A high number of concurrent queries can slow each other down
so that none of them is reasonbly responsive. This commit limits
the number of queries being concurrently executed.
This commit adds a relabelling stage on the set of base
labels from which a target is created. It allows to drop
targets and rewrite any regular or internal label.
This commits renames the RuleManager to Manager as the package
name is 'rules' now. The unused layer of abstraction of the
RuleManager interface is removed.
This commit changes the configuration interface from job configs to scrape
configs. This includes allowing multiple ways of target definition at once
and moving DNS SD to its own config message. DNS SD can now contain multiple
DNS names per configured discovery.
This copies the evaluation logic from the current rules/ package.
The new engine handles the execution process from query string to final result.
It provides query timeout and cancellation and general flexibility for
future changes.
functions.go: Add evaluation implementation. Slight changes to in/out data but
not to the processing logic.
quantile.go: No changes.
analyzer.go: No changes.
engine.go: Actually new part. Mainly consists of evaluation methods
which were not changed.
setup_test.go: Copy of rules/helpers_test.go to setup test storage.
promql_test.go: Copy of rules/rules_test.go.
This commit shifts responsibility for maintaining targets from providers and
pools to the target manager. Target groups have a source name that identifies
them for updates.
This commit creates a (so far unused) package. It contains the a custom
lexer/parser for the query language.
ast.go: New AST that interacts well with the parser.
lex.go: Custom lexer (new).
lex_test.go: Lexer tests (new).
parse.go: Custom parser (new).
parse_test.go: Parser tests (new).
functions.go: Changed function type, dummies for parser testing (barely changed/dummies).
printer.go: Adapted from rules/ and adjusted to new AST (mostly unchanged, few additions).
This adds the population standard deviation and
variance as aggregation functions, useful for
spotting how many standard deviations some samples
are from the mean.
