4 ms·
Until you want to know which query is slow, which metrics won't tell you. Being able to do "where query_time_ms > 5000" and then seeing the query has made some
by deathanatos 4y ago
Until you want to know which query is slow, which metrics won't tell you.
Being able to do "where query_time_ms > 5000" and then seeing the query has made some of my systems incredibly debuggable¹.
Or just finding a failing request with "where response_code = 500". Yeah, I can "grep 500", but you would be shocked at how often those characters occur by happenstance in logs "grep ' 500 '" is a bit closer but … you're just dancing around a solution engineered to do the job: structured logs.
¹and then finding out someone drew a rather large bounding box that managed to be centered precisely between and encapsulate both Philly & NYC. This kills the DB.
- adra 4y agoMost metric systems include tags, which allows you to have infinite dimensions of data correlation at your finger tips. Want the full query, or just a normalized version of the query? It should take a couple minutes in most metric engines to add such a simple requirement.
- spondyl 4y ago> Most metric systems include tags, which allows you to have infinite dimensions of data correlation at your finger tips. Unfortunately with most SaaS metric services, your credit card does not scale to support infinite dimensions of data correlation. Tagging a high cardinality value like a customer ID for example would quickly blow out your bill.
- lanstin 4y agoA mergable data type “sample values” would be awesome for these things. Host is dc1b001, api called is /whatever, p99 latency is 117 ms, status is 4xx, sample_corr_id is 0xfafedd12346