Comment by prabhatsharma
Comment by prabhatsharma 18 hours ago
Opentelmetry is definitely a good thing that will help reduce vendor lock-in and exploitative practices from some vendors when they see that the customer is locked in due to the proprietary code instrumentation. In addition, opentelemetry autoinstrumentation is fantastic and allows one to get started with zero code instrumentation.
Going back to the basics - 12 factor app principles must also be adhered to in scenarios where opentelemtry might not be an option for observability. e.g. Logging is not very mature in Opentlemetry for all the languages as of now. Sending logs to stdout provides a good way to allow the infrastructure to capture logs in a vendor neutral way using standard log forwarders of your choice like fluentbit and otel-collector. Refer - https://12factor.net/logs
OTLP is a great leveler in terms of choice that allows people to switch backends seamlessly and will force vendors to be nice to customers and ensure that enough value is provided for the price.
For those who are using kubernetes you should check the opentelemtry operator, which allows you to autoinstrument your applications written in Java, NodeJS, Python, PHP and Go by adding a single annotation to your manifest file. Check an example here of sutoinstrumentation -
/-> review (python)
/
frontend (go) -> shop (nodejs) -> product (java)
\
\-> price (dotnet)Check for complete code - https://github.com/openobserve/hotcommerce
p.s. An OpenObserve maintainer here.
I'd argue that since most observability use cases are "write once, read hardly ever" they aren't really transactional (OLTP-oriented). You're doing inserts at a high rate, quick scans in real time, and a few exploratory reads when you need. Generally you're not doing upserts, overwriting existing data; you're doing time-series, where each "moment" has to be captured atomically.
Given that, it makes sense that if you have an OLAP data, like Apache Pinot, you can do the same and better than OLTP. You can do faster aggregations. Quicker large range or full table scans.
(Disclosure: I work at StarTree, which is powered by Apache Pinot)