obs

obs for Observability

Insighter to aggregate observability tools

Logging, Metrics and Tracing, are the tools that we have for observability (or telemetry). The three of them share some functionality: all of them allow to set tags with values.

The package has be called obs (short form for Observability), to avoid long hard to type

Interfaces definitions

There are ongoing efforts to standarize the way to use traces, metrics and logs with the OpenTelemetry.io.

Creating our interfaces for what we need allows us to use the current libraries but easily switch to the opentelemetry library to be "vendor independent".

Insighter interface

The Insights object groups all these observability methods. In order to be easy to use, the "subsystems" should have very short name.

• T: for Traces interface
• M: for Metrics interface
• L: for Logs interface

A part from containing the other interfaces, the insights objects could provide also methods for setting tags ((key, value) pairs), that will be set automatically for all the subsystems.

Tag Definitions

Adding tags to metrics or traces can cause extra costs, and performance issues when indexing them (specially with tags that can have lots of different values).

Providing Tag Definitions when creating an Insighter object allows us to discard tags that are not defined at startup time. This restriction is only applied at the Insighter level, so if you want to bypass it you can use the ins.L / ins.M / ins.T to set the tags.

type TagDefinition struct {
	Name    string
	TagType int
	ToL     bool
	ToM     bool
	ToT     bool
}

It also allows to send those tags to each of the "subsystems" (logs, metrics, traces).

Adding tags to a log message is usually not an issue as long as those tags are not automatically used for indexing (usually log collectors have their configuration to define on what to index).

A recommendation is to define the tag names with constants, and not use something like: ins.L.Str("foo", "bar") but ind.L.Str(kTagFoo, "bar"). (This way we can later add some tool to process

Using a "builder" pattern.

In order to encapsulate the configuration for the different implementations of each subsystem, we use obtain a "builder function" at startup time per each implementation that we want to have, for each of the subsystems (Logger / Meter / Tracer).

For example, at start up time we would call:

var promMeter MeterBuilderFn

func main() {
    var err error
    var conf *PrometheusConfig = ReadPrometheusConfigFromSomewhere()
    promMeter, err = NewPrometheusMeterBuilder(log, conf)
    if err != nil {
        panic("")
    }
}

So, we could have several builder functions availabe for when we receive a new request (yep, we need a global place to have that function :/).

Usually, after that we would also create / load all the TagDefinitions (those tags that can be shared as are read only)

var (
    logrusLoggerBuilder logs.LoggerBuilderFn

    promMeterBuilder    meter.MeterBuilderFn
    ddogMeterBuilder    meter.MeterBuilderFn
    multiMeterBuileer   meter.MeterBuilderFn

    nopTracerBuilder    tracer.TracerBuilderFn
    jaegerTracerBuilder tracer.TracerBuilderFn

    insighterTagDefinitions  *obs.InsighterTagTargets
)

Steps to instantiate a new Insighter instance

• Call one of the LoggerBuilderFn that will return the Logger interface to be used

• Call the selected TracerBuilderFn and MeterBuilderFn (passing the instantiated builder).

• Call the NewInsighter constructor passing the created subsystem instances and the tag targets.

• Set any tags know at the moment of creation

For API Requests

We want to create a new Insigher instance for each request, never reuse a global one. The builder function approach allows us to select the implementation depending on configuration flags / environment.

Access to the Insights instance

FromContext

We need to have access to an Insights instance as soon as we receive a request, so it needs to be created at the outer layer of the middleware stack, and be attached to the context that is passed to other middlewares.

The obs.FromContext implementation should never return a null instance. If no Insights object has been set, a No-Op one will be returned, to avoid nil checks in "client" code, and also to have to create extra dependencies to be added in mock objects.

Extract it from the context at the controller layer

In order to reduce the amount of stuff that we retrieve from the context, we should extract the Insights instance from the context in the Controller, and pass it explictly to the use case.

A UseCase can:

• have an explicit Insights param in their function calls to be able to log, report metrics, etc...
• store the Insights instace at construction time (with .New(... , obs Insights), so all internal functions do not need to have the extra param).

Logs

Log interface styles:

• logrus style: for each message we set the additional (key, values) with want: this approach is more "free form", any logged output can have any additional key value pairs of any type.

• zerolog style: for each additional (key, value) we call a method that accepts an strong typed value (Str(key, val string), I64(key string, val int64) ...)

• struct type approach: we do not provide "free form" (key, value) to be attached to the log. Instead we must define a struct type for each log that we want to output.

Zerolog style

The zerolog style approach allows for giving more meaning to each value (as it has the type), and allows to use the optimized zerolog library ;).

struct style

This is the more strict one, and less pragmatic to write logs. The good part of this interface would be that each log output is like a Message (like the ones that could be sent through a rabbitmq), only that is written to the output, and that we could extract the type definitions from the code and have a JSON Schema. This one is a little bit overkill, but ... wouldn't be nice to have a catalog of all possible log outputs!? :)

In order to 'inherit' message attributes, we can just use embedded structs.

Metrics

The most common metrics usage are:

• counters (monotonic / not)
• rates (also called gauges, in statsd style)

Currently, I haven't seen any reference to the 'histogram' or 'distribution' in the OpenTelemetry spec. However, those are 'client side' aggregations, and perhaps is more a concern of how the underlying counter is implemented. So, at Insights object creation time, we could define some keys, that for rates, should be treated as an histogram aggregation (abstracting the client code about how that metric will be displayed).

Like in the case of logs, we can have stronger definitions (struct) of the metrics that can be used.

Traces

At some point we should start to use traces (and its Span's) to keep trace of the logic. And make sure that when we make a request to another system we include the trace in some way (a header, message field, etc..).

Structs style

About struct approach: One the problem of having structs is that prevents us from having shortcuts to set tags in all subsystems. That can be kind of solve by creating an 'InsightContext' struct with typed data, whose fields are always set for any of the the metrics, logs and traces.

Concurrency

In case of concurrency (spawning several goroutines), we should clone the Insights instance (that would cost copying an small amount of dicts ?), and pass those to the goroutines.