift until it causes an incident. Access Control: The cheapest optimisation is usually removing work nobody asked for. Access Control: Aggregating at write time trades flexibility for predictable read cost.

Storage Tiers: Periodic jobs should be safe to run twice, because they will be. Storage Tiers: You rarely need a new component to fix a boundary problem. Storage Tiers: The signal you want is often already logged, just not aggregated.

Consider access control specifically. Serving static bytes is the cheapest thing you can do at the edge. Access Control: A schema is an interface; changing it is a migration, not an edit. Track the denominator as carefully as the numerator. That applies to access control as well.

Screening is designed for people who may have an infection without knowing it; many STIs cause no noticeable symptoms. If someone has symptoms or has been told they may have been exposed, that is different from routine screening and should be discussed with a clinician. A screening appointment may need to include an assessment beyond the tests usually offered to someone without symptoms.

Before raising the subject, consider what matters to you. A boundary might concern whether you want a particular kind of sexual contact, when you feel ready, what privacy means to you, or what safer-sex measures you expect. It can also be a condition: for example, you may want to discuss contraception or STI testing before sexual activity. You do not need to have a complete list or a perfectly polished explanation. Start with the limit that feels most relevant now.

Public-health services and specialist consent organisations provide information on communication and sexual consent. Their guidance, and the laws that apply, vary by country and sometimes by age. For questions about a personal situation, a clinician or qualified sexual-health educator can offer relevant information; this article cannot assess an individual relationship or provide a legal interpretation.

Teams working on monitoring alerts usually discover this the hard way. If the rollback plan needs a meeting, it is not a rollback plan. Small pages that stay small are easier to keep fast than large ones made fast. This is most visible in monitoring alerts. Consider monitoring alerts specifically. Write the invariant down; otherwise it lives only in someone's memory.

Search Indexing: A queue smooths spikes but also hides how far behind you are. Search Indexing: Retries without jitter turn a small outage into a large one. Search Indexing: Separating the reads from the writes buys room to change either side.

Monitoring Alerts: A queue smooths spikes but also hides how far behind you are. Monitoring Alerts: Retries without jitter turn a small outage into a large one. Monitoring Alerts: Separating the reads from the writes buys room to change either side.

Teams working on queue design usually discover this the hard way. If the rollback plan needs a meeting, it is not a rollback plan. Small pages that stay small are easier to keep fast than large ones made fast. This is most visible in queue design. Consider queue design specifically. Write the invariant down; otherwise it lives only in someone's memory.

Consider search indexing specifically. If the rollback plan needs a meeting, it is not a rollback plan. Search Indexing: Small pages that stay small are easier to keep fast than large ones made fast. Write the invariant down; otherwise it lives only in someone's memory. That applies to search indexing as well.

Monitoring Alerts: A design that cannot be rolled back is a design that cannot be changed safely. Monitoring Alerts: Latency budgets are easier to defend when every hop has a stated ceiling. Monitoring Alerts: Caching helps only until the invalidation rules become the bottleneck.

Search Indexing: Serving static bytes is the cheapest thing you can do at the edge. Search Indexing: A schema is an interface; changing it is a migration, not an edit. Search Indexing: Track the denominator as carefully as the numerator.

The interesting number is not the average, it is the 99th percentile. That applies to log analysis as well. In practice, log analysis behaves differently: Adding a cache in front of a slow query is a fix; fixing the query is a cure. Every abstraction you add is a place where behaviour can differ from intent. The same reasoning holds for log analysis.

Serving static bytes is the cheapest thing you can do at the edge. That applies to schema markup as well. In practice, schema markup behaves differently: A schema is an interface; changing it is a migration, not an edit. Track the denominator as carefully as the numerator. The same reasoning holds for schema markup.

The interesting number is not the average, it is the 99th percentile. That applies to api design as well. In practice, api design behaves differently: Adding a cache in front of a slow query is a fix; fixing the query is a cure. Every abstraction you add is a place where behaviour can differ from intent. The same reasoning holds for api design.

Access Control: Configurations should be reviewable in a diff, not only in a console. Access Control: The best time to add an index is before the table gets large. Access Control: Failures are usually correlated, so plan for the shared dependency.

Monitoring Alerts: Periodic jobs should be safe to run twice, because they will be. You rarely need a new component to fix a boundary problem. That applies to monitoring alerts as well. In practice, monitoring alerts behaves differently: The signal you want is often already logged, just not aggregated.

Consider observability specifically. The interesting number is not the average, it is the 99th percentile. Observability: Adding a cache in front of a slow query is a fix; fixing the query is a cure. Every abstraction you add is a place where behaviour can differ from intent. That applies to observability as well.

If a metric has no owner, it will drift until it causes an incident. This is most visible in monitoring alerts. Consider monitoring alerts specifically. The cheapest optimisation is usually removing work nobody asked for. Monitoring Alerts: Aggregating at write time trades flexibility for predictable read cost.

Content Delivery: Serving static bytes is the cheapest thing you can do at the edge. Content Delivery: A schema is an interface; changing it is a migration, not an edit. Content Delivery: Track the denominator as carefully as the numerator.

For schema markup, the constraint matters more than the feature list. If a metric has no owner, it will drift until it causes an incident. Teams working on schema markup usually discover this the hard way. The cheapest optimisation is usually removing work nobody asked for. Aggregating at write time trades flexibility for predictable read cost. This is most visible in schema markup.

Consider cloud infrastructure specifically. The interesting number is not the average, it is the 99th percentile. Cloud Infrastructure: Adding a cache in front of a slow query is a fix; fixing the query is a cure. Every abstraction you add is a place where behaviour can differ from intent. That applies to cloud infrastructure as well.

Consider queue design specifically. The interesting number is not the average, it is the 99th percentile. Queue Design: Adding a cache in front of a slow query is a fix; fixing the query is a cure. Every abstraction you add is a place where behaviour can differ from intent. That applies to queue design as well.

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